mirror of
https://github.com/freqtrade/freqtrade.git
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Merge branch 'develop' into pairlocks_direction
This commit is contained in:
@@ -299,6 +299,7 @@ A backtesting result will look like that:
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| Final balance | 0.01762792 BTC |
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| Absolute profit | 0.00762792 BTC |
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| Total profit % | 76.2% |
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| CAGR % | 460.87% |
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| Trades per day | 3.575 |
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| Avg. stake amount | 0.001 BTC |
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| Total trade volume | 0.429 BTC |
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@@ -388,6 +389,7 @@ It contains some useful key metrics about performance of your strategy on backte
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| Final balance | 0.01762792 BTC |
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| Absolute profit | 0.00762792 BTC |
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| Total profit % | 76.2% |
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| CAGR % | 460.87% |
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| Avg. stake amount | 0.001 BTC |
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| Total trade volume | 0.429 BTC |
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| | |
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@@ -51,6 +51,14 @@ Please read the [exchange specific notes](exchanges.md) to learn about eventual,
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- [X] [OKX](https://okx.com/) (Former OKEX)
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- [ ] [potentially many others through <img alt="ccxt" width="30px" src="assets/ccxt-logo.svg" />](https://github.com/ccxt/ccxt/). _(We cannot guarantee they will work)_
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### Experimentally, freqtrade also supports futures on the following exchanges:
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- [X] [Binance](https://www.binance.com/)
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- [X] [Gate.io](https://www.gate.io/ref/6266643)
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- [X] [OKX](https://okx.com/).
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Please make sure to read the [exchange specific notes](exchanges.md), as well as the [trading with leverage](leverage.md) documentation before diving in.
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### Community tested
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Exchanges confirmed working by the community:
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@@ -1,5 +1,5 @@
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mkdocs==1.3.0
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mkdocs-material==8.2.9
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mkdocs-material==8.2.10
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mdx_truly_sane_lists==1.2
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pymdown-extensions==9.3
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pymdown-extensions==9.4
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jinja2==3.1.1
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@@ -7,6 +7,7 @@ Depending on the callback used, they may be called when entering / exiting a tra
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Currently available callbacks:
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* [`bot_start()`](#bot-start)
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* [`bot_loop_start()`](#bot-loop-start)
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* [`custom_stake_amount()`](#stake-size-management)
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* [`custom_exit()`](#custom-exit-signal)
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@@ -21,6 +22,29 @@ Currently available callbacks:
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!!! Tip "Callback calling sequence"
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You can find the callback calling sequence in [bot-basics](bot-basics.md#bot-execution-logic)
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## Bot start
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A simple callback which is called once when the strategy is loaded.
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This can be used to perform actions that must only be performed once and runs after dataprovider and wallet are set
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``` python
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import requests
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class AwesomeStrategy(IStrategy):
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# ... populate_* methods
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def bot_start(self, **kwargs) -> None:
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"""
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Called only once after bot instantiation.
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:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
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"""
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if self.config['runmode'].value in ('live', 'dry_run'):
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# Assign this to the class by using self.*
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# can then be used by populate_* methods
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self.cust_remote_data = requests.get('https://some_remote_source.example.com')
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```
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## Bot loop start
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A simple callback which is called once at the start of every bot throttling iteration (roughly every 5 seconds, unless configured differently).
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@@ -122,11 +146,11 @@ See [Dataframe access](strategy-advanced.md#dataframe-access) for more informati
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## Custom stoploss
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Called for open trade every throttling iteration (roughly every 5 seconds) until a trade is closed.
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Called for open trade every iteration (roughly every 5 seconds) until a trade is closed.
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The usage of the custom stoploss method must be enabled by setting `use_custom_stoploss=True` on the strategy object.
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The stoploss price can only ever move upwards - if the stoploss value returned from `custom_stoploss` would result in a lower stoploss price than was previously set, it will be ignored. The traditional `stoploss` value serves as an absolute lower level and will be instated as the initial stoploss (before this method is called for the first time for a trade).
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The stoploss price can only ever move upwards - if the stoploss value returned from `custom_stoploss` would result in a lower stoploss price than was previously set, it will be ignored. The traditional `stoploss` value serves as an absolute lower level and will be instated as the initial stoploss (before this method is called for the first time for a trade), and is still mandatory.
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The method must return a stoploss value (float / number) as a percentage of the current price.
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E.g. If the `current_rate` is 200 USD, then returning `0.02` will set the stoploss price 2% lower, at 196 USD.
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@@ -365,30 +389,30 @@ class AwesomeStrategy(IStrategy):
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# ... populate_* methods
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def custom_entry_price(self, pair: str, current_time: datetime, proposed_rate: float,
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def custom_entry_price(self, pair: str, current_time: datetime, proposed_rate: float,
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entry_tag: Optional[str], side: str, **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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current_profit: float, exit_tag: Optional[str], **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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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, which is 2% below the current (proposed) rate.
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!!! Warning "Backtesting"
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@@ -430,7 +454,7 @@ class AwesomeStrategy(IStrategy):
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'exit': 60 * 25
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}
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def check_entry_timeout(self, pair: str, trade: 'Trade', order: 'Order',
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def check_entry_timeout(self, pair: str, trade: 'Trade', order: 'Order',
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current_time: datetime, **kwargs) -> bool:
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if trade.open_rate > 100 and trade.open_date_utc < current_time - timedelta(minutes=5):
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return True
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@@ -508,7 +532,7 @@ class AwesomeStrategy(IStrategy):
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# ... populate_* methods
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def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
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time_in_force: str, current_time: datetime, entry_tag: Optional[str],
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time_in_force: str, current_time: datetime, entry_tag: Optional[str],
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side: str, **kwargs) -> bool:
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"""
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Called right before placing a entry order.
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@@ -616,35 +640,35 @@ from freqtrade.persistence import Trade
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class DigDeeperStrategy(IStrategy):
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position_adjustment_enable = True
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# Attempts to handle large drops with DCA. High stoploss is required.
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stoploss = -0.30
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# ... populate_* methods
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# Example specific variables
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max_entry_position_adjustment = 3
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# This number is explained a bit further down
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max_dca_multiplier = 5.5
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# This is called when placing the initial order (opening trade)
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def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
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proposed_stake: float, min_stake: float, max_stake: float,
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entry_tag: Optional[str], side: str, **kwargs) -> float:
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# We need to leave most of the funds for possible further DCA orders
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# This also applies to fixed stakes
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return proposed_stake / self.max_dca_multiplier
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def adjust_trade_position(self, trade: Trade, current_time: datetime,
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current_rate: float, current_profit: float, min_stake: float,
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max_stake: float, **kwargs):
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"""
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Custom trade adjustment logic, returning the stake amount that a trade should be increased.
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This means extra buy orders with additional fees.
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:param trade: trade object.
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:param current_time: datetime object, containing the current datetime
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:param current_rate: Current buy rate.
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@@ -654,7 +678,7 @@ class DigDeeperStrategy(IStrategy):
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:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
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:return float: Stake amount to adjust your trade
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"""
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if current_profit > -0.05:
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return None
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