Merge branch 'develop' into feat/backtest_detail
This commit is contained in:
@@ -335,7 +335,7 @@ Once the optimized parameters and conditions have been implemented into your str
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To achieve same results (number of trades, their durations, profit, etc.) than during Hyperopt, please use same configuration and parameters (timerange, timeframe, ...) used for hyperopt `--dmmp`/`--disable-max-market-positions` and `--eps`/`--enable-position-stacking` for Backtesting.
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Should results don't match, please double-check to make sure you transferred all conditions correctly.
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Should results not match, please double-check to make sure you transferred all conditions correctly.
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Pay special care to the stoploss (and trailing stoploss) parameters, as these are often set in configuration files, which override changes to the strategy.
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You should also carefully review the log of your backtest to ensure that there were no parameters inadvertently set by the configuration (like `stoploss` or `trailing_stop`).
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@@ -66,7 +66,7 @@ optional arguments:
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this together with `--export trades`, the strategy-
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name is injected into the filename (so `backtest-
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data.json` becomes `backtest-data-
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DefaultStrategy.json`
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SampleStrategy.json`
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--export {none,trades}
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Export backtest results (default: trades).
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--export-filename PATH
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@@ -7,7 +7,7 @@ This page provides you some basic concepts on how Freqtrade works and operates.
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* **Strategy**: Your trading strategy, telling the bot what to do.
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* **Trade**: Open position.
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* **Open Order**: Order which is currently placed on the exchange, and is not yet complete.
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* **Pair**: Tradable pair, usually in the format of Quote/Base (e.g. XRP/USDT).
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* **Pair**: Tradable pair, usually in the format of Base/Quote (e.g. XRP/USDT).
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* **Timeframe**: Candle length to use (e.g. `"5m"`, `"1h"`, ...).
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* **Indicators**: Technical indicators (SMA, EMA, RSI, ...).
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* **Limit order**: Limit orders which execute at the defined limit price or better.
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@@ -36,11 +36,12 @@ By default, loop runs every few seconds (`internals.process_throttle_secs`) and
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* Calls `check_sell_timeout()` strategy callback for open sell orders.
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* Verifies existing positions and eventually places sell orders.
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* Considers stoploss, ROI and sell-signal, `custom_sell()` and `custom_stoploss()`.
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* Determine sell-price based on `ask_strategy` configuration setting.
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* Determine sell-price based on `ask_strategy` configuration setting or by using the `custom_exit_price()` callback.
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* Before a sell order is placed, `confirm_trade_exit()` strategy callback is called.
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* Check if trade-slots are still available (if `max_open_trades` is reached).
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* Verifies buy signal trying to enter new positions.
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* Determine buy-price based on `bid_strategy` configuration setting.
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* Determine buy-price based on `bid_strategy` configuration setting, or by using the `custom_entry_price()` callback.
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* Determine stake size by calling the `custom_stake_amount()` callback.
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* Before a buy order is placed, `confirm_trade_entry()` strategy callback is called.
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This loop will be repeated again and again until the bot is stopped.
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@@ -105,11 +105,12 @@ Mandatory parameters are marked as **Required**, which means that they are requi
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| `ask_strategy.order_book_top` | Bot will use the top N rate in Order Book "price_side" to sell. I.e. a value of 2 will allow the bot to pick the 2nd ask rate in [Order Book Asks](#sell-price-with-orderbook-enabled)<br>*Defaults to `1`.* <br> **Datatype:** Positive Integer
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| `use_sell_signal` | Use sell signals produced by the strategy in addition to the `minimal_roi`. [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `true`.* <br> **Datatype:** Boolean
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| `sell_profit_only` | Wait until the bot reaches `sell_profit_offset` before taking a sell decision. [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `false`.* <br> **Datatype:** Boolean
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| `sell_profit_offset` | Sell-signal is only active above this value. [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `0.0`.* <br> **Datatype:** Float (as ratio)
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| `sell_profit_offset` | Sell-signal is only active above this value. Only active in combination with `sell_profit_only=True`. [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `0.0`.* <br> **Datatype:** Float (as ratio)
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| `ignore_roi_if_buy_signal` | Do not sell if the buy signal is still active. This setting takes preference over `minimal_roi` and `use_sell_signal`. [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `false`.* <br> **Datatype:** Boolean
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| `ignore_buying_expired_candle_after` | Specifies the number of seconds until a buy signal is no longer used. <br> **Datatype:** Integer
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| `order_types` | Configure order-types depending on the action (`"buy"`, `"sell"`, `"stoploss"`, `"stoploss_on_exchange"`). [More information below](#understand-order_types). [Strategy Override](#parameters-in-the-strategy).<br> **Datatype:** Dict
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| `order_time_in_force` | Configure time in force for buy and sell orders. [More information below](#understand-order_time_in_force). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** Dict
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| `custom_price_max_distance_ratio` | Configure maximum distance ratio between current and custom entry or exit price. <br>*Defaults to `0.02` 2%).*<br> **Datatype:** Positive float
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| `exchange.name` | **Required.** Name of the exchange class to use. [List below](#user-content-what-values-for-exchangename). <br> **Datatype:** String
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| `exchange.sandbox` | Use the 'sandbox' version of the exchange, where the exchange provides a sandbox for risk-free integration. See [here](sandbox-testing.md) in more details.<br> **Datatype:** Boolean
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| `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
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@@ -105,7 +105,7 @@ To use subaccounts with FTX, you need to edit the configuration and add the foll
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## Kucoin
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Kucoin requries a passphrase for each api key, you will therefore need to add this key into the configuration so your exchange section looks as follows:
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Kucoin requires a passphrase for each api key, you will therefore need to add this key into the configuration so your exchange section looks as follows:
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```json
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"exchange": {
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@@ -48,7 +48,7 @@ usage: freqtrade hyperopt [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH]
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[--hyperopt-path PATH] [--eps] [--dmmp]
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[--enable-protections]
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[--dry-run-wallet DRY_RUN_WALLET] [-e INT]
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[--spaces {all,buy,sell,roi,stoploss,trailing,default} [{all,buy,sell,roi,stoploss,trailing,default} ...]]
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[--spaces {all,buy,sell,roi,stoploss,trailing,protection,default} [{all,buy,sell,roi,stoploss,trailing,protection,default} ...]]
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[--print-all] [--no-color] [--print-json] [-j JOBS]
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[--random-state INT] [--min-trades INT]
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[--hyperopt-loss NAME] [--disable-param-export]
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@@ -92,7 +92,7 @@ optional arguments:
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Starting balance, used for backtesting / hyperopt and
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dry-runs.
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-e INT, --epochs INT Specify number of epochs (default: 100).
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--spaces {all,buy,sell,roi,stoploss,trailing,default} [{all,buy,sell,roi,stoploss,trailing,default} ...]
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--spaces {all,buy,sell,roi,stoploss,trailing,protection,default} [{all,buy,sell,roi,stoploss,trailing,protection,default} ...]
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Specify which parameters to hyperopt. Space-separated
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list.
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--print-all Print all results, not only the best ones.
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@@ -456,7 +456,7 @@ class MyAwesomeStrategy(IStrategy):
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"only_per_pair": False
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})
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return protection
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return prot
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def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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# ...
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@@ -576,7 +576,8 @@ Legal values are:
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* `roi`: just optimize the minimal profit table for your strategy
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* `stoploss`: search for the best stoploss value
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* `trailing`: search for the best trailing stop values
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* `default`: `all` except `trailing`
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* `protection`: search for the best protection parameters (read the [protections section](#optimizing-protections) on how to properly define these)
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* `default`: `all` except `trailing` and `protection`
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* space-separated list of any of the above values for example `--spaces roi stoploss`
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The default Hyperopt Search Space, used when no `--space` command line option is specified, does not include the `trailing` hyperspace. We recommend you to run optimization for the `trailing` hyperspace separately, when the best parameters for other hyperspaces were found, validated and pasted into your custom strategy.
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@@ -826,8 +827,8 @@ After you run Hyperopt for the desired amount of epochs, you can later list all
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Once the optimized strategy has been implemented into your strategy, you should backtest this strategy to make sure everything is working as expected.
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To achieve same results (number of trades, their durations, profit, etc.) than during Hyperopt, please use same configuration and parameters (timerange, timeframe, ...) used for hyperopt `--dmmp`/`--disable-max-market-positions` and `--eps`/`--enable-position-stacking` for Backtesting.
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To achieve same the results (number of trades, their durations, profit, etc.) as during Hyperopt, please use the same configuration and parameters (timerange, timeframe, ...) used for hyperopt `--dmmp`/`--disable-max-market-positions` and `--eps`/`--enable-position-stacking` for Backtesting.
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Should results don't match, please double-check to make sure you transferred all conditions correctly.
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Should results not match, please double-check to make sure you transferred all conditions correctly.
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Pay special care to the stoploss (and trailing stoploss) parameters, as these are often set in configuration files, which override changes to the strategy.
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You should also carefully review the log of your backtest to ensure that there were no parameters inadvertently set by the configuration (like `stoploss` or `trailing_stop`).
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@@ -1,4 +1,4 @@
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mkdocs==1.2.2
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mkdocs-material==7.2.2
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mkdocs-material==7.2.5
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mdx_truly_sane_lists==1.2
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pymdown-extensions==8.2
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@@ -357,6 +357,55 @@ See [Dataframe access](#dataframe-access) for more information about dataframe u
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---
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## Custom order price rules
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By default, freqtrade use the orderbook to automatically set an order price([Relevant documentation](configuration.md#prices-used-for-orders)), you also have the option to create custom order prices based on your strategy.
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You can use this feature by creating a `custom_entry_price()` function in your strategy file to customize entry prices and `custom_exit_price()` for exits.
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!!! Note
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If your custom pricing function return None or an invalid value, price will fall back to `proposed_rate`, which is based on the regular pricing configuration.
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### Custom order entry and exit price example
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``` python
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from datetime import datetime, timedelta, timezone
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from freqtrade.persistence import Trade
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class AwesomeStrategy(IStrategy):
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# ... populate_* methods
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def custom_entry_price(self, pair: str, current_time: datetime,
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proposed_rate, **kwargs) -> float:
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dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=pair,
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timeframe=self.timeframe)
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new_entryprice = dataframe['bollinger_10_lowerband'].iat[-1]
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return new_entryprice
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def custom_exit_price(self, pair: str, trade: Trade,
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current_time: datetime, proposed_rate: float,
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current_profit: float, **kwargs) -> float:
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dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=pair,
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timeframe=self.timeframe)
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new_exitprice = dataframe['bollinger_10_upperband'].iat[-1]
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return new_exitprice
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```
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!!! Warning
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Modifying entry and exit prices will only work for limit orders. Depending on the price chosen, this can result in a lot of unfilled orders. By default the maximum allowed distance between the current price and the custom price is 2%, this value can be changed in config with the `custom_price_max_distance_ratio` parameter.
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!!! Example
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If the new_entryprice is 97, the proposed_rate is 100 and the `custom_price_max_distance_ratio` is set to 2%, The retained valid custom entry price will be 98.
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!!! Warning "No backtesting support"
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Custom entry-prices are currently not supported during backtesting.
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## Custom order timeout rules
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Simple, time-based order-timeouts can be configured either via strategy or in the configuration in the `unfilledtimeout` section.
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@@ -228,7 +228,7 @@ graph = generate_candlestick_graph(pair=pair,
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# Show graph inline
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# graph.show()
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# Render graph in a seperate window
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# Render graph in a separate window
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graph.show(renderer="browser")
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```
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Reference in New Issue
Block a user