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Update docs to include info on new functionality.

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eSeR1805 2022-04-16 14:42:41 +03:00
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4
docs/bot-basics.md
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@ -24,7 +24,7 @@ By default, loop runs every few seconds (`internals.process_throttle_secs`) and
* 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)
* 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.
@ -34,6 +34,8 @@ By default, loop runs every few seconds (`internals.process_throttle_secs`) and
* Check timeouts for open orders.
* Calls `check_entry_timeout()` strategy callback for open entry orders.
* Calls `check_exit_timeout()` strategy callback for open exit orders.
* Check readjustment request for open orders.
* Calls `readjust_entry_price()` strategy callback for open entry orders.
* Verifies existing positions and eventually places exit orders.
* Considers stoploss, ROI and exit-signal, `custom_exit()` and `custom_stoploss()`.
* Determine exit-price based on `exit_pricing` configuration setting or by using the `custom_exit_price()` callback.

73
docs/strategy-callbacks.md
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@ -16,6 +16,7 @@ Currently available callbacks:
* [`confirm_trade_entry()`](#trade-entry-buy-order-confirmation)
* [`confirm_trade_exit()`](#trade-exit-sell-order-confirmation)
* [`adjust_trade_position()`](#adjust-trade-position)
* [`readjust_entry_price()`](#readjust-entry-price)
* [`leverage()`](#leverage-callback)
!!! Tip "Callback calling sequence"
@ -365,13 +366,13 @@ class AwesomeStrategy(IStrategy):
# ... populate_* methods
def custom_entry_price(self, pair: str, current_time: datetime, proposed_rate: float,
def custom_entry_price(self, pair: str, current_time: datetime, proposed_rate: float,
entry_tag: Optional[str], side: str, **kwargs) -> float:
dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=pair,
timeframe=self.timeframe)
new_entryprice = dataframe['bollinger_10_lowerband'].iat[-1]
return new_entryprice
def custom_exit_price(self, pair: str, trade: Trade,
@ -381,14 +382,14 @@ class AwesomeStrategy(IStrategy):
dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=pair,
timeframe=self.timeframe)
new_exitprice = dataframe['bollinger_10_upperband'].iat[-1]
return new_exitprice
```
!!! Warning
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.
**Example**:
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.
**Example**:
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.
!!! Warning "Backtesting"
@ -430,7 +431,7 @@ class AwesomeStrategy(IStrategy):
'exit': 60 * 25
}
def check_entry_timeout(self, pair: str, trade: 'Trade', order: dict,
def check_entry_timeout(self, pair: str, trade: 'Trade', order: dict,
current_time: datetime, **kwargs) -> bool:
if trade.open_rate > 100 and trade.open_date_utc < current_time - timedelta(minutes=5):
return True
@ -508,7 +509,7 @@ class AwesomeStrategy(IStrategy):
# ... populate_* methods
def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
time_in_force: str, current_time: datetime, entry_tag: Optional[str],
time_in_force: str, current_time: datetime, entry_tag: Optional[str],
side: str, **kwargs) -> bool:
"""
Called right before placing a entry order.
@ -616,35 +617,35 @@ from freqtrade.persistence import Trade
class DigDeeperStrategy(IStrategy):
position_adjustment_enable = True
# Attempts to handle large drops with DCA. High stoploss is required.
stoploss = -0.30
# ... populate_* methods
# Example specific variables
max_entry_position_adjustment = 3
# This number is explained a bit further down
max_dca_multiplier = 5.5
# This is called when placing the initial order (opening trade)
def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
proposed_stake: float, min_stake: float, max_stake: float,
entry_tag: Optional[str], side: str, **kwargs) -> float:
# We need to leave most of the funds for possible further DCA orders
# This also applies to fixed stakes
return proposed_stake / self.max_dca_multiplier
def adjust_trade_position(self, trade: Trade, current_time: datetime,
current_rate: float, current_profit: float, min_stake: float,
max_stake: float, **kwargs):
"""
Custom trade adjustment logic, returning the stake amount that a trade should be increased.
This means extra buy orders with additional fees.
:param trade: trade object.
:param current_time: datetime object, containing the current datetime
:param current_rate: Current buy rate.
@ -654,7 +655,7 @@ class DigDeeperStrategy(IStrategy):
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
:return float: Stake amount to adjust your trade
"""
if current_profit > -0.05:
return None
@ -689,6 +690,46 @@ class DigDeeperStrategy(IStrategy):
```
## Readjust Entry Price
The `readjust_entry_price()` callback may be used by strategy developer to refresh/replace limit orders upon arrival of new candles.
Be aware that `custom_entry_price()` is still the one dictating initial entry limit order price target at the time of entry trigger.
!!! Warning This mechanism will not trigger if previous orders were partially or fully filled.
!!! Warning Entry `unfilledtimeout` mechanism takes precedence over this. Be sure to update timeout values to match your expectancy.
```python
from freqtrade.persistence import Trade
from datetime import timedelta
class AwesomeStrategy(IStrategy):
# ... populate_* methods
def readjust_entry_price(self, pair: str, current_time: datetime, proposed_rate: float,
entry_tag: Optional[str], side: str, **kwargs) -> float:
"""
Entry price readjustment logic, returning the readjusted entry price.
:param pair: Pair that's currently analyzed
:param trade: Trade object.
:param current_time: datetime object, containing the current datetime
:param proposed_rate: Rate, calculated based on pricing settings in exit_pricing.
:param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
:param side: 'long' or 'short' - indicating the direction of the proposed trade
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
:return float: New entry price value if provided
"""
# Limit orders to use and follow SMA200 as price target for the first 10 minutes since entry trigger for BTC/USDT pair.
if pair == 'BTC/USDT' and entry_tag == 'long_sma200' and side == 'long' and (current_time - timedelta(minutes=10) > trade.open_date_utc:
dataframe, _ = self.dp.get_analyzed_dataframe(pair=pair, timeframe=self.timeframe)
current_candle = dataframe.iloc[-1].squeeze()
return current_candle['sma_200']
return proposed_rate
```
## Leverage Callback
When trading in markets that allow leverage, this method must return the desired Leverage (Defaults to 1 -> No leverage).