Merge branch 'develop' into pr/yazeed/3091

docs/advanced-hyperopt.md

@@ -63,8 +63,8 @@ class SuperDuperHyperOptLoss(IHyperOptLoss):
         * 0.25: Avoiding trade loss
         * 1.0 to total profit, compared to the expected value (`EXPECTED_MAX_PROFIT`) defined above
         """
-        total_profit = results.profit_percent.sum()
-        trade_duration = results.trade_duration.mean()
+        total_profit = results['profit_percent'].sum()
+        trade_duration = results['trade_duration'].mean()
 
         trade_loss = 1 - 0.25 * exp(-(trade_count - TARGET_TRADES) ** 2 / 10 ** 5.8)
         profit_loss = max(0, 1 - total_profit / EXPECTED_MAX_PROFIT)

docs/advanced-setup.md

@@ -4,6 +4,54 @@ This page explains some advanced tasks and configuration options that can be per
 
 If you do not know what things mentioned here mean, you probably do not need it.
 
+## Running multiple instances of Freqtrade
+
+This section will show you how to run multiple bots at the same time, on the same machine.
+
+### Things to consider
+
+* Use different database files.
+* Use different Telegram bots (requires multiple different configuration files; applies only when Telegram is enabled).
+* Use different ports (applies only when Freqtrade REST API webserver is enabled).
+
+### Different database files
+
+In order to keep track of your trades, profits, etc., freqtrade is using a SQLite database where it stores various types of information such as the trades you performed in the past and the current position(s) you are holding at any time. This allows you to keep track of your profits, but most importantly, keep track of ongoing activity if the bot process would be restarted or would be terminated unexpectedly.
+
+Freqtrade will, by default, use separate database files for dry-run and live bots (this assumes no database-url is given in either configuration nor via command line argument).
+For live trading mode, the default database will be `tradesv3.sqlite` and for dry-run it will be `tradesv3.dryrun.sqlite`.
+
+The optional argument to the trade command used to specify the path of these files is `--db-url`, which requires a valid SQLAlchemy url.
+So when you are starting a bot with only the config and strategy arguments in dry-run mode, the following 2 commands would have the same outcome.
+
+``` bash
+freqtrade trade -c MyConfig.json -s MyStrategy
+# is equivalent to
+freqtrade trade -c MyConfig.json -s MyStrategy --db-url sqlite:///tradesv3.dryrun.sqlite
+```
+
+It means that if you are running the trade command in two different terminals, for example to test your strategy both for trades in USDT and in another instance for trades in BTC, you will have to run them with different databases.
+
+If you specify the URL of a database which does not exist, freqtrade will create one with the name you specified. So to test your custom strategy with BTC and USDT stake currencies, you could use the following commands (in 2 separate terminals):
+
+``` bash
+# Terminal 1:
+freqtrade trade -c MyConfigBTC.json -s MyCustomStrategy --db-url sqlite:///user_data/tradesBTC.dryrun.sqlite
+# Terminal 2:
+freqtrade trade -c MyConfigUSDT.json -s MyCustomStrategy --db-url sqlite:///user_data/tradesUSDT.dryrun.sqlite
+```
+
+Conversely, if you wish to do the same thing in production mode, you will also have to create at least one new database (in addition to the default one) and specify the path to the "live" databases, for example:
+
+``` bash
+# Terminal 1:
+freqtrade trade -c MyConfigBTC.json -s MyCustomStrategy --db-url sqlite:///user_data/tradesBTC.live.sqlite
+# Terminal 2:
+freqtrade trade -c MyConfigUSDT.json -s MyCustomStrategy --db-url sqlite:///user_data/tradesUSDT.live.sqlite
+```
+
+For more information regarding usage of the sqlite databases, for example to manually enter or remove trades, please refer to the [SQL Cheatsheet](sql_cheatsheet.md).
+
 ## Configure the bot running as a systemd service
 
 Copy the `freqtrade.service` file to your systemd user directory (usually `~/.config/systemd/user`) and update `WorkingDirectory` and `ExecStart` to match your setup.
@@ -37,30 +85,30 @@ as the watchdog.
 
 ## Advanced Logging
 
-On many Linux systems the bot can be configured to send its log messages to `syslog` or `journald` system services. Logging to a remote `syslog` server is also available on Windows. The special values for the `--logfilename` command line option can be used for this.
+On many Linux systems the bot can be configured to send its log messages to `syslog` or `journald` system services. Logging to a remote `syslog` server is also available on Windows. The special values for the `--logfile` command line option can be used for this.
 
 ### Logging to syslog
 
-To send Freqtrade log messages to a local or remote `syslog` service use the `--logfilename` command line option with the value in the following format:
+To send Freqtrade log messages to a local or remote `syslog` service use the `--logfile` command line option with the value in the following format:
 
-* `--logfilename syslog:<syslog_address>` -- send log messages to `syslog` service using the `<syslog_address>` as the syslog address.
+* `--logfile syslog:<syslog_address>` -- send log messages to `syslog` service using the `<syslog_address>` as the syslog address.
 
 The syslog address can be either a Unix domain socket (socket filename) or a UDP socket specification, consisting of IP address and UDP port, separated by the `:` character.
 
 So, the following are the examples of possible usages:
 
-* `--logfilename syslog:/dev/log` -- log to syslog (rsyslog) using the `/dev/log` socket, suitable for most systems.
-* `--logfilename syslog` -- same as above, the shortcut for `/dev/log`.
-* `--logfilename syslog:/var/run/syslog` -- log to syslog (rsyslog) using the `/var/run/syslog` socket. Use this on MacOS.
-* `--logfilename syslog:localhost:514` -- log to local syslog using UDP socket, if it listens on port 514.
-* `--logfilename syslog:<ip>:514` -- log to remote syslog at IP address and port 514. This may be used on Windows for remote logging to an external syslog server.
+* `--logfile syslog:/dev/log` -- log to syslog (rsyslog) using the `/dev/log` socket, suitable for most systems.
+* `--logfile syslog` -- same as above, the shortcut for `/dev/log`.
+* `--logfile syslog:/var/run/syslog` -- log to syslog (rsyslog) using the `/var/run/syslog` socket. Use this on MacOS.
+* `--logfile syslog:localhost:514` -- log to local syslog using UDP socket, if it listens on port 514.
+* `--logfile syslog:<ip>:514` -- log to remote syslog at IP address and port 514. This may be used on Windows for remote logging to an external syslog server.
 
 Log messages are send to `syslog` with the `user` facility. So you can see them with the following commands:
 
 * `tail -f /var/log/user`, or 
 * install a comprehensive graphical viewer (for instance, 'Log File Viewer' for Ubuntu).
 
-On many systems `syslog` (`rsyslog`) fetches data from `journald` (and vice versa), so both `--logfilename syslog` or `--logfilename journald` can be used and the messages be viewed with both `journalctl` and a syslog viewer utility. You can combine this in any way which suites you better.
+On many systems `syslog` (`rsyslog`) fetches data from `journald` (and vice versa), so both `--logfile syslog` or `--logfile journald` can be used and the messages be viewed with both `journalctl` and a syslog viewer utility. You can combine this in any way which suites you better.
 
 For `rsyslog` the messages from the bot can be redirected into a separate dedicated log file. To achieve this, add
 ```
@@ -78,9 +126,9 @@ $RepeatedMsgReduction on
 
 This needs the `systemd` python package installed as the dependency, which is not available on Windows. Hence, the whole journald logging functionality is not available for a bot running on Windows.
 
-To send Freqtrade log messages to `journald` system service use the `--logfilename` command line option with the value in the following format:
+To send Freqtrade log messages to `journald` system service use the `--logfile` command line option with the value in the following format:
 
-* `--logfilename journald` -- send log messages to `journald`.
+* `--logfile journald` -- send log messages to `journald`.
 
 Log messages are send to `journald` with the `user` facility. So you can see them with the following commands:
 
@@ -89,4 +137,4 @@ Log messages are send to `journald` with the `user` facility. So you can see the
 
 There are many other options in the `journalctl` utility to filter the messages, see manual pages for this utility.
 
-On many systems `syslog` (`rsyslog`) fetches data from `journald` (and vice versa), so both `--logfilename syslog` or `--logfilename journald` can be used and the messages be viewed with both `journalctl` and a syslog viewer utility. You can combine this in any way which suites you better.
+On many systems `syslog` (`rsyslog`) fetches data from `journald` (and vice versa), so both `--logfile syslog` or `--logfile journald` can be used and the messages be viewed with both `journalctl` and a syslog viewer utility. You can combine this in any way which suites you better.

docs/backtesting.md

@@ -12,13 +12,17 @@ real data. This is what we call
 [backtesting](https://en.wikipedia.org/wiki/Backtesting).
 
 Backtesting will use the crypto-currencies (pairs) from your config file and load historical candle (OHCLV) data from `user_data/data/<exchange>` by default.
-If no data is available for the exchange / pair / timeframe (ticker interval) combination, backtesting will ask you to download them first using `freqtrade download-data`.
+If no data is available for the exchange / pair / timeframe combination, backtesting will ask you to download them first using `freqtrade download-data`.
 For details on downloading, please refer to the [Data Downloading](data-download.md) section in the documentation.
 
 The result of backtesting will confirm if your bot has better odds of making a profit than a loss.
 
-!!! Tip "Using dynamic pairlists for backtesting"
-    While using dynamic pairlists during backtesting is not possible, a dynamic pairlist using current data can be generated via the [`test-pairlist`](utils.md#test-pairlist) command, and needs to be specified as `"pair_whitelist"` attribute in the configuration.
+!!! Warning "Using dynamic pairlists for backtesting"
+    Using dynamic pairlists is possible, however it relies on the current market conditions - which will not reflect the historic status of the pairlist.
+    Also, when using pairlists other than StaticPairlist, reproducability of backtesting-results cannot be guaranteed.
+    Please read the [pairlists documentation](configuration.md#pairlists) for more information.
+
+    To achieve reproducible results, best generate a pairlist via the [`test-pairlist`](utils.md#test-pairlist) command and use that as static pairlist.
 
 ### Run a backtesting against the currencies listed in your config file
 
@@ -31,7 +35,7 @@ freqtrade backtesting
 #### With 1 min candle (OHLCV) data
 
 ```bash
-freqtrade backtesting --ticker-interval 1m
+freqtrade backtesting --timeframe 1m
 ```
 
 #### Using a different on-disk historical candle (OHLCV) data source
@@ -54,7 +58,7 @@ Where `-s SampleStrategy` refers to the class name within the strategy file `sam
 #### Comparing multiple Strategies
 
 ```bash
-freqtrade backtesting --strategy-list SampleStrategy1 AwesomeStrategy --ticker-interval 5m
+freqtrade backtesting --strategy-list SampleStrategy1 AwesomeStrategy --timeframe 5m
 ```
 
 Where `SampleStrategy1` and `AwesomeStrategy` refer to class names of strategies.
@@ -62,7 +66,7 @@ Where `SampleStrategy1` and `AwesomeStrategy` refer to class names of strategies
 #### Exporting trades to file
 
 ```bash
-freqtrade backtesting --export trades
+freqtrade backtesting --export trades --config config.json --strategy SampleStrategy
 ```
 
 The exported trades can be used for [further analysis](#further-backtest-result-analysis), or can be used by the plotting script `plot_dataframe.py` in the scripts directory.
@@ -198,7 +202,7 @@ Since backtesting lacks some detailed information about what happens within a ca
 
 - Buys happen at open-price
 - Sell signal sells happen at open-price of the following candle
-- Low happens before high for stoploss, protecting capital first.
+- Low happens before high for stoploss, protecting capital first
 - ROI
   - sells are compared to high - but the ROI value is used (e.g. ROI = 2%, high=5% - so the sell will be at 2%)
   - sells are never "below the candle", so a ROI of 2% may result in a sell at 2.4% if low was at 2.4% profit
@@ -208,6 +212,7 @@ Since backtesting lacks some detailed information about what happens within a ca
   - High happens first - adjusting stoploss
   - Low uses the adjusted stoploss (so sells with large high-low difference are backtested correctly)
 - Sell-reason does not explain if a trade was positive or negative, just what triggered the sell (this can look odd if negative ROI values are used)
+- Stoploss (and trailing stoploss) is evaluated before ROI within one candle. So you can often see more trades with the `stoploss` and/or `trailing_stop` sell reason comparing to the results obtained with the same strategy in the Dry Run/Live Trade modes.
 
 Taking these assumptions, backtesting tries to mirror real trading as closely as possible. However, backtesting will **never** replace running a strategy in dry-run mode.
 Also, keep in mind that past results don't guarantee future success.
@@ -223,13 +228,13 @@ You can then load the trades to perform further analysis as shown in our [data a
 
 To compare multiple strategies, a list of Strategies can be provided to backtesting.
 
-This is limited to 1 timeframe (ticker interval) value per run. However, data is only loaded once from disk so if you have multiple
+This is limited to 1 timeframe value per run. However, data is only loaded once from disk so if you have multiple
 strategies you'd like to compare, this will give a nice runtime boost.
 
 All listed Strategies need to be in the same directory.
 
 ``` bash
-freqtrade backtesting --timerange 20180401-20180410 --ticker-interval 5m --strategy-list Strategy001 Strategy002 --export trades
+freqtrade backtesting --timerange 20180401-20180410 --timeframe 5m --strategy-list Strategy001 Strategy002 --export trades
 ```
 
 This will save the results to `user_data/backtest_results/backtest-result-<strategy>.json`, injecting the strategy-name into the target filename.

docs/bot-basics.md

@@ -0,0 +1,58 @@
+# Freqtrade basics
+
+This page provides you some basic concepts on how Freqtrade works and operates.
+
+## Freqtrade terminology
+
+* Trade: Open position.
+* Open Order: Order which is currently placed on the exchange, and is not yet complete.
+* Pair: Tradable pair, usually in the format of Quote/Base (e.g. XRP/USDT).
+* Timeframe: Candle length to use (e.g. `"5m"`, `"1h"`, ...).
+* Indicators: Technical indicators (SMA, EMA, RSI, ...).
+* Limit order: Limit orders which execute at the defined limit price or better.
+* Market order: Guaranteed to fill, may move price depending on the order size.
+
+## Fee handling
+
+All profit calculations of Freqtrade include fees. For Backtesting / Hyperopt / Dry-run modes, the exchange default fee is used (lowest tier on the exchange). For live operations, fees are used as applied by the exchange (this includes BNB rebates etc.).
+
+## Bot execution logic
+
+Starting freqtrade in dry-run or live mode (using `freqtrade trade`) will start the bot and start the bot iteration loop.
+By default, loop runs every few seconds (`internals.process_throttle_secs`) and does roughly the following in the following sequence:
+
+* Fetch open trades from persistence.
+* Calculate current list of tradable pairs.
+* Download ohlcv data for the pairlist including all [informative pairs](strategy-customization.md#get-data-for-non-tradeable-pairs)  
+  This step is only executed once per Candle to avoid unnecessary network traffic.
+* Call `bot_loop_start()` strategy callback.
+* Analyze strategy per pair.
+  * Call `populate_indicators()`
+  * Call `populate_buy_trend()`
+  * Call `populate_sell_trend()`
+* Check timeouts for open orders.
+  * Calls `check_buy_timeout()` strategy callback for open buy orders.
+  * Calls `check_sell_timeout()` strategy callback for open sell orders.
+* Verifies existing positions and eventually places sell orders.
+  * Considers stoploss, ROI and sell-signal.
+  * Determine sell-price based on `ask_strategy` configuration setting.
+  * Before a sell order is placed, `confirm_trade_exit()` strategy callback is called.
+* Check if trade-slots are still available (if `max_open_trades` is reached).
+* Verifies buy signal trying to enter new positions.
+  * Determine buy-price based on `bid_strategy` configuration setting.
+  * Before a buy order is placed, `confirm_trade_entry()` strategy callback is called.
+
+This loop will be repeated again and again until the bot is stopped.
+
+## Backtesting / Hyperopt execution logic
+
+[backtesting](backtesting.md) or [hyperopt](hyperopt.md) do only part of the above logic, since most of the trading operations are fully simulated.
+
+* Load historic data for configured pairlist.
+* Calculate indicators (calls `populate_indicators()`).
+* Calls `populate_buy_trend()` and `populate_sell_trend()`
+* Loops per candle simulating entry and exit points.
+* Generate backtest report output
+
+!!! Note
+    Both Backtesting and Hyperopt include exchange default Fees in the calculation. Custom fees can be passed to backtesting / hyperopt by specifying the `--fee` argument.

docs/bot-usage.md

@@ -9,22 +9,35 @@ This page explains the different parameters of the bot and how to run it.
 
 ```
 usage: freqtrade [-h] [-V]
-                 {trade,backtesting,edge,hyperopt,create-userdir,list-exchanges,list-timeframes,download-data,plot-dataframe,plot-profit}
+                 {trade,create-userdir,new-config,new-hyperopt,new-strategy,download-data,convert-data,convert-trade-data,backtesting,edge,hyperopt,hyperopt-list,hyperopt-show,list-exchanges,list-hyperopts,list-markets,list-pairs,list-strategies,list-timeframes,show-trades,test-pairlist,plot-dataframe,plot-profit}
                  ...
 
 Free, open source crypto trading bot
 
 positional arguments:
-  {trade,backtesting,edge,hyperopt,create-userdir,list-exchanges,list-timeframes,download-data,plot-dataframe,plot-profit}
+  {trade,create-userdir,new-config,new-hyperopt,new-strategy,download-data,convert-data,convert-trade-data,backtesting,edge,hyperopt,hyperopt-list,hyperopt-show,list-exchanges,list-hyperopts,list-markets,list-pairs,list-strategies,list-timeframes,show-trades,test-pairlist,plot-dataframe,plot-profit}
     trade               Trade module.
+    create-userdir      Create user-data directory.
+    new-config          Create new config
+    new-hyperopt        Create new hyperopt
+    new-strategy        Create new strategy
+    download-data       Download backtesting data.
+    convert-data        Convert candle (OHLCV) data from one format to
+                        another.
+    convert-trade-data  Convert trade data from one format to another.
     backtesting         Backtesting module.
     edge                Edge module.
     hyperopt            Hyperopt module.
-    create-userdir      Create user-data directory.
+    hyperopt-list       List Hyperopt results
+    hyperopt-show       Show details of Hyperopt results
     list-exchanges      Print available exchanges.
-    list-timeframes     Print available ticker intervals (timeframes) for the
-                        exchange.
-    download-data       Download backtesting data.
+    list-hyperopts      Print available hyperopt classes.
+    list-markets        Print markets on exchange.
+    list-pairs          Print pairs on exchange.
+    list-strategies     Print available strategies.
+    list-timeframes     Print available timeframes for the exchange.
+    show-trades         Show trades.
+    test-pairlist       Test your pairlist configuration.
     plot-dataframe      Plot candles with indicators.
     plot-profit         Generate plot showing profits.
 
@@ -72,7 +85,6 @@ Strategy arguments:
                         Specify strategy class name which will be used by the
                         bot.
   --strategy-path PATH  Specify additional strategy lookup path.
-.
 
 ```
 
@@ -144,10 +156,10 @@ It is recommended to use version control to keep track of changes to your strate
 ### How to use **--strategy**?
 
 This parameter will allow you to load your custom strategy class.
-Per default without `--strategy` or `-s` the bot will load the
-`DefaultStrategy` included with the bot (`freqtrade/strategy/default_strategy.py`).
+To test the bot installation, you can use the `SampleStrategy` installed by the `create-userdir` subcommand (usually `user_data/strategy/sample_strategy.py`).
 
-The bot will search your strategy file within `user_data/strategies` and `freqtrade/strategy`.
+The bot will search your strategy file within `user_data/strategies`.
+To use other directories, please read the next section about `--strategy-path`.
 
 To load a strategy, simply pass the class name (e.g.: `CustomStrategy`) in this parameter.
 
@@ -197,7 +209,7 @@ Backtesting also uses the config specified via `-c/--config`.
 ```
 usage: freqtrade backtesting [-h] [-v] [--logfile FILE] [-V] [-c PATH]
                              [-d PATH] [--userdir PATH] [-s NAME]
-                             [--strategy-path PATH] [-i TICKER_INTERVAL]
+                             [--strategy-path PATH] [-i TIMEFRAME]
                              [--timerange TIMERANGE] [--max-open-trades INT]
                              [--stake-amount STAKE_AMOUNT] [--fee FLOAT]
                              [--eps] [--dmmp]
@@ -206,7 +218,7 @@ usage: freqtrade backtesting [-h] [-v] [--logfile FILE] [-V] [-c PATH]
 
 optional arguments:
   -h, --help            show this help message and exit
-  -i TICKER_INTERVAL, --ticker-interval TICKER_INTERVAL
+  -i TIMEFRAME, --timeframe TIMEFRAME, --ticker-interval TIMEFRAME
                         Specify ticker interval (`1m`, `5m`, `30m`, `1h`,
                         `1d`).
   --timerange TIMERANGE
@@ -280,7 +292,7 @@ to find optimal parameter values for your strategy.
 ```
 usage: freqtrade hyperopt [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH]
                           [--userdir PATH] [-s NAME] [--strategy-path PATH]
-                          [-i TICKER_INTERVAL] [--timerange TIMERANGE]
+                          [-i TIMEFRAME] [--timerange TIMERANGE]
                           [--max-open-trades INT]
                           [--stake-amount STAKE_AMOUNT] [--fee FLOAT]
                           [--hyperopt NAME] [--hyperopt-path PATH] [--eps]
@@ -292,7 +304,7 @@ usage: freqtrade hyperopt [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH]
 
 optional arguments:
   -h, --help            show this help message and exit
-  -i TICKER_INTERVAL, --ticker-interval TICKER_INTERVAL
+  -i TIMEFRAME, --timeframe TIMEFRAME, --ticker-interval TIMEFRAME
                         Specify ticker interval (`1m`, `5m`, `30m`, `1h`,
                         `1d`).
   --timerange TIMERANGE
@@ -323,7 +335,7 @@ optional arguments:
   --print-all           Print all results, not only the best ones.
   --no-color            Disable colorization of hyperopt results. May be
                         useful if you are redirecting output to a file.
-  --print-json          Print best results in JSON format.
+  --print-json          Print output in JSON format.
   -j JOBS, --job-workers JOBS
                         The number of concurrently running jobs for
                         hyperoptimization (hyperopt worker processes). If -1
@@ -341,11 +353,11 @@ optional arguments:
                         class (IHyperOptLoss). Different functions can
                         generate completely different results, since the
                         target for optimization is different. Built-in
-                        Hyperopt-loss-functions are:
-                        DefaultHyperOptLoss, OnlyProfitHyperOptLoss,
-                        SharpeHyperOptLoss, SharpeHyperOptLossDaily,
-                        SortinoHyperOptLoss, SortinoHyperOptLossDaily.
-                        (default: `DefaultHyperOptLoss`).
+                        Hyperopt-loss-functions are: DefaultHyperOptLoss,
+                        OnlyProfitHyperOptLoss, SharpeHyperOptLoss,
+                        SharpeHyperOptLossDaily, SortinoHyperOptLoss,
+                        SortinoHyperOptLossDaily.(default:
+                        `DefaultHyperOptLoss`).
 
 Common arguments:
   -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
@@ -378,13 +390,13 @@ To know your trade expectancy and winrate against historical data, you can use E
 ```
 usage: freqtrade edge [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH]
                       [--userdir PATH] [-s NAME] [--strategy-path PATH]
-                      [-i TICKER_INTERVAL] [--timerange TIMERANGE]
+                      [-i TIMEFRAME] [--timerange TIMERANGE]
                       [--max-open-trades INT] [--stake-amount STAKE_AMOUNT]
                       [--fee FLOAT] [--stoplosses STOPLOSS_RANGE]
 
 optional arguments:
   -h, --help            show this help message and exit
-  -i TICKER_INTERVAL, --ticker-interval TICKER_INTERVAL
+  -i TIMEFRAME, --timeframe TIMEFRAME, --ticker-interval TIMEFRAME
                         Specify ticker interval (`1m`, `5m`, `30m`, `1h`,
                         `1d`).
   --timerange TIMERANGE

docs/configuration.md

@@ -34,26 +34,27 @@ The prevelance for all Options is as follows:
 
 - CLI arguments override any other option
 - Configuration files are used in sequence (last file wins), and override Strategy configurations.
-- Strategy configurations are only used if they are not set via configuration or via command line arguments. These options are market with [Strategy Override](#parameters-in-the-strategy) in the below table.
+- Strategy configurations are only used if they are not set via configuration or via command line arguments. These options are marked with [Strategy Override](#parameters-in-the-strategy) in the below table.
 
 Mandatory parameters are marked as **Required**, which means that they are required to be set in one of the possible ways.
 
 |  Parameter | Description |
 |------------|-------------|
-| `max_open_trades` | **Required.** Number of trades open your bot will have. If -1 then it is ignored (i.e. potentially unlimited open trades). [More information below](#configuring-amount-per-trade).<br> **Datatype:** Positive integer or -1.
+| `max_open_trades` | **Required.** Number of open trades your bot is allowed to have. Only one open trade per pair is possible, so the length of your pairlist is another limitation which can apply. If -1 then it is ignored (i.e. potentially unlimited open trades, limited by the pairlist). [More information below](#configuring-amount-per-trade).<br> **Datatype:** Positive integer or -1.
 | `stake_currency` | **Required.** Crypto-currency used for trading. [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** String
 | `stake_amount` | **Required.** Amount of crypto-currency your bot will use for each trade. Set it to `"unlimited"` to allow the bot to use all available balance. [More information below](#configuring-amount-per-trade). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** Positive float or `"unlimited"`.
 | `tradable_balance_ratio` | Ratio of the total account balance the bot is allowed to trade. [More information below](#configuring-amount-per-trade). <br>*Defaults to `0.99` 99%).*<br> **Datatype:** Positive float between `0.1` and `1.0`.
 | `amend_last_stake_amount` | Use reduced last stake amount if necessary. [More information below](#configuring-amount-per-trade). <br>*Defaults to `false`.* <br> **Datatype:** Boolean
 | `last_stake_amount_min_ratio` | Defines minimum stake amount that has to be left and executed. Applies only to the last stake amount when it's amended to a reduced value (i.e. if `amend_last_stake_amount` is set to `true`). [More information below](#configuring-amount-per-trade). <br>*Defaults to `0.5`.* <br> **Datatype:** Float (as ratio)
 | `amount_reserve_percent` | Reserve some amount in min pair stake amount. The bot will reserve `amount_reserve_percent` + stoploss value when calculating min pair stake amount in order to avoid possible trade refusals. <br>*Defaults to `0.05` (5%).* <br> **Datatype:** Positive Float as ratio.
-| `ticker_interval` | The timeframe (ticker interval) to use (e.g `1m`, `5m`, `15m`, `30m`, `1h` ...). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** String
+| `timeframe` | The timeframe (former ticker interval) to use (e.g `1m`, `5m`, `15m`, `30m`, `1h` ...). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** String
 | `fiat_display_currency` | Fiat currency used to show your profits. [More information below](#what-values-can-be-used-for-fiat_display_currency). <br> **Datatype:** String
 | `dry_run` | **Required.** Define if the bot must be in Dry Run or production mode. <br>*Defaults to `true`.* <br> **Datatype:** Boolean
 | `dry_run_wallet` | Define the starting amount in stake currency for the simulated wallet used by the bot running in the Dry Run mode.<br>*Defaults to `1000`.* <br> **Datatype:** Float
+| `cancel_open_orders_on_exit` | Cancel open orders when the `/stop` RPC command is issued, `Ctrl+C` is pressed or the bot dies unexpectedly. When set to `true`, this allows you to use `/stop` to cancel unfilled and partially filled orders in the event of a market crash. It does not impact open positions. <br>*Defaults to `false`.* <br> **Datatype:** Boolean
 | `process_only_new_candles` | Enable processing of indicators only when new candles arrive. If false each loop populates the indicators, this will mean the same candle is processed many times creating system load but can be useful of your strategy depends on tick data not only candle. [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `false`.*  <br> **Datatype:** Boolean
-| `minimal_roi` | **Required.** Set the threshold in percent the bot will use to sell a trade. [More information below](#understand-minimal_roi). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** Dict
-| `stoploss` |  **Required.** Value of the stoploss in percent used by the bot. More details in the [stoploss documentation](stoploss.md). [Strategy Override](#parameters-in-the-strategy).  <br> **Datatype:** Float (as ratio)
+| `minimal_roi` | **Required.** Set the threshold as ratio the bot will use to sell a trade. [More information below](#understand-minimal_roi). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** Dict
+| `stoploss` |  **Required.** Value as ratio of the stoploss used by the bot. More details in the [stoploss documentation](stoploss.md). [Strategy Override](#parameters-in-the-strategy).  <br> **Datatype:** Float (as ratio)
 | `trailing_stop` | Enables trailing stoploss (based on `stoploss` in either configuration or strategy file). More details in the [stoploss documentation](stoploss.md). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** Boolean
 | `trailing_stop_positive` | Changes stoploss once profit has been reached. More details in the [stoploss documentation](stoploss.md). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** Float
 | `trailing_stop_positive_offset` | Offset on when to apply `trailing_stop_positive`. Percentage value which should be positive. More details in the [stoploss documentation](stoploss.md). [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `0.0` (no offset).* <br> **Datatype:** Float
@@ -80,14 +81,15 @@ Mandatory parameters are marked as **Required**, which means that they are requi
 | `exchange.key` | API key to use for the exchange. Only required when you are in production mode.<br>**Keep it in secret, do not disclose publicly.** <br> **Datatype:** String
 | `exchange.secret` | API secret to use for the exchange. Only required when you are in production mode.<br>**Keep it in secret, do not disclose publicly.** <br> **Datatype:** String
 | `exchange.password` | API password to use for the exchange. Only required when you are in production mode and for exchanges that use password for API requests.<br>**Keep it in secret, do not disclose publicly.** <br> **Datatype:** String
-| `exchange.pair_whitelist` | List of pairs to use by the bot for trading and to check for potential trades during backtesting. Not used by VolumePairList (see [below](#dynamic-pairlists)). <br> **Datatype:** List
-| `exchange.pair_blacklist` | List of pairs the bot must absolutely avoid for trading and backtesting (see [below](#dynamic-pairlists)). <br> **Datatype:** List
-| `exchange.ccxt_config` | Additional CCXT parameters passed to the regular ccxt instance. Parameters may differ from exchange to exchange and are documented in the [ccxt documentation](https://ccxt.readthedocs.io/en/latest/manual.html#instantiation) <br> **Datatype:** Dict
+| `exchange.pair_whitelist` | List of pairs to use by the bot for trading and to check for potential trades during backtesting. Not used by VolumePairList (see [below](#pairlists-and-pairlist-handlers)). <br> **Datatype:** List
+| `exchange.pair_blacklist` | List of pairs the bot must absolutely avoid for trading and backtesting (see [below](#pairlists-and-pairlist-handlers)). <br> **Datatype:** List
+| `exchange.ccxt_config` | Additional CCXT parameters passed to both ccxt instances (sync and async). This is usually the correct place for ccxt configurations. Parameters may differ from exchange to exchange and are documented in the [ccxt documentation](https://ccxt.readthedocs.io/en/latest/manual.html#instantiation) <br> **Datatype:** Dict
+| `exchange.ccxt_sync_config` | Additional CCXT parameters passed to the regular (sync) ccxt instance. Parameters may differ from exchange to exchange and are documented in the [ccxt documentation](https://ccxt.readthedocs.io/en/latest/manual.html#instantiation) <br> **Datatype:** Dict
 | `exchange.ccxt_async_config` | Additional CCXT parameters passed to the async ccxt instance. Parameters may differ from exchange to exchange  and are documented in the [ccxt documentation](https://ccxt.readthedocs.io/en/latest/manual.html#instantiation) <br> **Datatype:** Dict
 | `exchange.markets_refresh_interval` | The interval in minutes in which markets are reloaded. <br>*Defaults to `60` minutes.* <br> **Datatype:** Positive Integer
 | `edge.*` | Please refer to [edge configuration document](edge.md) for detailed explanation.
 | `experimental.block_bad_exchanges` | Block exchanges known to not work with freqtrade. Leave on default unless you want to test if that exchange works now. <br>*Defaults to `true`.* <br> **Datatype:** Boolean
-| `pairlists` | Define one or more pairlists to be used. [More information below](#dynamic-pairlists). <br>*Defaults to `StaticPairList`.*  <br> **Datatype:** List of Dicts
+| `pairlists` | Define one or more pairlists to be used. [More information below](#pairlists-and-pairlist-handlers). <br>*Defaults to `StaticPairList`.*  <br> **Datatype:** List of Dicts
 | `telegram.enabled` | Enable the usage of Telegram. <br> **Datatype:** Boolean
 | `telegram.token` | Your Telegram bot token. Only required if `telegram.enabled` is `true`. <br>**Keep it in secret, do not disclose publicly.** <br> **Datatype:** String
 | `telegram.chat_id` | Your personal Telegram account id. Only required if `telegram.enabled` is `true`. <br>**Keep it in secret, do not disclose publicly.** <br> **Datatype:** String
@@ -101,14 +103,16 @@ Mandatory parameters are marked as **Required**, which means that they are requi
 | `api_server.enabled` | Enable usage of API Server. See the [API Server documentation](rest-api.md) for more details. <br> **Datatype:** Boolean
 | `api_server.listen_ip_address` | Bind IP address. See the [API Server documentation](rest-api.md) for more details. <br> **Datatype:** IPv4
 | `api_server.listen_port` | Bind Port. See the [API Server documentation](rest-api.md) for more details. <br>**Datatype:** Integer between 1024 and 65535
+| `api_server.verbosity` | Logging verbosity. `info` will print all RPC Calls, while "error" will only display errors. <br>**Datatype:** Enum, either `info` or `error`. Defaults to `info`.
 | `api_server.username` | Username for API server. See the [API Server documentation](rest-api.md) for more details. <br>**Keep it in secret, do not disclose publicly.**<br> **Datatype:** String
 | `api_server.password` | Password for API server. See the [API Server documentation](rest-api.md) for more details. <br>**Keep it in secret, do not disclose publicly.**<br> **Datatype:** String
 | `db_url` | Declares database URL to use. NOTE: This defaults to `sqlite:///tradesv3.dryrun.sqlite` if `dry_run` is `true`, and to `sqlite:///tradesv3.sqlite` for production instances. <br> **Datatype:** String, SQLAlchemy connect string
 | `initial_state` | Defines the initial application state. More information below. <br>*Defaults to `stopped`.* <br> **Datatype:** Enum, either `stopped` or `running`
 | `forcebuy_enable` | Enables the RPC Commands to force a buy. More information below. <br> **Datatype:** Boolean
+| `disable_dataframe_checks` | Disable checking the OHLCV dataframe returned from the strategy methods for correctness. Only use when intentionally changing the dataframe and understand what you are doing. [Strategy Override](#parameters-in-the-strategy).<br> *Defaults to `False`*. <br> **Datatype:** Boolean
 | `strategy` | **Required** Defines Strategy class to use. Recommended to be set via `--strategy NAME`. <br> **Datatype:** ClassName
 | `strategy_path` | Adds an additional strategy lookup path (must be a directory). <br> **Datatype:** String
-| `internals.process_throttle_secs` | Set the process throttle. Value in second. <br>*Defaults to `5` seconds.* <br> **Datatype:** Positive Intege
+| `internals.process_throttle_secs` | Set the process throttle. Value in second. <br>*Defaults to `5` seconds.* <br> **Datatype:** Positive Integer
 | `internals.heartbeat_interval` | Print heartbeat message every N seconds. Set to 0 to disable heartbeat messages. <br>*Defaults to `60` seconds.* <br> **Datatype:** Positive Integer or 0
 | `internals.sd_notify` | Enables use of the sd_notify protocol to tell systemd service manager about changes in the bot state and issue keep-alive pings. See [here](installation.md#7-optional-configure-freqtrade-as-a-systemd-service) for more details. <br> **Datatype:** Boolean
 | `logfile` | Specifies logfile name. Uses a rolling strategy for log file rotation for 10 files with the 1MB limit per file. <br> **Datatype:** String
@@ -122,7 +126,7 @@ The following parameters can be set in either configuration file or strategy.
 Values set in the configuration file always overwrite values set in the strategy.
 
 * `minimal_roi`
-* `ticker_interval`
+* `timeframe`
 * `stoploss`
 * `trailing_stop`
 * `trailing_stop_positive`
@@ -134,6 +138,7 @@ Values set in the configuration file always overwrite values set in the strategy
 * `stake_currency`
 * `stake_amount`
 * `unfilledtimeout`
+* `disable_dataframe_checks`
 * `use_sell_signal` (ask_strategy)
 * `sell_profit_only` (ask_strategy)
 * `ignore_roi_if_buy_signal` (ask_strategy)
@@ -213,7 +218,7 @@ To allow the bot to trade all the available `stake_currency` in your account (mi
 ### Understand minimal_roi
 
 The `minimal_roi` configuration parameter is a JSON object where the key is a duration
-in minutes and the value is the minimum ROI in percent.
+in minutes and the value is the minimum ROI as ratio.
 See the example below:
 
 ```json
@@ -267,10 +272,10 @@ the static list of pairs) if we should buy.
 
 ### Understand order_types
 
-The `order_types` configuration parameter maps actions (`buy`, `sell`, `stoploss`) to order-types (`market`, `limit`, ...) as well as configures stoploss to be on the exchange and defines stoploss on exchange update interval in seconds.
+The `order_types` configuration parameter maps actions (`buy`, `sell`, `stoploss`, `emergencysell`) to order-types (`market`, `limit`, ...) as well as configures stoploss to be on the exchange and defines stoploss on exchange update interval in seconds.
 
 This allows to buy using limit orders, sell using
-limit-orders, and create stoplosses using using market orders. It also allows to set the
+limit-orders, and create stoplosses using market orders. It also allows to set the
 stoploss "on exchange" which means stoploss order would be placed immediately once
 the buy order is fulfilled.
 If `stoploss_on_exchange` and `trailing_stop` are both set, then the bot will use `stoploss_on_exchange_interval` to check and update the stoploss on exchange periodically.
@@ -283,8 +288,12 @@ If this is configured, the following 4 values (`buy`, `sell`, `stoploss` and
 `emergencysell` is an optional value, which defaults to `market` and is used when creating stoploss on exchange orders fails.
 The below is the default which is used if this is not configured in either strategy or configuration file.
 
-Since `stoploss_on_exchange` uses limit orders, the exchange needs 2 prices, the stoploss_price and the Limit price.
-`stoploss` defines the stop-price - and limit should be slightly below this. This defaults to 0.99 / 1% (configurable via `stoploss_on_exchange_limit_ratio`).
+Not all Exchanges support `stoploss_on_exchange`. If an exchange supports both limit and market stoploss orders, then the value of `stoploss` will be used to determine the stoploss type.
+
+If `stoploss_on_exchange` uses limit orders, the exchange needs 2 prices, the stoploss_price and the Limit price.
+`stoploss` defines the stop-price - and limit should be slightly below this.
+
+This defaults to 0.99 / 1% (configurable via `stoploss_on_exchange_limit_ratio`).
 Calculation example: we bought the asset at 100$.
 Stop-price is 95$, then limit would be `95 * 0.99 = 94.05$` - so the stoploss will happen between 95$ and 94.05$.
 
@@ -326,7 +335,10 @@ Configuration:
     refer to [the stoploss documentation](stoploss.md).
 
 !!! Note
-    If `stoploss_on_exchange` is enabled and the stoploss is cancelled manually on the exchange, then the bot will create a new order.
+    If `stoploss_on_exchange` is enabled and the stoploss is cancelled manually on the exchange, then the bot will create a new stoploss order.
+
+!!! Warning "Using market orders"
+    Please read the section [Market order pricing](#market-order-pricing) section when using market orders.
 
 !!! Warning "Warning: stoploss_on_exchange failures"
     If stoploss on exchange creation fails for some reason, then an "emergency sell" is initiated. By default, this will sell the asset using a market order. The order-type for the emergency-sell can be changed by setting the `emergencysell` value in the `order_types` dictionary - however this is not advised.
@@ -454,6 +466,9 @@ Prices are always retrieved right before an order is placed, either by querying
 !!! Note
     Orderbook data used by Freqtrade are the data retrieved from exchange by the ccxt's function `fetch_order_book()`, i.e. are usually data from the L2-aggregated orderbook, while the ticker data are the structures returned by the ccxt's `fetch_ticker()`/`fetch_tickers()` functions. Refer to the ccxt library [documentation](https://github.com/ccxt/ccxt/wiki/Manual#market-data) for more details.
 
+!!! Warning "Using market orders"
+    Please read the section [Market order pricing](#market-order-pricing) section when using market orders.
+
 ### Buy price
 
 #### Check depth of market
@@ -544,32 +559,57 @@ A fixed slot (mirroring `bid_strategy.order_book_top`) can be defined by setting
     Using `ask_strategy.order_book_max` higher than 1 will result in improper dry-run results (significantly better than real orders executed on exchange), since dry-run assumes orders to be filled almost instantly.
     It is therefore advised to not use this setting for dry-runs.
 
-
 #### Sell price without Orderbook enabled
 
 When not using orderbook (`ask_strategy.use_order_book=False`), the price at the `ask_strategy.price_side` side (defaults to `"ask"`) from the ticker will be used as the sell price.
 
-## Pairlists
+### Market order pricing
 
-Pairlists define the list of pairs that the bot should trade.
-There are [`StaticPairList`](#static-pair-list) and dynamic Whitelists available.
+When using market orders, prices should be configured to use the "correct" side of the orderbook to allow realistic pricing detection.
+Assuming both buy and sell are using market orders, a configuration similar to the following might be used
 
-[`PrecisionFilter`](#precision-filter) and [`PriceFilter`](#price-pair-filter) act as filters, removing low-value pairs.
+``` jsonc
+  "order_types": {
+    "buy": "market",
+    "sell": "market"
+    // ...
+  },
+  "bid_strategy": {
+    "price_side": "ask",
+    // ...
+  },
+  "ask_strategy":{
+    "price_side": "bid",
+    // ...
+  },
+```
 
-All pairlists can be chained, and a combination of all pairlists will become your new whitelist. Pairlists are executed in the sequence they are configured. You should always configure either `StaticPairList` or `DynamicPairList` as starting pairlists.
+Obviously, if only one side is using limit orders, different pricing combinations can be used.
 
-Inactive markets and blacklisted pairs are always removed from the resulting `pair_whitelist`.
+## Pairlists and Pairlist Handlers
 
-### Available Pairlists
+Pairlist Handlers define the list of pairs (pairlist) that the bot should trade. They are configured in the `pairlists` section of the configuration settings.
+
+In your configuration, you can use Static Pairlist (defined by the [`StaticPairList`](#static-pair-list) Pairlist Handler) and Dynamic Pairlist (defined by the [`VolumePairList`](#volume-pair-list) Pairlist Handler).
+
+Additionaly, [`AgeFilter`](#agefilter), [`PrecisionFilter`](#precisionfilter), [`PriceFilter`](#pricefilter), [`ShuffleFilter`](#shufflefilter) and [`SpreadFilter`](#spreadfilter) act as Pairlist Filters, removing certain pairs and/or moving their positions in the pairlist.
+
+If multiple Pairlist Handlers are used, they are chained and a combination of all Pairlist Handlers forms the resulting pairlist the bot uses for trading and backtesting. Pairlist Handlers are executed in the sequence they are configured. You should always configure either `StaticPairList` or `VolumePairList` as the starting Pairlist Handler.
+
+Inactive markets are always removed from the resulting pairlist. Explicitly blacklisted pairs (those in the `pair_blacklist` configuration setting) are also always removed from the resulting pairlist.
+
+### Available Pairlist Handlers
 
 * [`StaticPairList`](#static-pair-list) (default, if not configured differently)
 * [`VolumePairList`](#volume-pair-list)
-* [`PrecisionFilter`](#precision-filter)
-* [`PriceFilter`](#price-pair-filter)
-* [`SpreadFilter`](#spread-filter)
+* [`AgeFilter`](#agefilter)
+* [`PrecisionFilter`](#precisionfilter)
+* [`PriceFilter`](#pricefilter)
+* [`ShuffleFilter`](#shufflefilter)
+* [`SpreadFilter`](#spreadfilter)
 
 !!! Tip "Testing pairlists"
-    Pairlist configurations can be quite tricky to get right. Best use the [`test-pairlist`](utils.md#test-pairlist) subcommand to test your configuration quickly.
+    Pairlist configurations can be quite tricky to get right. Best use the [`test-pairlist`](utils.md#test-pairlist) utility subcommand to test your configuration quickly.
 
 #### Static Pair List
 
@@ -585,16 +625,16 @@ It uses configuration from `exchange.pair_whitelist` and `exchange.pair_blacklis
 
 #### Volume Pair List
 
-`VolumePairList` selects `number_assets` top pairs based on `sort_key`, which can be one of `askVolume`, `bidVolume` and `quoteVolume` and defaults to `quoteVolume`.
+`VolumePairList` employs sorting/filtering of pairs by their trading volume. It selects `number_assets` top pairs with sorting based on the `sort_key` (which can only be `quoteVolume`).
 
-`VolumePairList` considers outputs of previous pairlists unless  it's the first configured pairlist, it does not consider `pair_whitelist`, but selects the top assets from all available markets (with matching stake-currency) on the exchange.
+When used in the chain of Pairlist Handlers in a non-leading position (after StaticPairList and other Pairlist Filters), `VolumePairList` considers outputs of previous Pairlist Handlers, adding its sorting/selection of the pairs by the trading volume.
 
-`refresh_period` allows setting the period (in seconds), at which the pairlist will be refreshed. Defaults to 1800s (30 minutes).
+When used on the leading position of the chain of Pairlist Handlers, it does not consider `pair_whitelist` configuration setting, but selects the top assets from all available markets (with matching stake-currency) on the exchange.
 
-`VolumePairList` is based on the ticker data, as reported by the ccxt library:
+The `refresh_period` setting allows to define the period (in seconds), at which the pairlist will be refreshed. Defaults to 1800s (30 minutes).
+
+`VolumePairList` is based on the ticker data from exchange, as reported by the ccxt library:
 
-* The `bidVolume` is the volume (amount) of current best bid in the orderbook.
-* The `askVolume` is the volume (amount) of current best ask in the orderbook.
 * The `quoteVolume` is the amount of quote (stake) currency traded (bought or sold) in last 24 hours.
 
 ```json
@@ -603,32 +643,63 @@ It uses configuration from `exchange.pair_whitelist` and `exchange.pair_blacklis
         "number_assets": 20,
         "sort_key": "quoteVolume",
         "refresh_period": 1800,
-],
+}],
 ```
 
-#### Precision Filter
+#### AgeFilter
 
-Filters low-value coins which would not allow setting a stoploss.
+Removes pairs that have been listed on the exchange for less than `min_days_listed` days (defaults to `10`).
 
-#### Price Pair Filter
+When pairs are first listed on an exchange they can suffer huge price drops and volatility
+in the first few days while the pair goes through its price-discovery period. Bots can often
+be caught out buying before the pair has finished dropping in price.
 
-The `PriceFilter` allows filtering of pairs by price.
-Currently, only `low_price_ratio` is implemented, where a raise of 1 price unit (pip) is below the `low_price_ratio` ratio.
+This filter allows freqtrade to ignore pairs until they have been listed for at least `min_days_listed` days.
+
+#### PrecisionFilter
+
+Filters low-value coins which would not allow setting stoplosses.
+
+#### PriceFilter
+
+The `PriceFilter` allows filtering of pairs by price. Currently the following price filters are supported:
+* `min_price`
+* `max_price`
+* `low_price_ratio`
+
+The `min_price` setting removes pairs where the price is below the specified price. This is useful if you wish to avoid trading very low-priced pairs.
 This option is disabled by default, and will only apply if set to <> 0.
 
-Calculation example:  
-Min price precision is 8 decimals. If price is 0.00000011 - one step would be 0.00000012 - which is almost 10% higher than the previous value. 
+The `max_price` setting removes pairs where the price is above the specified price. This is useful if you wish to trade only low-priced pairs.
+This option is disabled by default, and will only apply if set to <> 0.
+
+The `low_price_ratio` setting removes pairs where a raise of 1 price unit (pip) is above the `low_price_ratio` ratio.
+This option is disabled by default, and will only apply if set to <> 0.
+
+Calculation example:
+
+Min price precision is 8 decimals. If price is 0.00000011 - one step would be 0.00000012 - which is almost 10% higher than the previous value.
 
 These pairs are dangerous since it may be impossible to place the desired stoploss - and often result in high losses.
 
-#### Spread Filter
-Removes pairs that have a difference between asks and bids above the specified ratio (default `0.005`).
+#### ShuffleFilter
+
+Shuffles (randomizes) pairs in the pairlist. It can be used for preventing the bot from trading some of the pairs more frequently then others when you want all pairs be treated with the same priority.
+
+!!! Tip
+    You may set the `seed` value for this Pairlist to obtain reproducible results, which can be useful for repeated backtesting sessions. If `seed` is not set, the pairs are shuffled in the non-repeatable random order.
+
+#### SpreadFilter
+
+Removes pairs that have a difference between asks and bids above the specified ratio, `max_spread_ratio` (defaults to `0.005`).
+
 Example:
-If `DOGE/BTC` maximum bid is 0.00000026 and minimum ask is 0.00000027 the ratio is calculated as: `1 - bid/ask ~= 0.037` which is `> 0.005` 
 
-### Full Pairlist example
+If `DOGE/BTC` maximum bid is 0.00000026 and minimum ask is 0.00000027, the ratio is calculated as: `1 - bid/ask ~= 0.037` which is `> 0.005` and this pair will be filtered out.
 
-The below example blacklists `BNB/BTC`, uses `VolumePairList` with `20` assets, sorting by `quoteVolume` and applies both [`PrecisionFilter`](#precision-filter) and [`PriceFilter`](#price-pair-filter), filtering all assets where 1 priceunit is > 1%.
+### Full example of Pairlist Handlers
+
+The below example blacklists `BNB/BTC`, uses `VolumePairList` with `20` assets, sorting pairs by `quoteVolume` and applies both [`PrecisionFilter`](#precisionfilter) and [`PriceFilter`](#price-filter), filtering all assets where 1 priceunit is > 1%. Then the `SpreadFilter` is applied and pairs are finally shuffled with the random seed set to some predefined value.
 
 ```json
 "exchange": {
@@ -641,8 +712,11 @@ The below example blacklists `BNB/BTC`, uses `VolumePairList` with `20` assets,
         "number_assets": 20,
         "sort_key": "quoteVolume",
     },
+    {"method": "AgeFilter", "min_days_listed": 10},
     {"method": "PrecisionFilter"},
-    {"method": "PriceFilter", "low_price_ratio": 0.01}
+    {"method": "PriceFilter", "low_price_ratio": 0.01},
+    {"method": "SpreadFilter", "max_spread_ratio": 0.005},
+    {"method": "ShuffleFilter", "seed": 42}
     ],
 ```
 

docs/data-download.md

@@ -109,7 +109,7 @@ The following command will convert all candle (OHLCV) data available in `~/.freq
 It'll also remove original json data files (`--erase` parameter).
 
 ``` bash
-freqtrade convert-data --format-from json --format-to jsongz --data-dir ~/.freqtrade/data/binance -t 5m 15m --erase
+freqtrade convert-data --format-from json --format-to jsongz --datadir ~/.freqtrade/data/binance -t 5m 15m --erase
 ```
 
 #### Subcommand convert-trade data
@@ -155,7 +155,59 @@ The following command will convert all available trade-data in `~/.freqtrade/dat
 It'll also remove original jsongz data files (`--erase` parameter).
 
 ``` bash
-freqtrade convert-trade-data --format-from jsongz --format-to json --data-dir ~/.freqtrade/data/kraken --erase
+freqtrade convert-trade-data --format-from jsongz --format-to json --datadir ~/.freqtrade/data/kraken --erase
+```
+
+### Subcommand list-data
+
+You can get a list of downloaded data using the `list-data` subcommand.
+
+```
+usage: freqtrade list-data [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH]
+                           [--userdir PATH] [--exchange EXCHANGE]
+                           [--data-format-ohlcv {json,jsongz}]
+                           [-p PAIRS [PAIRS ...]]
+
+optional arguments:
+  -h, --help            show this help message and exit
+  --exchange EXCHANGE   Exchange name (default: `bittrex`). Only valid if no
+                        config is provided.
+  --data-format-ohlcv {json,jsongz}
+                        Storage format for downloaded candle (OHLCV) data.
+                        (default: `json`).
+  -p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...]
+                        Show profits for only these pairs. Pairs are space-
+                        separated.
+
+Common arguments:
+  -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
+  --logfile FILE        Log to the file specified. Special values are:
+                        'syslog', 'journald'. See the documentation for more
+                        details.
+  -V, --version         show program's version number and exit
+  -c PATH, --config PATH
+                        Specify configuration file (default:
+                        `userdir/config.json` or `config.json` whichever
+                        exists). Multiple --config options may be used. Can be
+                        set to `-` to read config from stdin.
+  -d PATH, --datadir PATH
+                        Path to directory with historical backtesting data.
+  --userdir PATH, --user-data-dir PATH
+                        Path to userdata directory.
+```
+
+#### Example list-data
+
+```bash
+> freqtrade list-data --userdir ~/.freqtrade/user_data/
+
+Found 33 pair / timeframe combinations.
+pairs       timeframe
+----------  -----------------------------------------
+ADA/BTC     5m, 15m, 30m, 1h, 2h, 4h, 6h, 12h, 1d
+ADA/ETH     5m, 15m, 30m, 1h, 2h, 4h, 6h, 12h, 1d
+ETH/BTC     5m, 15m, 30m, 1h, 2h, 4h, 6h, 12h, 1d
+ETH/USDT    5m, 15m, 30m, 1h, 2h, 4h
 ```
 
 ### Pairs file

docs/deprecated.md

@@ -24,3 +24,13 @@ and in freqtrade 2019.7 (master branch).
 `--live` in the context of backtesting allowed to download the latest tick data for backtesting.
 Did only download the latest 500 candles, so was ineffective in getting good backtest data.
 Removed in 2019-7-dev (develop branch) and in freqtrade 2019-8 (master branch)
+
+### Allow running multiple pairlists in sequence
+
+The former `"pairlist"` section in the configuration has been removed, and is replaced by `"pairlists"` - being a list to specify a sequence of pairlists.
+
+The old section of configuration parameters (`"pairlist"`) has been deprecated in 2019.11 and has been removed in 2020.4.
+
+### deprecation of bidVolume and askVolume from volumepairlist
+
+Since only quoteVolume can be compared between assets, the other options (bidVolume, askVolume) have been deprecated in 2020.4.

docs/developer.md

@@ -92,13 +92,13 @@ docker-compose exec freqtrade_develop /bin/bash
 You have a great idea for a new pair selection algorithm you would like to try out? Great.
 Hopefully you also want to contribute this back upstream.
 
-Whatever your motivations are - This should get you off the ground in trying to develop a new Pairlist provider.
+Whatever your motivations are - This should get you off the ground in trying to develop a new Pairlist Handler.
 
-First of all, have a look at the [VolumePairList](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/pairlist/VolumePairList.py) provider, and best copy this file with a name of your new Pairlist Provider.
+First of all, have a look at the [VolumePairList](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/pairlist/VolumePairList.py) Handler, and best copy this file with a name of your new Pairlist Handler.
 
-This is a simple provider, which however serves as a good example on how to start developing.
+This is a simple Handler, which however serves as a good example on how to start developing.
 
-Next, modify the classname of the provider (ideally align this with the Filename).
+Next, modify the classname of the Handler (ideally align this with the module filename).
 
 The base-class provides an instance of the exchange (`self._exchange`) the pairlist manager (`self._pairlistmanager`), as well as the main configuration (`self._config`), the pairlist dedicated configuration (`self._pairlistconfig`) and the absolute position within the list of pairlists.
 
@@ -114,28 +114,44 @@ Now, let's step through the methods which require actions:
 
 #### Pairlist configuration
 
-Configuration for PairListProvider is done in the bot configuration file in the element `"pairlist"`.
-This Pairlist-object may contain configurations with additional configurations for the configured pairlist.
-By convention, `"number_assets"` is used to specify the maximum number of pairs to keep in the whitelist. Please follow this to ensure a consistent user experience.
+Configuration for the chain of Pairlist Handlers is done in the bot configuration file in the element `"pairlists"`, an array of configuration parameters for each Pairlist Handlers in the chain.
 
-Additional elements can be configured as needed. `VolumePairList` uses `"sort_key"` to specify the sorting value - however feel free to specify whatever is necessary for your great algorithm to be successfull and dynamic.
+By convention, `"number_assets"` is used to specify the maximum number of pairs to keep in the pairlist. Please follow this to ensure a consistent user experience.
+
+Additional parameters can be configured as needed. For instance, `VolumePairList` uses `"sort_key"` to specify the sorting value - however feel free to specify whatever is necessary for your great algorithm to be successfull and dynamic.
 
 #### short_desc
 
 Returns a description used for Telegram messages.
-This should contain the name of the Provider, as well as a short description containing the number of assets. Please follow the format `"PairlistName - top/bottom X pairs"`.
+
+This should contain the name of the Pairlist Handler, as well as a short description containing the number of assets. Please follow the format `"PairlistName - top/bottom X pairs"`.
+
+#### gen_pairlist
+
+Override this method if the Pairlist Handler can be used as the leading Pairlist Handler in the chain, defining the initial pairlist which is then handled by all Pairlist Handlers in the chain. Examples are `StaticPairList` and `VolumePairList`.
+
+This is called with each iteration of the bot (only if the Pairlist Handler is at the first location) - so consider implementing caching for compute/network heavy calculations.
+
+It must return the resulting pairlist (which may then be passed into the chain of Pairlist Handlers).
+
+Validations are optional, the parent class exposes a `_verify_blacklist(pairlist)` and `_whitelist_for_active_markets(pairlist)` to do default filtering. Use this if you limit your result to a certain number of pairs - so the endresult is not shorter than expected.
 
 #### filter_pairlist
 
-Override this method and run all calculations needed in this method.
+This method is called for each Pairlist Handler in the chain by the pairlist manager.
+
 This is called with each iteration of the bot - so consider implementing caching for compute/network heavy calculations.
 
 It get's passed a pairlist (which can be the result of previous pairlists) as well as `tickers`, a pre-fetched version of `get_tickers()`.
 
-It must return the resulting pairlist (which may then be passed into the next pairlist filter).
+The default implementation in the base class simply calls the `_validate_pair()` method for each pair in the pairlist, but you may override it. So you should either implement the `_validate_pair()` in your Pairlist Handler or override `filter_pairlist()` to do something else.
+
+If overridden, it must return the resulting pairlist (which may then be passed into the next Pairlist Handler in the chain).
 
 Validations are optional, the parent class exposes a `_verify_blacklist(pairlist)` and `_whitelist_for_active_markets(pairlist)` to do default filters. Use this if you limit your result to a certain number of pairs - so the endresult is not shorter than expected.
 
+In `VolumePairList`, this implements different methods of sorting, does early validation so only the expected number of pairs is returned.
+
 ##### sample
 
 ``` python
@@ -145,11 +161,6 @@ Validations are optional, the parent class exposes a `_verify_blacklist(pairlist
         return pairs
 ```
 
-#### _gen_pair_whitelist
-
-This is a simple method used by `VolumePairList` - however serves as a good example.
-In VolumePairList, this implements different methods of sorting, does early validation so only the expected number of pairs is returned.
-
 ## Implement a new Exchange (WIP)
 
 !!! Note

docs/docker.md

@@ -22,6 +22,9 @@ Freqtrade provides an official Docker image on [Dockerhub](https://hub.docker.co
 !!! Note
     All below comands use relative directories and will have to be executed from the directory containing the `docker-compose.yml` file.
 
+!!! Note "Docker on Raspberry"
+    If you're running freqtrade on a Raspberry PI, you must change the image from `freqtradeorg/freqtrade:master` to `freqtradeorg/freqtrade:master_pi` or `freqtradeorg/freqtrade:develop_pi`, otherwise the image will not work.
+
 ### Docker quick start
 
 Create a new directory and place the [docker-compose file](https://github.com/freqtrade/freqtrade/blob/develop/docker-compose.yml) in this directory.
@@ -65,7 +68,7 @@ docker-compose up -d
 
 #### Docker-compose logs
 
-Logs will be written to `user_data/freqtrade.log`. 
+Logs will be written to `user_data/logs/freqtrade.log`. 
 Alternatively, you can check the latest logs using `docker-compose logs -f`.
 
 #### Database

docs/edge.md

@@ -79,7 +79,7 @@ So lets say your Win rate is 28% and your Risk Reward Ratio is 5:
 Expectancy = (5 X 0.28) – 0.72 = 0.68
 ```
 
-Superficially, this means that on average you expect this strategy’s trades to return .68 times the size of your loses. This is important for two reasons: First, it may seem obvious, but you know right away that you have a positive return. Second, you now have a number you can compare to other candidate systems to make decisions about which ones you employ.
+Superficially, this means that on average you expect this strategy’s trades to return 1.68 times the size of your loses. Said another way, you can expect to win $1.68 for every $1 you lose. This is important for two reasons: First, it may seem obvious, but you know right away that you have a positive return. Second, you now have a number you can compare to other candidate systems to make decisions about which ones you employ.
 
 It is important to remember that any system with an expectancy greater than 0 is profitable using past data. The key is finding one that will be profitable in the future.
 
@@ -148,7 +148,6 @@ Edge module has following configuration options:
 | `enabled` | If true, then Edge will run periodically. <br>*Defaults to `false`.* <br> **Datatype:** Boolean
 | `process_throttle_secs` | How often should Edge run in seconds. <br>*Defaults to `3600` (once per hour).* <br> **Datatype:** Integer
 | `calculate_since_number_of_days` | Number of days of data against which Edge calculates Win Rate, Risk Reward and Expectancy. <br> **Note** that it downloads historical data so increasing this number would lead to slowing down the bot. <br>*Defaults to `7`.* <br> **Datatype:** Integer
-| `capital_available_percentage` | **DEPRECATED - [replaced with `tradable_balance_ratio`](configuration.md#Available balance)** This is the percentage of the total capital on exchange in stake currency. <br>As an example if you have 10 ETH available in your wallet on the exchange and this value is 0.5 (which is 50%), then the bot will use a maximum amount of 5 ETH for trading and considers it as available capital. <br>*Defaults to `0.5`.* <br> **Datatype:** Float
 | `allowed_risk` | Ratio of allowed risk per trade. <br>*Defaults to `0.01` (1%)).* <br> **Datatype:** Float
 | `stoploss_range_min` | Minimum stoploss. <br>*Defaults to `-0.01`.* <br> **Datatype:** Float
 | `stoploss_range_max` | Maximum stoploss. <br>*Defaults to `-0.10`.* <br> **Datatype:** Float
@@ -156,7 +155,7 @@ Edge module has following configuration options:
 | `minimum_winrate` | It filters out pairs which don't have at least minimum_winrate. <br>This comes handy if you want to be conservative and don't comprise win rate in favour of risk reward ratio. <br>*Defaults to `0.60`.* <br> **Datatype:** Float
 | `minimum_expectancy` | It filters out pairs which have the expectancy lower than this number. <br>Having an expectancy of 0.20 means if you put 10$ on a trade you expect a 12$ return. <br>*Defaults to `0.20`.* <br> **Datatype:** Float
 | `min_trade_number` | When calculating *W*, *R* and *E* (expectancy) against historical data, you always want to have a minimum number of trades. The more this number is the more Edge is reliable. <br>Having a win rate of 100% on a single trade doesn't mean anything at all. But having a win rate of 70% over past 100 trades means clearly something. <br>*Defaults to `10` (it is highly recommended not to decrease this number).* <br> **Datatype:** Integer
-| `max_trade_duration_minute` | Edge will filter out trades with long duration. If a trade is profitable after 1 month, it is hard to evaluate the strategy based on it. But if most of trades are profitable and they have maximum duration of 30 minutes, then it is clearly a good sign.<br>**NOTICE:** While configuring this value, you should take into consideration your timeframe (ticker interval). As an example filtering out trades having duration less than one day for a strategy which has 4h interval does not make sense. Default value is set assuming your strategy interval is relatively small (1m or 5m, etc.).<br>*Defaults to `1440` (one day).* <br> **Datatype:** Integer
+| `max_trade_duration_minute` | Edge will filter out trades with long duration. If a trade is profitable after 1 month, it is hard to evaluate the strategy based on it. But if most of trades are profitable and they have maximum duration of 30 minutes, then it is clearly a good sign.<br>**NOTICE:** While configuring this value, you should take into consideration your timeframe. As an example filtering out trades having duration less than one day for a strategy which has 4h interval does not make sense. Default value is set assuming your strategy interval is relatively small (1m or 5m, etc.).<br>*Defaults to `1440` (one day).* <br> **Datatype:** Integer
 | `remove_pumps` | Edge will remove sudden pumps in a given market while going through historical data. However, given that pumps happen very often in crypto markets, we recommend you keep this off.<br>*Defaults to `false`.* <br> **Datatype:** Boolean
 
 ## Running Edge independently

docs/exchanges.md

@@ -30,6 +30,15 @@ Binance has been split into 3, and users must use the correct ccxt exchange ID f
 The Kraken API does only provide 720 historic candles, which is sufficient for Freqtrade dry-run and live trade modes, but is a problem for backtesting.
 To download data for the Kraken exchange, using `--dl-trades` is mandatory, otherwise the bot will download the same 720 candles over and over, and you'll not have enough backtest data.
 
+Due to the heavy rate-limiting applied by Kraken, the following configuration section should be used to download data:
+
+``` json
+    "ccxt_async_config": {
+        "enableRateLimit": true,
+        "rateLimit": 3100
+    },
+```
+
 ## Bittrex
 
 ### Order types
@@ -62,6 +71,30 @@ res = [ f"{x['MarketCurrency']}/{x['BaseCurrency']}" for x in ct.publicGetMarket
 print(res)
 ```
 
+## FTX
+
+!!! Tip "Stoploss on Exchange"
+    FTX supports `stoploss_on_exchange` and can use both stop-loss-market and stop-loss-limit orders. It provides great advantages, so we recommend to benefit from it.
+    You can use either `"limit"` or `"market"` in the `order_types.stoploss` configuration setting to decide.
+
+
+### Using subaccounts
+
+To use subaccounts with FTX, you need to edit the configuration and add the following:
+
+``` json
+"exchange": {
+    "ccxt_config": {
+        "headers": {
+            "FTX-SUBACCOUNT": "name"
+        }
+    },
+}
+```
+
+!!! Note
+    Older versions of freqtrade may require this key to be added to `"ccxt_async_config"` as well.
+
 ## All exchanges
 
 Should you experience constant errors with Nonce (like `InvalidNonce`), it is best to regenerate the API keys. Resetting Nonce is difficult and it's usually easier to regenerate the API keys.
@@ -74,23 +107,13 @@ Should you experience constant errors with Nonce (like `InvalidNonce`), it is be
 $ pip3 install web3
 ```
 
-### Send incomplete candles to the strategy
+### Getting latest price / Incomplete candles
 
 Most exchanges return current incomplete candle via their OHLCV/klines API interface.
 By default, Freqtrade assumes that incomplete candle is fetched from the exchange and removes the last candle assuming it's the incomplete candle.
 
 Whether your exchange returns incomplete candles or not can be checked using [the helper script](developer.md#Incomplete-candles) from the Contributor documentation.
 
-If the exchange does return incomplete candles and you would like to have incomplete candles in your strategy, you can set the following parameter in the configuration file.
+Due to the danger of repainting, Freqtrade does not allow you to use this incomplete candle.
 
-``` json
-{
-
-    "exchange": {
-        "_ft_has_params": {"ohlcv_partial_candle": false}
-    }
-}
-```
-
-!!! Warning "Danger of repainting"
-    Changing this parameter makes the strategy responsible to avoid repainting and handle this accordingly. Doing this is therefore not recommended, and should only be performed by experienced users who are fully aware of the impact this setting has.
+However, if it is based on the need for the latest price for your strategy - then this requirement can be acquired using the [data provider](strategy-customization.md#possible-options-for-dataprovider) from within the strategy.

docs/faq.md

@@ -45,6 +45,20 @@ the tutorial [here|Testing-new-strategies-with-Hyperopt](bot-usage.md#hyperopt-c
 
 You can use the `/forcesell all` command from Telegram.
 
+### I want to run multiple bots on the same machine
+
+Please look at the [advanced setup documentation Page](advanced-setup.md#running-multiple-instances-of-freqtrade).
+
+### I'm getting "Missing data fillup" messages in the log
+
+This message is just a warning that the latest candles had missing candles in them.
+Depending on the exchange, this can indicate that the pair didn't have a trade for the timeframe you are using - and the exchange does only return candles with volume.
+On low volume pairs, this is a rather common occurance.
+
+If this happens for all pairs in the pairlist, this might indicate a recent exchange downtime. Please check your exchange's public channels for details.
+
+Irrespectively of the reason, Freqtrade will fill up these candles with "empty" candles, where open, high, low and close are set to the previous candle close - and volume is empty. In a chart, this will look like a `_` - and is aligned with how exchanges usually represent 0 volume candles.
+
 ### I'm getting the "RESTRICTED_MARKET" message in the log
 
 Currently known to happen for US Bittrex users.  
@@ -100,7 +114,7 @@ $ tail -f /path/to/mylogfile.log | grep 'something'
 ```
 from a separate terminal window.
 
-On Windows, the `--logfilename` option is also supported by Freqtrade and you can use the `findstr` command to search the log for the string of interest:
+On Windows, the `--logfile` option is also supported by Freqtrade and you can use the `findstr` command to search the log for the string of interest:
 ```
 > type \path\to\mylogfile.log | findstr "something"
 ```

docs/hyperopt.md

@@ -6,9 +6,7 @@ algorithms included in the `scikit-optimize` package to accomplish this. The
 search will burn all your CPU cores, make your laptop sound like a fighter jet
 and still take a long time.
 
-In general, the search for best parameters starts with a few random combinations and then uses Bayesian search with a
-ML regressor algorithm (currently ExtraTreesRegressor) to quickly find a combination of parameters in the search hyperspace
-that minimizes the value of the [loss function](#loss-functions).
+In general, the search for best parameters starts with a few random combinations (see [below](#reproducible-results) for more details) and then uses Bayesian search with a ML regressor algorithm (currently ExtraTreesRegressor) to quickly find a combination of parameters in the search hyperspace that minimizes the value of the [loss function](#loss-functions).
 
 Hyperopt requires historic data to be available, just as backtesting does.
 To learn how to get data for the pairs and exchange you're interested in, head over to the [Data Downloading](data-download.md) section of the documentation.
@@ -16,6 +14,24 @@ To learn how to get data for the pairs and exchange you're interested in, head o
 !!! Bug
     Hyperopt can crash when used with only 1 CPU Core as found out in [Issue #1133](https://github.com/freqtrade/freqtrade/issues/1133)
 
+## Install hyperopt dependencies
+
+Since Hyperopt dependencies are not needed to run the bot itself, are heavy, can not be easily built on some platforms (like Raspberry PI), they are not installed by default. Before you run Hyperopt, you need to install the corresponding dependencies, as described in this section below.
+
+!!! Note
+    Since Hyperopt is a resource intensive process, running it on a Raspberry Pi is not recommended nor supported.
+
+### Docker
+
+The docker-image includes hyperopt dependencies, no further action needed.
+
+### Easy installation script (setup.sh) / Manual installation
+
+```bash
+source .env/bin/activate
+pip install -r requirements-hyperopt.txt
+```
+
 ## Prepare Hyperopting
 
 Before we start digging into Hyperopt, we recommend you to take a look at
@@ -47,6 +63,9 @@ Optional - can also be loaded from a strategy:
 !!! Note
     Assuming the optional methods are not in your hyperopt file, please use `--strategy AweSomeStrategy` which contains these methods so hyperopt can use these methods instead.
 
+!!! Note
+    You always have to provide a strategy to Hyperopt, even if your custom Hyperopt class contains all methods.
+
 Rarely you may also need to override:
 
 * `roi_space` - for custom ROI optimization (if you need the ranges for the ROI parameters in the optimization hyperspace that differ from default)
@@ -105,9 +124,9 @@ To avoid naming collisions in the search-space, please prefix all sell-spaces wi
 
 #### Using timeframe as a part of the Strategy
 
-The Strategy class exposes the timeframe (ticker interval) value as the `self.ticker_interval` attribute.
-The same value is available as class-attribute `HyperoptName.ticker_interval`.
-In the case of the linked sample-value this would be `SampleHyperOpt.ticker_interval`.
+The Strategy class exposes the timeframe value as the `self.timeframe` attribute.
+The same value is available as class-attribute `HyperoptName.timeframe`.
+In the case of the linked sample-value this would be `SampleHyperOpt.timeframe`.
 
 ## Solving a Mystery
 
@@ -246,7 +265,7 @@ freqtrade hyperopt --timerange 20180401-20180501
 Hyperopt can reuse `populate_indicators`, `populate_buy_trend`, `populate_sell_trend` from your strategy, assuming these methods are **not** in your custom hyperopt file, and a strategy is provided.
 
 ```bash
-freqtrade hyperopt --strategy SampleStrategy --customhyperopt SampleHyperopt
+freqtrade hyperopt --strategy SampleStrategy --hyperopt SampleHyperopt
 ```
 
 ### Running Hyperopt with Smaller Search Space
@@ -293,7 +312,7 @@ You can also enable position stacking in the configuration file by explicitly se
 
 ### Reproducible results
 
-The search for optimal parameters starts with a few (currently 30) random combinations in the hyperspace of parameters, random Hyperopt epochs. These random epochs are marked with a leading asterisk sign at the Hyperopt output.
+The search for optimal parameters starts with a few (currently 30) random combinations in the hyperspace of parameters, random Hyperopt epochs. These random epochs are marked with an asterisk character (`*`) in the first column in the Hyperopt output.
 
 The initial state for generation of these random values (random state) is controlled by the value of the `--random-state` command line option. You can set it to some arbitrary value of your choice to obtain reproducible results.
 
@@ -384,7 +403,7 @@ As stated in the comment, you can also use it as the value of the `minimal_roi`
 
 #### Default ROI Search Space
 
-If you are optimizing ROI, Freqtrade creates the 'roi' optimization hyperspace for you -- it's the hyperspace of components for the ROI tables. By default, each ROI table generated by the Freqtrade consists of 4 rows (steps). Hyperopt implements adaptive ranges for ROI tables with ranges for values in the ROI steps that depend on the ticker_interval used. By default the values vary in the following ranges (for some of the most used timeframes, values are rounded to 5 digits after the decimal point):
+If you are optimizing ROI, Freqtrade creates the 'roi' optimization hyperspace for you -- it's the hyperspace of components for the ROI tables. By default, each ROI table generated by the Freqtrade consists of 4 rows (steps). Hyperopt implements adaptive ranges for ROI tables with ranges for values in the ROI steps that depend on the timeframe used. By default the values vary in the following ranges (for some of the most used timeframes, values are rounded to 5 digits after the decimal point):
 
 | # step | 1m     |                   | 5m       |             | 1h         |                   | 1d           |                   |
 | ------ | ------ | ----------------- | -------- | ----------- | ---------- | ----------------- | ------------ | ----------------- |
@@ -393,7 +412,7 @@ If you are optimizing ROI, Freqtrade creates the 'roi' optimization hyperspace f
 | 3      | 4...20 | 0.00387...0.01547 | 20...100 | 0.01...0.04 | 240...1200 | 0.02294...0.09177 | 5760...28800 | 0.04059...0.16237 |
 | 4      | 6...44 | 0.0               | 30...220 | 0.0         | 360...2640 | 0.0               | 8640...63360 | 0.0               |
 
-These ranges should be sufficient in most cases. The minutes in the steps (ROI dict keys) are scaled linearly depending on the timeframe (ticker interval) used. The ROI values in the steps (ROI dict values) are scaled logarithmically depending on the timeframe used.
+These ranges should be sufficient in most cases. The minutes in the steps (ROI dict keys) are scaled linearly depending on the timeframe used. The ROI values in the steps (ROI dict values) are scaled logarithmically depending on the timeframe used.
 
 If you have the `generate_roi_table()` and `roi_space()` methods in your custom hyperopt file, remove them in order to utilize these adaptive ROI tables and the ROI hyperoptimization space generated by Freqtrade by default.
 
@@ -468,7 +487,7 @@ As stated in the comment, you can also use it as the values of the corresponding
 
 If you are optimizing trailing stop values, Freqtrade creates the 'trailing' optimization hyperspace for you. By default, the `trailing_stop` parameter is always set to True in that hyperspace, the value of the `trailing_only_offset_is_reached` vary between True and False, the values of the `trailing_stop_positive` and `trailing_stop_positive_offset` parameters vary in the ranges 0.02...0.35 and 0.01...0.1 correspondingly, which is sufficient in most cases.
 
-Override the `trailing_space()` method and define the desired range in it if you need values of the trailing stop parameters to vary in other ranges during hyperoptimization. A sample for this method can be found in [user_data/hyperopts/sample_hyperopt_advanced.py](https://github.com/freqtrade/freqtrade/blob/develop/user_data/hyperopts/sample_hyperopt_advanced.py).
+Override the `trailing_space()` method and define the desired range in it if you need values of the trailing stop parameters to vary in other ranges during hyperoptimization. A sample for this method can be found in [user_data/hyperopts/sample_hyperopt_advanced.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_hyperopt_advanced.py).
 
 ## Show details of Hyperopt results
 
@@ -479,8 +498,3 @@ After you run Hyperopt for the desired amount of epochs, you can later list all
 Once the optimized strategy has been implemented into your strategy, you should backtest this strategy to make sure everything is working as expected.
 
 To achieve same results (number of trades, their durations, profit, etc.) than during Hyperopt, please use same set of arguments `--dmmp`/`--disable-max-market-positions` and `--eps`/`--enable-position-stacking` for Backtesting.
-
-## Next Step
-
-Now you have a perfect bot and want to control it from Telegram. Your
-next step is to learn the [Telegram usage](telegram-usage.md).

docs/installation.md

@@ -13,7 +13,7 @@ Click each one for install guide:
 * [Python >= 3.6.x](http://docs.python-guide.org/en/latest/starting/installation/)
 * [pip](https://pip.pypa.io/en/stable/installing/)
 * [git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git)
-* [virtualenv](https://virtualenv.pypa.io/en/stable/installation/) (Recommended)
+* [virtualenv](https://virtualenv.pypa.io/en/stable/installation.html) (Recommended)
 * [TA-Lib](https://mrjbq7.github.io/ta-lib/install.html) (install instructions below)
 
  We also recommend a [Telegram bot](telegram-usage.md#setup-your-telegram-bot), which is optional but recommended.
@@ -248,14 +248,14 @@ git clone https://github.com/freqtrade/freqtrade.git
 
 Install ta-lib according to the [ta-lib documentation](https://github.com/mrjbq7/ta-lib#windows).
 
-As compiling from source on windows has heavy dependencies (requires a partial visual studio installation), there is also a repository of unofficial precompiled windows Wheels [here](https://www.lfd.uci.edu/~gohlke/pythonlibs/#ta-lib), which needs to be downloaded and installed using `pip install TA_Lib‑0.4.17‑cp36‑cp36m‑win32.whl` (make sure to use the version matching your python version)
+As compiling from source on windows has heavy dependencies (requires a partial visual studio installation), there is also a repository of unofficial precompiled windows Wheels [here](https://www.lfd.uci.edu/~gohlke/pythonlibs/#ta-lib), which needs to be downloaded and installed using `pip install TA_Lib‑0.4.18‑cp38‑cp38‑win_amd64.whl` (make sure to use the version matching your python version)
 
 ```cmd
 >cd \path\freqtrade-develop
 >python -m venv .env
 >.env\Scripts\activate.bat
 REM optionally install ta-lib from wheel
-REM >pip install TA_Lib‑0.4.17‑cp36‑cp36m‑win32.whl
+REM >pip install TA_Lib‑0.4.18‑cp38‑cp38‑win_amd64.whl
 >pip install -r requirements.txt
 >pip install -e .
 >freqtrade

docs/plotting.md

@@ -31,7 +31,7 @@ usage: freqtrade plot-dataframe [-h] [-v] [--logfile FILE] [-V] [-c PATH]
                                 [--plot-limit INT] [--db-url PATH]
                                 [--trade-source {DB,file}] [--export EXPORT]
                                 [--export-filename PATH]
-                                [--timerange TIMERANGE] [-i TICKER_INTERVAL]
+                                [--timerange TIMERANGE] [-i TIMEFRAME]
                                 [--no-trades]
 
 optional arguments:
@@ -65,7 +65,7 @@ optional arguments:
                         _today.json`
   --timerange TIMERANGE
                         Specify what timerange of data to use.
-  -i TICKER_INTERVAL, --ticker-interval TICKER_INTERVAL
+  -i TIMEFRAME, --timeframe TIMEFRAME, --ticker-interval TIMEFRAME
                         Specify ticker interval (`1m`, `5m`, `30m`, `1h`,
                         `1d`).
   --no-trades           Skip using trades from backtesting file and DB.
@@ -227,7 +227,7 @@ usage: freqtrade plot-profit [-h] [-v] [--logfile FILE] [-V] [-c PATH]
                              [-d PATH] [--userdir PATH] [-p PAIRS [PAIRS ...]]
                              [--timerange TIMERANGE] [--export EXPORT]
                              [--export-filename PATH] [--db-url PATH]
-                             [--trade-source {DB,file}] [-i TICKER_INTERVAL]
+                             [--trade-source {DB,file}] [-i TIMEFRAME]
 
 optional arguments:
   -h, --help            show this help message and exit
@@ -250,7 +250,7 @@ optional arguments:
   --trade-source {DB,file}
                         Specify the source for trades (Can be DB or file
                         (backtest file)) Default: file
-  -i TICKER_INTERVAL, --ticker-interval TICKER_INTERVAL
+  -i TIMEFRAME, --timeframe TIMEFRAME, --ticker-interval TIMEFRAME
                         Specify ticker interval (`1m`, `5m`, `30m`, `1h`,
                         `1d`).
 
@@ -261,9 +261,10 @@ Common arguments:
                         details.
   -V, --version         show program's version number and exit
   -c PATH, --config PATH
-                        Specify configuration file (default: `config.json`).
-                        Multiple --config options may be used. Can be set to
-                        `-` to read config from stdin.
+                        Specify configuration file (default:
+                        `userdir/config.json` or `config.json` whichever
+                        exists). Multiple --config options may be used. Can be
+                        set to `-` to read config from stdin.
   -d PATH, --datadir PATH
                         Path to directory with historical backtesting data.
   --userdir PATH, --user-data-dir PATH

docs/requirements-docs.txt

@@ -1,2 +1,2 @@
-mkdocs-material==4.6.3
+mkdocs-material==5.5.3
 mdx_truly_sane_lists==1.2

docs/rest-api.md

@@ -11,6 +11,9 @@ Sample configuration:
         "enabled": true,
         "listen_ip_address": "127.0.0.1",
         "listen_port": 8080,
+        "verbosity": "info",
+        "jwt_secret_key": "somethingrandom",
+        "CORS_origins": [],
         "username": "Freqtrader",
         "password": "SuperSecret1!"
     },
@@ -29,7 +32,7 @@ This should return the response:
 {"status":"pong"}
 ```
 
-All other endpoints return sensitive info and require authentication, so are not available through a web browser.
+All other endpoints return sensitive info and require authentication and are therefore not available through a web browser.
 
 To generate a secure password, either use a password manager, or use the below code snipped.
 
@@ -38,9 +41,12 @@ import secrets
 secrets.token_hex()
 ```
 
+!!! Hint
+    Use the same method to also generate a JWT secret key (`jwt_secret_key`).
+
 ### Configuration with docker
 
-If you run your bot using docker, you'll need to have the bot listen to incomming connections. The security is then handled by docker.
+If you run your bot using docker, you'll need to have the bot listen to incoming connections. The security is then handled by docker.
 
 ``` json
     "api_server": {
@@ -100,26 +106,29 @@ python3 scripts/rest_client.py --config rest_config.json <command> [optional par
 
 ## Available commands
 
-|  Command | Default | Description |
-|----------|---------|-------------|
-| `start` | | Starts the trader
-| `stop` | | Stops the trader
-| `stopbuy` | | Stops the trader from opening new trades. Gracefully closes open trades according to their rules.
-| `reload_conf` | | Reloads the configuration file
-| `show_config` | | Shows part of the current configuration with relevant settings to operation
-| `status` | | Lists all open trades
-| `count` | | Displays number of trades used and available
-| `profit` | | Display a summary of your profit/loss from close trades and some stats about your performance
-| `forcesell <trade_id>` | | Instantly sells the given trade  (Ignoring `minimum_roi`).
-| `forcesell all` | | Instantly sells all open trades (Ignoring `minimum_roi`).
-| `forcebuy <pair> [rate]` | | Instantly buys the given pair. Rate is optional. (`forcebuy_enable` must be set to True)
-| `performance` | | Show performance of each finished trade grouped by pair
-| `balance` | | Show account balance per currency
-| `daily <n>` | 7 | Shows profit or loss per day, over the last n days
-| `whitelist` | | Show the current whitelist
-| `blacklist [pair]` | | Show the current blacklist, or adds a pair to the blacklist.
-| `edge` | | Show validated pairs by Edge if it is enabled.
-| `version` | | Show version
+|  Command | Description |
+|----------|-------------|
+| `ping` | Simple command testing the API Readiness - requires no authentication.
+| `start` | Starts the trader
+| `stop` | Stops the trader
+| `stopbuy` | Stops the trader from opening new trades. Gracefully closes open trades according to their rules.
+| `reload_config` | Reloads the configuration file
+| `trades` | List last trades.
+| `delete_trade <trade_id>` | Remove trade from the database. Tries to close open orders. Requires manual handling of this trade on the exchange.
+| `show_config` | Shows part of the current configuration with relevant settings to operation
+| `status` | Lists all open trades
+| `count` | Displays number of trades used and available
+| `profit` | Display a summary of your profit/loss from close trades and some stats about your performance
+| `forcesell <trade_id>` | Instantly sells the given trade  (Ignoring `minimum_roi`).
+| `forcesell all` | Instantly sells all open trades (Ignoring `minimum_roi`).
+| `forcebuy <pair> [rate]` | Instantly buys the given pair. Rate is optional. (`forcebuy_enable` must be set to True)
+| `performance` | Show performance of each finished trade grouped by pair
+| `balance` | Show account balance per currency
+| `daily <n>` | Shows profit or loss per day, over the last n days (n defaults to 7)
+| `whitelist` | Show the current whitelist
+| `blacklist [pair]` | Show the current blacklist, or adds a pair to the blacklist.
+| `edge` | Show validated pairs by Edge if it is enabled.
+| `version` | Show version
 
 Possible commands can be listed from the rest-client script using the `help` command.
 
@@ -169,7 +178,7 @@ profit
         Returns the profit summary
         :returns: json object
 
-reload_conf
+reload_config
         Reload configuration
         :returns: json object
 
@@ -191,7 +200,7 @@ stop
 
 stopbuy
         Stop buying (but handle sells gracefully).
-        use reload_conf to reset
+        use reload_config to reset
         :returns: json object
 
 version
@@ -202,3 +211,51 @@ whitelist
         Show the current whitelist
         :returns: json object
 ```
+
+## Advanced API usage using JWT tokens
+
+!!! Note
+    The below should be done in an application (a Freqtrade REST API client, which fetches info via API), and is not intended to be used on a regular basis.
+
+Freqtrade's REST API also offers JWT (JSON Web Tokens).
+You can login using the following command, and subsequently use the resulting access_token.
+
+``` bash
+> curl -X POST --user Freqtrader http://localhost:8080/api/v1/token/login
+{"access_token":"eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpYXQiOjE1ODkxMTk2ODEsIm5iZiI6MTU4OTExOTY4MSwianRpIjoiMmEwYmY0NWUtMjhmOS00YTUzLTlmNzItMmM5ZWVlYThkNzc2IiwiZXhwIjoxNTg5MTIwNTgxLCJpZGVudGl0eSI6eyJ1IjoiRnJlcXRyYWRlciJ9LCJmcmVzaCI6ZmFsc2UsInR5cGUiOiJhY2Nlc3MifQ.qt6MAXYIa-l556OM7arBvYJ0SDI9J8bIk3_glDujF5g","refresh_token":"eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpYXQiOjE1ODkxMTk2ODEsIm5iZiI6MTU4OTExOTY4MSwianRpIjoiZWQ1ZWI3YjAtYjMwMy00YzAyLTg2N2MtNWViMjIxNWQ2YTMxIiwiZXhwIjoxNTkxNzExNjgxLCJpZGVudGl0eSI6eyJ1IjoiRnJlcXRyYWRlciJ9LCJ0eXBlIjoicmVmcmVzaCJ9.d1AT_jYICyTAjD0fiQAr52rkRqtxCjUGEMwlNuuzgNQ"}
+
+> access_token="eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpYXQiOjE1ODkxMTk2ODEsIm5iZiI6MTU4OTExOTY4MSwianRpIjoiMmEwYmY0NWUtMjhmOS00YTUzLTlmNzItMmM5ZWVlYThkNzc2IiwiZXhwIjoxNTg5MTIwNTgxLCJpZGVudGl0eSI6eyJ1IjoiRnJlcXRyYWRlciJ9LCJmcmVzaCI6ZmFsc2UsInR5cGUiOiJhY2Nlc3MifQ.qt6MAXYIa-l556OM7arBvYJ0SDI9J8bIk3_glDujF5g"
+# Use access_token for authentication
+> curl -X GET --header "Authorization: Bearer ${access_token}" http://localhost:8080/api/v1/count
+
+```
+
+Since the access token has a short timeout (15 min) - the `token/refresh` request should be used periodically to get a fresh access token:
+
+``` bash
+> curl -X POST --header "Authorization: Bearer ${refresh_token}"http://localhost:8080/api/v1/token/refresh
+{"access_token":"eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpYXQiOjE1ODkxMTk5NzQsIm5iZiI6MTU4OTExOTk3NCwianRpIjoiMDBjNTlhMWUtMjBmYS00ZTk0LTliZjAtNWQwNTg2MTdiZDIyIiwiZXhwIjoxNTg5MTIwODc0LCJpZGVudGl0eSI6eyJ1IjoiRnJlcXRyYWRlciJ9LCJmcmVzaCI6ZmFsc2UsInR5cGUiOiJhY2Nlc3MifQ.1seHlII3WprjjclY6DpRhen0rqdF4j6jbvxIhUFaSbs"}
+```
+
+## CORS
+
+All web-based frontends are subject to [CORS](https://developer.mozilla.org/en-US/docs/Web/HTTP/CORS) - Cross-Origin Resource Sharing.
+Since most of the requests to the Freqtrade API must be authenticated, a proper CORS policy is key to avoid security problems.
+Also, the standard disallows `*` CORS policies for requests with credentials, so this setting must be set appropriately.
+
+Users can configure this themselves via the `CORS_origins` configuration setting.
+It consists of a list of allowed sites that are allowed to consume resources from the bot's API.
+
+Assuming your application is deployed as `https://frequi.freqtrade.io/home/` - this would mean that the following configuration becomes necessary:
+
+```jsonc
+{
+    //...
+    "jwt_secret_key": "somethingrandom",
+    "CORS_origins": ["https://frequi.freqtrade.io"],
+    //...
+}
+```
+
+!!! Note
+    We strongly recommend to also set `jwt_secret_key` to something random and known only to yourself to avoid unauthorized access to your bot.

docs/sql_cheatsheet.md

@@ -1,13 +1,29 @@
 # SQL Helper
+
 This page contains some help if you want to edit your sqlite db.
 
 ## Install sqlite3
-**Ubuntu/Debian installation**
+
+Sqlite3 is a terminal based sqlite application.
+Feel free to use a visual Database editor like SqliteBrowser if you feel more comfortable with that.
+
+### Ubuntu/Debian installation
+
 ```bash
 sudo apt-get install sqlite3
 ```
 
+### Using sqlite3 via docker-compose
+
+The freqtrade docker image does contain sqlite3, so you can edit the database without having to install anything on the host system.
+
+``` bash
+docker-compose exec freqtrade /bin/bash
+sqlite3 <databasefile>.sqlite
+```
+
 ## Open the DB
+
 ```bash
 sqlite3
 .open <filepath>
@@ -16,45 +32,61 @@ sqlite3
 ## Table structure
 
 ### List tables
+
 ```bash
 .tables
 ```
 
 ### Display table structure
+
 ```bash
 .schema <table_name>
 ```
 
 ### Trade table structure
+
 ```sql
-CREATE TABLE trades (
-	id INTEGER NOT NULL,
-	exchange VARCHAR NOT NULL,
-	pair VARCHAR NOT NULL,
-	is_open BOOLEAN NOT NULL,
-	fee_open FLOAT NOT NULL,
-	fee_close FLOAT NOT NULL,
-	open_rate FLOAT,
-	open_rate_requested FLOAT,
-	close_rate FLOAT,
-	close_rate_requested FLOAT,
-	close_profit FLOAT,
-	stake_amount FLOAT NOT NULL,
-	amount FLOAT,
-	open_date DATETIME NOT NULL,
-	close_date DATETIME,
-	open_order_id VARCHAR,
-	stop_loss FLOAT,
-	initial_stop_loss FLOAT,
-	stoploss_order_id VARCHAR,
-	stoploss_last_update DATETIME,
-	max_rate FLOAT,
-	sell_reason VARCHAR,
-	strategy VARCHAR,
-	ticker_interval INTEGER,
-	PRIMARY KEY (id),
-	CHECK (is_open IN (0, 1))
+CREATE TABLE trades
+    id INTEGER NOT NULL,
+    exchange VARCHAR NOT NULL,
+    pair VARCHAR NOT NULL,
+    is_open BOOLEAN NOT NULL,
+    fee_open FLOAT NOT NULL,
+    fee_open_cost FLOAT,
+    fee_open_currency VARCHAR,
+    fee_close FLOAT NOT NULL,
+    fee_close_cost FLOAT,
+    fee_close_currency VARCHAR,
+    open_rate FLOAT,
+    open_rate_requested FLOAT,
+    open_trade_price FLOAT,
+    close_rate FLOAT,
+    close_rate_requested FLOAT,
+    close_profit FLOAT,
+    close_profit_abs FLOAT,
+    stake_amount FLOAT NOT NULL,
+    amount FLOAT,
+    open_date DATETIME NOT NULL,
+    close_date DATETIME,
+    open_order_id VARCHAR,
+    stop_loss FLOAT,
+    stop_loss_pct FLOAT,
+    initial_stop_loss FLOAT,
+    initial_stop_loss_pct FLOAT,
+    stoploss_order_id VARCHAR,
+    stoploss_last_update DATETIME,
+    max_rate FLOAT,
+    min_rate FLOAT,
+    sell_reason VARCHAR,
+    strategy VARCHAR,
+    timeframe INTEGER,
+    PRIMARY KEY (id),
+    CHECK (is_open IN (0, 1))
 );
+CREATE INDEX ix_trades_stoploss_order_id ON trades (stoploss_order_id);
+CREATE INDEX ix_trades_pair ON trades (pair);
+CREATE INDEX ix_trades_is_open ON trades (is_open);
+
 ```
 
 ## Get all trades in the table
@@ -67,42 +99,60 @@ SELECT * FROM trades;
 
 !!! Warning
   	Manually selling a pair on the exchange will not be detected by the bot and it will try to sell anyway. Whenever possible, forcesell <tradeid> should be used to accomplish the same thing.  
-		It is strongly advised to backup your database file before making any manual changes.
+	It is strongly advised to backup your database file before making any manual changes.
 
 !!! Note
   	This should not be necessary after /forcesell, as forcesell orders are closed automatically by the bot on the next iteration.
 
 ```sql
 UPDATE trades
-SET is_open=0, close_date=<close_date>, close_rate=<close_rate>, close_profit=close_rate/open_rate-1, sell_reason=<sell_reason>  
+SET is_open=0,
+  close_date=<close_date>,
+  close_rate=<close_rate>,
+  close_profit = close_rate / open_rate - 1,
+  close_profit_abs = (amount * <close_rate> * (1 - fee_close) - (amount * (open_rate * 1 - fee_open))),
+  sell_reason=<sell_reason>
 WHERE id=<trade_ID_to_update>;
 ```
 
-##### Example
+### Example
 
 ```sql
 UPDATE trades
-SET is_open=0, close_date='2017-12-20 03:08:45.103418', close_rate=0.19638016, close_profit=0.0496, sell_reason='force_sell'  
+SET is_open=0,
+  close_date='2020-06-20 03:08:45.103418',
+  close_rate=0.19638016,
+  close_profit=0.0496,
+  close_profit_abs = (amount * 0.19638016 * (1 - fee_close) - (amount * open_rate * (1 - fee_open))),
+  sell_reason='force_sell'  
 WHERE id=31;
 ```
 
-## Insert manually a new trade
+## Manually insert a new trade
 
 ```sql
 INSERT INTO trades (exchange, pair, is_open, fee_open, fee_close, open_rate, stake_amount, amount, open_date)
-VALUES ('bittrex', 'ETH/BTC', 1, 0.0025, 0.0025, <open_rate>, <stake_amount>, <amount>, '<datetime>')
+VALUES ('binance', 'ETH/BTC', 1, 0.0025, 0.0025, <open_rate>, <stake_amount>, <amount>, '<datetime>')
 ```
 
-##### Example:
+### Insert trade example
 
 ```sql
 INSERT INTO trades (exchange, pair, is_open, fee_open, fee_close, open_rate, stake_amount, amount, open_date)
-VALUES ('bittrex', 'ETH/BTC', 1, 0.0025, 0.0025, 0.00258580, 0.002, 0.7715262081, '2017-11-28 12:44:24.000000')
+VALUES ('binance', 'ETH/BTC', 1, 0.0025, 0.0025, 0.00258580, 0.002, 0.7715262081, '2020-06-28 12:44:24.000000')
 ```
 
-## Fix wrong fees in the table
-If your DB was created before [PR#200](https://github.com/freqtrade/freqtrade/pull/200) was merged (before 12/23/17).
+## Remove trade from the database
+
+Maybe you'd like to remove a trade from the database, because something went wrong.
 
 ```sql
-UPDATE trades SET fee=0.0025 WHERE fee=0.005;
+DELETE FROM trades WHERE id = <tradeid>;
 ```
+
+```sql
+DELETE FROM trades WHERE id = 31;
+```
+
+!!! Warning
+    This will remove this trade from the database. Please make sure you got the correct id and **NEVER** run this query without the `where` clause.

docs/stoploss.md

@@ -1,6 +1,6 @@
 # Stop Loss
 
-The `stoploss` configuration parameter is loss in percentage that should trigger a sale.
+The `stoploss` configuration parameter is loss as ratio that should trigger a sale.
 For example, value `-0.10` will cause immediate sell if the profit dips below -10% for a given trade. This parameter is optional.
 
 Most of the strategy files already include the optimal `stoploss` value.
@@ -27,7 +27,7 @@ So this parameter will tell the bot how often it should update the stoploss orde
 This same logic will reapply a stoploss order on the exchange should you cancel it accidentally.
 
 !!! Note
-    Stoploss on exchange is only supported for Binance (stop-loss-limit) and Kraken (stop-loss-market) as of now.
+    Stoploss on exchange is only supported for Binance (stop-loss-limit), Kraken (stop-loss-market) and FTX (stop limit and stop-market) as of now.
 
 ## Static Stop Loss
 
@@ -84,7 +84,7 @@ This option can be used with or without `trailing_stop_positive`, but uses `trai
 
 ``` python
     trailing_stop_positive_offset = 0.011
-    trailing_only_offset_is_reached = true
+    trailing_only_offset_is_reached = True
 ```
 
 Simplified example:
@@ -101,7 +101,7 @@ Simplified example:
 
 ## Changing stoploss on open trades
 
-A stoploss on an open trade can be changed by changing the value in the configuration or strategy and use the `/reload_conf` command (alternatively, completely stopping and restarting the bot also works).
+A stoploss on an open trade can be changed by changing the value in the configuration or strategy and use the `/reload_config` command (alternatively, completely stopping and restarting the bot also works).
 
 The new stoploss value will be applied to open trades (and corresponding log-messages will be generated).
 

docs/strategy-advanced.md

@@ -0,0 +1,201 @@
+# Advanced Strategies
+
+This page explains some advanced concepts available for strategies.
+If you're just getting started, please be familiar with the methods described in the [Strategy Customization](strategy-customization.md) documentation and with the [Freqtrade basics](bot-basics.md) first.
+
+[Freqtrade basics](bot-basics.md) describes in which sequence each method described below is called, which can be helpful to understand which method to use for your custom needs.
+
+!!! Note
+    All callback methods described below should only be implemented in a strategy if they are actually used.
+
+## Custom order timeout rules
+
+Simple, timebased order-timeouts can be configured either via strategy or in the configuration in the `unfilledtimeout` section.
+
+However, freqtrade also offers a custom callback for both ordertypes, which allows you to decide based on custom criteria if a order did time out or not.
+
+!!! Note
+    Unfilled order timeouts are not relevant during backtesting or hyperopt, and are only relevant during real (live) trading. Therefore these methods are only called in these circumstances.
+
+### Custom order timeout example
+
+A simple example, which applies different unfilled-timeouts depending on the price of the asset can be seen below.
+It applies a tight timeout for higher priced assets, while allowing more time to fill on cheap coins.
+
+The function must return either `True` (cancel order) or `False` (keep order alive).
+
+``` python
+from datetime import datetime, timedelta
+from freqtrade.persistence import Trade
+
+class Awesomestrategy(IStrategy):
+
+    # ... populate_* methods
+
+    # Set unfilledtimeout to 25 hours, since our maximum timeout from below is 24 hours.
+    unfilledtimeout = {
+        'buy': 60 * 25,
+        'sell': 60 * 25
+    }
+
+    def check_buy_timeout(self, pair: str, trade: 'Trade', order: dict, **kwargs) -> bool:
+        if trade.open_rate > 100 and trade.open_date < datetime.utcnow() - timedelta(minutes=5):
+            return True
+        elif trade.open_rate > 10 and trade.open_date < datetime.utcnow() - timedelta(minutes=3):
+            return True
+        elif trade.open_rate < 1 and trade.open_date < datetime.utcnow() - timedelta(hours=24):
+           return True
+        return False
+
+
+    def check_sell_timeout(self, pair: str, trade: 'Trade', order: dict, **kwargs) -> bool:
+        if trade.open_rate > 100 and trade.open_date < datetime.utcnow() - timedelta(minutes=5):
+            return True
+        elif trade.open_rate > 10 and trade.open_date < datetime.utcnow() - timedelta(minutes=3):
+            return True
+        elif trade.open_rate < 1 and trade.open_date < datetime.utcnow() - timedelta(hours=24):
+           return True
+        return False
+```
+
+!!! Note
+    For the above example, `unfilledtimeout` must be set to something bigger than 24h, otherwise that type of timeout will apply first.
+
+### Custom order timeout example (using additional data)
+
+``` python
+from datetime import datetime
+from freqtrade.persistence import Trade
+
+class Awesomestrategy(IStrategy):
+
+    # ... populate_* methods
+
+    # Set unfilledtimeout to 25 hours, since our maximum timeout from below is 24 hours.
+    unfilledtimeout = {
+        'buy': 60 * 25,
+        'sell': 60 * 25
+    }
+
+    def check_buy_timeout(self, pair: str, trade: Trade, order: dict, **kwargs) -> bool:
+        ob = self.dp.orderbook(pair, 1)
+        current_price = ob['bids'][0][0]
+        # Cancel buy order if price is more than 2% above the order.
+        if current_price > order['price'] * 1.02:
+            return True
+        return False
+
+
+    def check_sell_timeout(self, pair: str, trade: Trade, order: dict, **kwargs) -> bool:
+        ob = self.dp.orderbook(pair, 1)
+        current_price = ob['asks'][0][0]
+        # Cancel sell order if price is more than 2% below the order.
+        if current_price < order['price'] * 0.98:
+            return True
+        return False
+```
+
+## Bot loop start callback
+
+A simple callback which is called once at the start of every bot throttling iteration.
+This can be used to perform calculations which are pair independent (apply to all pairs), loading of external data, etc.
+
+``` python
+import requests
+
+class Awesomestrategy(IStrategy):
+
+    # ... populate_* methods
+
+    def bot_loop_start(self, **kwargs) -> None:
+        """
+        Called at the start of the bot iteration (one loop).
+        Might be used to perform pair-independent tasks
+        (e.g. gather some remote resource for comparison)
+        :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+        """
+        if self.config['runmode'].value in ('live', 'dry_run'):
+            # Assign this to the class by using self.*
+            # can then be used by populate_* methods
+            self.remote_data = requests.get('https://some_remote_source.example.com')
+
+```
+
+## Bot order confirmation
+
+### Trade entry (buy order) confirmation
+
+`confirm_trade_entry()` can be used to abort a trade entry at the latest second (maybe because the price is not what we expect).
+
+``` python
+class Awesomestrategy(IStrategy):
+
+    # ... populate_* methods
+
+    def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
+                            time_in_force: str, **kwargs) -> bool:
+        """
+        Called right before placing a buy order.
+        Timing for this function is critical, so avoid doing heavy computations or
+        network requests in this method.
+
+        For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
+
+        When not implemented by a strategy, returns True (always confirming).
+
+        :param pair: Pair that's about to be bought.
+        :param order_type: Order type (as configured in order_types). usually limit or market.
+        :param amount: Amount in target (quote) currency that's going to be traded.
+        :param rate: Rate that's going to be used when using limit orders
+        :param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
+        :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+        :return bool: When True is returned, then the buy-order is placed on the exchange.
+            False aborts the process
+        """
+        return True
+
+```
+
+### Trade exit (sell order) confirmation
+
+`confirm_trade_exit()` can be used to abort a trade exit (sell) at the latest second (maybe because the price is not what we expect).
+
+``` python
+from freqtrade.persistence import Trade
+
+
+class Awesomestrategy(IStrategy):
+
+    # ... populate_* methods
+
+    def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str, amount: float,
+                           rate: float, time_in_force: str, sell_reason: str, **kwargs) -> bool:
+        """
+        Called right before placing a regular sell order.
+        Timing for this function is critical, so avoid doing heavy computations or
+        network requests in this method.
+
+        For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
+
+        When not implemented by a strategy, returns True (always confirming).
+
+        :param pair: Pair that's about to be sold.
+        :param order_type: Order type (as configured in order_types). usually limit or market.
+        :param amount: Amount in quote currency.
+        :param rate: Rate that's going to be used when using limit orders
+        :param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
+        :param sell_reason: Sell reason.
+            Can be any of ['roi', 'stop_loss', 'stoploss_on_exchange', 'trailing_stop_loss',
+                           'sell_signal', 'force_sell', 'emergency_sell']
+        :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+        :return bool: When True is returned, then the sell-order is placed on the exchange.
+            False aborts the process
+        """
+        if sell_reason == 'force_sell' and trade.calc_profit_ratio(rate) < 0:
+            # Reject force-sells with negative profit
+            # This is just a sample, please adjust to your needs
+            # (this does not necessarily make sense, assuming you know when you're force-selling)
+            return False
+        return True
+
+```

docs/strategy-customization.md

@@ -1,7 +1,8 @@
 # Strategy Customization
 
-This page explains where to customize your strategies, and add new
-indicators.
+This page explains how to customize your strategies, add new indicators and set up trading rules.
+
+Please familiarize yourself with [Freqtrade basics](bot-basics.md) first, which provides overall info on how the bot operates.
 
 ## Install a custom strategy file
 
@@ -140,10 +141,10 @@ By letting the bot know how much history is needed, backtest trades can start at
 
 #### Example
 
-Let's try to backtest 1 month (January 2019) of 5m candles using the an example strategy with EMA100, as above.
+Let's try to backtest 1 month (January 2019) of 5m candles using an example strategy with EMA100, as above.
 
 ``` bash
-freqtrade backtesting --timerange 20190101-20190201 --ticker-interval 5m
+freqtrade backtesting --timerange 20190101-20190201 --timeframe 5m
 ```
 
 Assuming `startup_candle_count` is set to 100, backtesting knows it needs 100 candles to generate valid buy signals. It will load data from `20190101 - (100 * 5m)` - which is ~2019-12-31 15:30:00.
@@ -249,7 +250,7 @@ minimal_roi = {
 
 While technically not completely disabled, this would sell once the trade reaches 10000% Profit.
 
-To use times based on candle duration (ticker_interval or timeframe), the following snippet can be handy.
+To use times based on candle duration (timeframe), the following snippet can be handy.
 This will allow you to change the ticket_interval for the strategy, and ROI times will still be set as candles (e.g. after 3 candles ...)
 
 ``` python
@@ -257,12 +258,12 @@ from freqtrade.exchange import timeframe_to_minutes
 
 class AwesomeStrategy(IStrategy):
 
-    ticker_interval = "1d"
-    ticker_interval_mins = timeframe_to_minutes(ticker_interval)
+    timeframe = "1d"
+    timeframe_mins = timeframe_to_minutes(timeframe)
     minimal_roi = {
         "0": 0.05,                             # 5% for the first 3 candles
-        str(ticker_interval_mins * 3)): 0.02,  # 2% after 3 candles
-        str(ticker_interval_mins * 6)): 0.01,  # 1% After 6 candles
+        str(timeframe_mins * 3)): 0.02,  # 2% after 3 candles
+        str(timeframe_mins * 6)): 0.01,  # 1% After 6 candles
     }
 ```
 
@@ -291,7 +292,7 @@ Common values are `"1m"`, `"5m"`, `"15m"`, `"1h"`, however all values supported
 
 Please note that the same buy/sell signals may work well with one timeframe, but not with the others.
 
-This setting is accessible within the strategy methods as the `self.ticker_interval` attribute.
+This setting is accessible within the strategy methods as the `self.timeframe` attribute.
 
 ### Metadata dict
 
@@ -325,67 +326,14 @@ class Awesomestrategy(IStrategy):
 !!! Note
     If the data is pair-specific, make sure to use pair as one of the keys in the dictionary.
 
-### Additional data (DataProvider)
+***
 
-The strategy provides access to the `DataProvider`. This allows you to get additional data to use in your strategy.
-
-All methods return `None` in case of failure (do not raise an exception).
-
-Please always check the mode of operation to select the correct method to get data (samples see below).
-
-#### Possible options for DataProvider
-
-- `available_pairs` - Property with tuples listing cached pairs with their intervals (pair, interval).
-- `ohlcv(pair, timeframe)` - Currently cached candle (OHLCV) data for the pair, returns DataFrame or empty DataFrame.
-- `historic_ohlcv(pair, timeframe)` - Returns historical data stored on disk.
-- `get_pair_dataframe(pair, timeframe)` - This is a universal method, which returns either historical data (for backtesting) or cached live data (for the Dry-Run and Live-Run modes).
-- `orderbook(pair, maximum)` - Returns latest orderbook data for the pair, a dict with bids/asks with a total of `maximum` entries.
-- `market(pair)` - Returns market data for the pair: fees, limits, precisions, activity flag, etc. See [ccxt documentation](https://github.com/ccxt/ccxt/wiki/Manual#markets) for more details on Market data structure.
-- `runmode` - Property containing the current runmode.
-
-#### Example: fetch live / historical candle (OHLCV) data for the first informative pair
-
-``` python
-if self.dp:
-    inf_pair, inf_timeframe = self.informative_pairs()[0]
-    informative = self.dp.get_pair_dataframe(pair=inf_pair,
-                                             timeframe=inf_timeframe)
-```
-
-!!! Warning "Warning about backtesting"
-    Be carefull when using dataprovider in backtesting. `historic_ohlcv()` (and `get_pair_dataframe()`
-    for the backtesting runmode) provides the full time-range in one go,
-    so please be aware of it and make sure to not "look into the future" to avoid surprises when running in dry/live mode).
-
-!!! Warning "Warning in hyperopt"
-    This option cannot currently be used during hyperopt.
-
-#### Orderbook
-
-``` python
-if self.dp:
-    if self.dp.runmode.value in ('live', 'dry_run'):
-        ob = self.dp.orderbook(metadata['pair'], 1)
-        dataframe['best_bid'] = ob['bids'][0][0]
-        dataframe['best_ask'] = ob['asks'][0][0]
-```
-
-!!! Warning
-    The order book is not part of the historic data which means backtesting and hyperopt will not work if this
-    method is used.
-
-#### Available Pairs
-
-``` python
-if self.dp:
-    for pair, timeframe in self.dp.available_pairs:
-        print(f"available {pair}, {timeframe}")
-```
+### Additional data (informative_pairs)
 
 #### Get data for non-tradeable pairs
 
 Data for additional, informative pairs (reference pairs) can be beneficial for some strategies.
-Ohlcv data for these pairs will be downloaded as part of the regular whitelist refresh process and is available via `DataProvider` just as other pairs (see above).
+Ohlcv data for these pairs will be downloaded as part of the regular whitelist refresh process and is available via `DataProvider` just as other pairs (see below).
 These parts will **not** be traded unless they are also specified in the pair whitelist, or have been selected by Dynamic Whitelisting.
 
 The pairs need to be specified as tuples in the format `("pair", "interval")`, with pair as the first and time interval as the second argument.
@@ -405,6 +353,178 @@ def informative_pairs(self):
     It is however better to use resampling to longer time-intervals when possible
     to avoid hammering the exchange with too many requests and risk being blocked.
 
+***
+
+### Additional data (DataProvider)
+
+The strategy provides access to the `DataProvider`. This allows you to get additional data to use in your strategy.
+
+All methods return `None` in case of failure (do not raise an exception).
+
+Please always check the mode of operation to select the correct method to get data (samples see below).
+
+#### Possible options for DataProvider
+
+- [`available_pairs`](#available_pairs) - Property with tuples listing cached pairs with their intervals (pair, interval).
+- [`current_whitelist()`](#current_whitelist) - Returns a current list of whitelisted pairs. Useful for accessing dynamic whitelists (ie. VolumePairlist)
+- [`get_pair_dataframe(pair, timeframe)`](#get_pair_dataframepair-timeframe) - This is a universal method, which returns either historical data (for backtesting) or cached live data (for the Dry-Run and Live-Run modes).
+- [`get_analyzed_dataframe(pair, timeframe)`](#get_analyzed_dataframepair-timeframe) - Returns the analyzed dataframe (after calling `populate_indicators()`, `populate_buy()`, `populate_sell()`) and the time of the latest analysis.
+- `historic_ohlcv(pair, timeframe)` - Returns historical data stored on disk.
+- `market(pair)` - Returns market data for the pair: fees, limits, precisions, activity flag, etc. See [ccxt documentation](https://github.com/ccxt/ccxt/wiki/Manual#markets) for more details on the Market data structure.
+- `ohlcv(pair, timeframe)` - Currently cached candle (OHLCV) data for the pair, returns DataFrame or empty DataFrame.
+- [`orderbook(pair, maximum)`](#orderbookpair-maximum) - Returns latest orderbook data for the pair, a dict with bids/asks with a total of `maximum` entries.
+- [`ticker(pair)`](#tickerpair) - Returns current ticker data for the pair. See [ccxt documentation](https://github.com/ccxt/ccxt/wiki/Manual#price-tickers) for more details on the Ticker data structure.
+- `runmode` - Property containing the current runmode.
+
+#### Example Usages:
+
+#### *available_pairs*
+
+``` python
+if self.dp:
+    for pair, timeframe in self.dp.available_pairs:
+        print(f"available {pair}, {timeframe}")
+```
+
+#### *current_whitelist()*
+
+Imagine you've developed a strategy that trades the `5m` timeframe using signals generated from a `1d` timeframe on the top 10 volume pairs by volume. 
+
+The strategy might look something like this:
+
+*Scan through the top 10 pairs by volume using the `VolumePairList` every 5 minutes and use a 14 day RSI to buy and sell.*
+
+Due to the limited available data, it's very difficult to resample our `5m` candles into daily candles for use in a 14 day RSI. Most exchanges limit us to just 500 candles which effectively gives us around 1.74 daily candles. We need 14 days at least!
+
+Since we can't resample our data we will have to use an informative pair; and since our whitelist will be dynamic we don't know which pair(s) to use.
+
+This is where calling `self.dp.current_whitelist()` comes in handy.
+
+```python
+class SampleStrategy(IStrategy):
+    # strategy init stuff...
+
+    timeframe = '5m'
+
+    # more strategy init stuff..
+
+    def informative_pairs(self):
+
+        # get access to all pairs available in whitelist.
+        pairs = self.dp.current_whitelist()
+        # Assign tf to each pair so they can be downloaded and cached for strategy.
+        informative_pairs = [(pair, '1d') for pair in pairs]
+        return informative_pairs
+
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+
+        inf_tf = '1d'
+        # Get the informative pair
+        informative = self.dp.get_pair_dataframe(pair=metadata['pair'], timeframe='1d')
+        # Get the 14 day rsi
+        informative['rsi'] = ta.RSI(informative, timeperiod=14)
+
+        # Rename columns to be unique
+        informative.columns = [f"{col}_{inf_tf}" for col in informative.columns]
+        # Assuming inf_tf = '1d' - then the columns will now be:
+        # date_1d, open_1d, high_1d, low_1d, close_1d, rsi_1d
+
+        # Combine the 2 dataframes
+        # all indicators on the informative sample MUST be calculated before this point
+        dataframe = pd.merge(dataframe, informative, left_on='date', right_on=f'date_{inf_tf}', how='left')
+        # FFill to have the 1d value available in every row throughout the day.
+        # Without this, comparisons would only work once per day.
+        dataframe = dataframe.ffill()
+        # Calculate rsi of the original dataframe (5m timeframe)
+        dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
+
+        # Do other stuff
+        # ...
+
+        return dataframe
+
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+
+        dataframe.loc[
+            (
+                (qtpylib.crossed_above(dataframe['rsi'], 30)) &  # Signal: RSI crosses above 30
+                (dataframe['rsi_1d'] < 30) &                     # Ensure daily RSI is < 30
+                (dataframe['volume'] > 0)                        # Ensure this candle had volume (important for backtesting)
+            ),
+            'buy'] = 1
+
+```
+
+#### *get_pair_dataframe(pair, timeframe)*
+
+``` python
+# fetch live / historical candle (OHLCV) data for the first informative pair
+if self.dp:
+    inf_pair, inf_timeframe = self.informative_pairs()[0]
+    informative = self.dp.get_pair_dataframe(pair=inf_pair,
+                                             timeframe=inf_timeframe)
+```
+
+!!! Warning "Warning about backtesting"
+    Be careful when using dataprovider in backtesting. `historic_ohlcv()` (and `get_pair_dataframe()`
+    for the backtesting runmode) provides the full time-range in one go,
+    so please be aware of it and make sure to not "look into the future" to avoid surprises when running in dry/live mode).
+
+!!! Warning "Warning in hyperopt"
+    This option cannot currently be used during hyperopt.
+
+#### *get_analyzed_dataframe(pair, timeframe)*
+
+This method is used by freqtrade internally to determine the last signal.
+It can also be used in specific callbacks to get the signal that caused the action (see [Advanced Strategy Documentation](strategy-advanced.md) for more details on available callbacks).
+
+``` python
+# fetch current dataframe
+if self.dp:
+    dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=metadata['pair'],
+                                                             timeframe=self.ticker_interval)
+```
+
+!!! Note "No data available"
+    Returns an empty dataframe if the requested pair was not cached.
+    This should not happen when using whitelisted pairs.
+
+!!! Warning "Warning in hyperopt"
+    This option cannot currently be used during hyperopt.
+
+#### *orderbook(pair, maximum)*
+
+``` python
+if self.dp:
+    if self.dp.runmode.value in ('live', 'dry_run'):
+        ob = self.dp.orderbook(metadata['pair'], 1)
+        dataframe['best_bid'] = ob['bids'][0][0]
+        dataframe['best_ask'] = ob['asks'][0][0]
+```
+
+!!! Warning
+    The order book is not part of the historic data which means backtesting and hyperopt will not work if this
+    method is used.
+
+#### *ticker(pair)*
+
+``` python
+if self.dp:
+    if self.dp.runmode.value in ('live', 'dry_run'):
+        ticker = self.dp.ticker(metadata['pair'])
+        dataframe['last_price'] = ticker['last']
+        dataframe['volume24h'] = ticker['quoteVolume']
+        dataframe['vwap'] = ticker['vwap']
+```
+
+!!! Warning
+    Although the ticker data structure is a part of the ccxt Unified Interface, the values returned by this method can
+    vary for different exchanges. For instance, many exchanges do not return `vwap` values, the FTX exchange
+    does not always fills in the `last` field (so it can be None), etc. So you need to carefully verify the ticker
+    data returned from the exchange and add appropriate error handling / defaults.
+
+***
+
 ### Additional data (Wallets)
 
 The strategy provides access to the `Wallets` object. This contains the current balances on the exchange.
@@ -427,6 +547,8 @@ if self.wallets:
 - `get_used(asset)` - currently tied up balance (open orders)
 - `get_total(asset)` - total available balance - sum of the 2 above
 
+***
+
 ### Additional data (Trades)
 
 A history of Trades can be retrieved in the strategy by querying the database.
@@ -491,7 +613,7 @@ Locks can also be lifted manually, by calling `self.unlock_pair(pair)`.
 To verify if a pair is currently locked, use `self.is_pair_locked(pair)`.
 
 !!! Note
-    Locked pairs are not persisted, so a restart of the bot, or calling `/reload_conf` will reset locked pairs.
+    Locked pairs are not persisted, so a restart of the bot, or calling `/reload_config` will reset locked pairs.
 
 !!! Warning
     Locking pairs is not functioning during backtesting.

docs/strategy_analysis_example.md

@@ -18,7 +18,7 @@ config = Configuration.from_files([])
 # config = Configuration.from_files(["config.json"])
 
 # Define some constants
-config["ticker_interval"] = "5m"
+config["timeframe"] = "5m"
 # Name of the strategy class
 config["strategy"] = "SampleStrategy"
 # Location of the data
@@ -33,7 +33,7 @@ pair = "BTC_USDT"
 from freqtrade.data.history import load_pair_history
 
 candles = load_pair_history(datadir=data_location,
-                            timeframe=config["ticker_interval"],
+                            timeframe=config["timeframe"],
                             pair=pair)
 
 # Confirm success

docs/telegram-usage.md

@@ -9,7 +9,7 @@ Telegram user id.
 
 Start a chat with the [Telegram BotFather](https://telegram.me/BotFather)
 
-Send the message `/newbot`. 
+Send the message `/newbot`.
 
 *BotFather response:*
 
@@ -47,28 +47,30 @@ Per default, the Telegram bot shows predefined commands. Some commands
 are only available by sending them to the bot. The table below list the
 official commands. You can ask at any moment for help with `/help`.
 
-|  Command | Default | Description |
-|----------|---------|-------------|
-| `/start` | | Starts the trader
-| `/stop` | | Stops the trader
-| `/stopbuy` | | Stops the trader from opening new trades. Gracefully closes open trades according to their rules.
-| `/reload_conf` | | Reloads the configuration file
-| `/show_config` | | Shows part of the current configuration with relevant settings to operation
-| `/status` | | Lists all open trades
-| `/status table` | | List all open trades in a table format. Pending buy orders are marked with an asterisk (*) Pending sell orders are marked with a double asterisk (**)
-| `/count` | | Displays number of trades used and available
-| `/profit` | | Display a summary of your profit/loss from close trades and some stats about your performance
-| `/forcesell <trade_id>` | | Instantly sells the given trade  (Ignoring `minimum_roi`).
-| `/forcesell all` | | Instantly sells all open trades (Ignoring `minimum_roi`).
-| `/forcebuy <pair> [rate]` | | Instantly buys the given pair. Rate is optional. (`forcebuy_enable` must be set to True)
-| `/performance` | | Show performance of each finished trade grouped by pair
-| `/balance` | | Show account balance per currency
-| `/daily <n>` | 7 | Shows profit or loss per day, over the last n days
-| `/whitelist` | | Show the current whitelist
-| `/blacklist [pair]` | | Show the current blacklist, or adds a pair to the blacklist.
-| `/edge` | | Show validated pairs by Edge if it is enabled.
-| `/help` | | Show help message
-| `/version` | | Show version
+|  Command | Description |
+|----------|-------------|
+| `/start` | Starts the trader
+| `/stop` | Stops the trader
+| `/stopbuy` | Stops the trader from opening new trades. Gracefully closes open trades according to their rules.
+| `/reload_config` | Reloads the configuration file
+| `/show_config` | Shows part of the current configuration with relevant settings to operation
+| `/status` | Lists all open trades
+| `/status table` | List all open trades in a table format. Pending buy orders are marked with an asterisk (*) Pending sell orders are marked with a double asterisk (**)
+| `/trades [limit]` | List all recently closed trades in a table format.
+| `/delete <trade_id>` | Delete a specific trade from the Database. Tries to close open orders. Requires manual handling of this trade on the exchange.
+| `/count` | Displays number of trades used and available
+| `/profit` | Display a summary of your profit/loss from close trades and some stats about your performance
+| `/forcesell <trade_id>` | Instantly sells the given trade  (Ignoring `minimum_roi`).
+| `/forcesell all` | Instantly sells all open trades (Ignoring `minimum_roi`).
+| `/forcebuy <pair> [rate]` | Instantly buys the given pair. Rate is optional. (`forcebuy_enable` must be set to True)
+| `/performance` | Show performance of each finished trade grouped by pair
+| `/balance` | Show account balance per currency
+| `/daily <n>` | Shows profit or loss per day, over the last n days (n defaults to 7)
+| `/whitelist` | Show the current whitelist
+| `/blacklist [pair]` | Show the current blacklist, or adds a pair to the blacklist.
+| `/edge` | Show validated pairs by Edge if it is enabled.
+| `/help` | Show help message
+| `/version` | Show version
 
 ## Telegram commands in action
 
@@ -85,14 +87,14 @@ Below, example of Telegram message you will receive for each command.
 
 ### /stopbuy
 
-> **status:** `Setting max_open_trades to 0. Run /reload_conf to reset.`
+> **status:** `Setting max_open_trades to 0. Run /reload_config to reset.`
 
 Prevents the bot from opening new trades by temporarily setting "max_open_trades" to 0. Open trades will be handled via their regular rules (ROI / Sell-signal, stoploss, ...).
 
 After this, give the bot time to close off open trades (can be checked via `/status table`).
 Once all positions are sold, run `/stop` to completely stop the bot.
 
-`/reload_conf` resets "max_open_trades" to the value set in the configuration and resets this command. 
+`/reload_config` resets "max_open_trades" to the value set in the configuration and resets this command.
 
 !!! Warning
    The stop-buy signal is ONLY active while the bot is running, and is not persisted anyway, so restarting the bot will cause this to reset.
@@ -113,6 +115,7 @@ For each open trade, the bot will send you the following message.
 ### /status table
 
 Return the status of all open trades in a table format.
+
 ```
    ID  Pair      Since    Profit
 ----  --------  -------  --------
@@ -123,6 +126,7 @@ Return the status of all open trades in a table format.
 ### /count
 
 Return the number of trades used and available.
+
 ```
 current    max
 ---------  -----
@@ -208,15 +212,15 @@ Shows the current whitelist
 
 Shows the current blacklist.
 If Pair is set, then this pair will be added to the pairlist.
-Also supports multiple pairs, seperated by a space.
-Use `/reload_conf` to reset the blacklist.
+Also supports multiple pairs, separated by a space.
+Use `/reload_config` to reset the blacklist.
 
 > Using blacklist `StaticPairList` with 2 pairs  
 >`DODGE/BTC`, `HOT/BTC`.
 
 ### /edge
 
-Shows pairs validated by Edge along with their corresponding winrate, expectancy and stoploss values.
+Shows pairs validated by Edge along with their corresponding win-rate, expectancy and stoploss values.
 
 > **Edge only validated following pairs:**
 ```

docs/utils.md

@@ -62,7 +62,7 @@ $ freqtrade new-config --config config_binance.json
 ? Please insert your stake currency: BTC
 ? Please insert your stake amount: 0.05
 ? Please insert max_open_trades (Integer or 'unlimited'): 3
-? Please insert your timeframe (ticker interval): 5m
+? Please insert your desired timeframe (e.g. 5m): 5m
 ? Please insert your display Currency (for reporting): USD
 ? Select exchange  binance
 ? Do you want to enable Telegram?  No
@@ -77,7 +77,7 @@ Results will be located in `user_data/strategies/<strategyclassname>.py`.
 
 ``` output
 usage: freqtrade new-strategy [-h] [--userdir PATH] [-s NAME]
-                              [--template {full,minimal}]
+                              [--template {full,minimal,advanced}]
 
 optional arguments:
   -h, --help            show this help message and exit
@@ -86,10 +86,10 @@ optional arguments:
   -s NAME, --strategy NAME
                         Specify strategy class name which will be used by the
                         bot.
-  --template {full,minimal}
-                        Use a template which is either `minimal` or `full`
-                        (containing multiple sample indicators). Default:
-                        `full`.
+  --template {full,minimal,advanced}
+                        Use a template which is either `minimal`, `full`
+                        (containing multiple sample indicators) or `advanced`.
+                        Default: `full`.
 
 ```
 
@@ -105,6 +105,12 @@ With custom user directory
 freqtrade new-strategy --userdir ~/.freqtrade/ --strategy AwesomeStrategy
 ```
 
+Using the advanced template (populates all optional functions and methods)
+
+```bash
+freqtrade new-strategy --strategy AwesomeStrategy --template advanced
+```
+
 ## Create new hyperopt
 
 Creates a new hyperopt from a template similar to SampleHyperopt.
@@ -114,7 +120,7 @@ Results will be located in `user_data/hyperopts/<classname>.py`.
 
 ``` output
 usage: freqtrade new-hyperopt [-h] [--userdir PATH] [--hyperopt NAME]
-                              [--template {full,minimal}]
+                              [--template {full,minimal,advanced}]
 
 optional arguments:
   -h, --help            show this help message and exit
@@ -122,10 +128,10 @@ optional arguments:
                         Path to userdata directory.
   --hyperopt NAME       Specify hyperopt class name which will be used by the
                         bot.
-  --template {full,minimal}
-                        Use a template which is either `minimal` or `full`
-                        (containing multiple sample indicators). Default:
-                        `full`.
+  --template {full,minimal,advanced}
+                        Use a template which is either `minimal`, `full`
+                        (containing multiple sample indicators) or `advanced`.
+                        Default: `full`.
 ```
 
 ### Sample usage of new-hyperopt
@@ -519,3 +525,48 @@ Prints JSON data with details for the last best epoch (i.e., the best of all epo
 ```
 freqtrade hyperopt-show --best -n -1 --print-json --no-header
 ```
+
+## Show trades
+
+Print selected (or all) trades from database to screen.
+
+```
+usage: freqtrade show-trades [-h] [-v] [--logfile FILE] [-V] [-c PATH]
+                             [-d PATH] [--userdir PATH] [--db-url PATH]
+                             [--trade-ids TRADE_IDS [TRADE_IDS ...]]
+                             [--print-json]
+
+optional arguments:
+  -h, --help            show this help message and exit
+  --db-url PATH         Override trades database URL, this is useful in custom
+                        deployments (default: `sqlite:///tradesv3.sqlite` for
+                        Live Run mode, `sqlite:///tradesv3.dryrun.sqlite` for
+                        Dry Run).
+  --trade-ids TRADE_IDS [TRADE_IDS ...]
+                        Specify the list of trade ids.
+  --print-json          Print output in JSON format.
+
+Common arguments:
+  -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
+  --logfile FILE        Log to the file specified. Special values are:
+                        'syslog', 'journald'. See the documentation for more
+                        details.
+  -V, --version         show program's version number and exit
+  -c PATH, --config PATH
+                        Specify configuration file (default:
+                        `userdir/config.json` or `config.json` whichever
+                        exists). Multiple --config options may be used. Can be
+                        set to `-` to read config from stdin.
+  -d PATH, --datadir PATH
+                        Path to directory with historical backtesting data.
+  --userdir PATH, --user-data-dir PATH
+                        Path to userdata directory.
+```
+
+### Examples
+
+Print trades with id 2 and 3 as json
+
+``` bash
+freqtrade show-trades --db-url sqlite:///tradesv3.sqlite --trade-ids 2 3 --print-json
+```

docs/webhook-config.md

@@ -47,6 +47,7 @@ Different payloads can be configured for different events. Not all fields are ne
 The fields in `webhook.webhookbuy` are filled when the bot executes a buy. Parameters are filled using string.format.
 Possible parameters are:
 
+* `trade_id`
 * `exchange`
 * `pair`
 * `limit`
@@ -63,6 +64,7 @@ Possible parameters are:
 The fields in `webhook.webhookbuycancel` are filled when the bot cancels a buy order. Parameters are filled using string.format.
 Possible parameters are:
 
+* `trade_id`
 * `exchange`
 * `pair`
 * `limit`
@@ -79,6 +81,7 @@ Possible parameters are:
 The fields in `webhook.webhooksell` are filled when the bot sells a trade. Parameters are filled using string.format.
 Possible parameters are:
 
+* `trade_id`
 * `exchange`
 * `pair`
 * `gain`
@@ -100,6 +103,7 @@ Possible parameters are:
 The fields in `webhook.webhooksellcancel` are filled when the bot cancels a sell order. Parameters are filled using string.format.
 Possible parameters are:
 
+* `trade_id`
 * `exchange`
 * `pair`
 * `gain`