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Merge pull request #3430 from freqtrade/timeframe

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ticker_interval -> timeframe
This commit is contained in:
Matthias
2020-06-15 13:47:26 +02:00
committed by GitHub
parent fad4723eae a3506f4d8e
commit 761407f74d
69 changed files with 309 additions and 230 deletions
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10
docs/backtesting.md
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@@ -12,7 +12,7 @@ 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.
@@ -35,7 +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
@@ -58,7 +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.
@@ -228,13 +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.

50
docs/bot-usage.md
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@@ -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.
.
```
@@ -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

4
docs/configuration.md
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@@ -47,7 +47,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi
| `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
@@ -126,7 +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`

2
docs/edge.md
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@@ -155,7 +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

10
docs/hyperopt.md
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@@ -124,9 +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
@@ -403,7 +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 | |
| ------ | ------ | ----------------- | -------- | ----------- | ---------- | ----------------- | ------------ | ----------------- |
@@ -412,7 +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.

15
docs/plotting.md
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@@ -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

2
docs/sql_cheatsheet.md
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@@ -70,7 +70,7 @@ CREATE TABLE trades
min_rate FLOAT,
sell_reason VARCHAR,
strategy VARCHAR,
ticker_interval INTEGER,
timeframe INTEGER,
PRIMARY KEY (id),
CHECK (is_open IN (0, 1))
);

16
docs/strategy-customization.md
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@@ -142,7 +142,7 @@ By letting the bot know how much history is needed, backtest trades can start at
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.
@@ -248,7 +248,7 @@ 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
@@ -256,12 +256,12 @@ 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
}
```
@@ -290,7 +290,7 @@ 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
@@ -400,7 +400,7 @@ This is where calling `self.dp.current_whitelist()` comes in handy.
class SampleStrategy(IStrategy):
# strategy init stuff...
ticker_interval = '5m'
timeframe = '5m'
# more strategy init stuff..

4
docs/strategy_analysis_example.md
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@@ -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

2
docs/utils.md
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@@ -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