mirror of
https://github.com/freqtrade/freqtrade.git
synced 2024-11-10 10:21:59 +00:00
Merge branch 'feat/short' into pr/samgermain/5780
This commit is contained in:
Matthias
commit
51e54a666c
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@ -204,9 +204,8 @@ There are several methods to configure how much of the stake currency the bot wi
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#### Minimum trade stake
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The minimum stake amount will depend on exchange and pair and is usually listed in the exchange support pages.
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Assuming the minimum tradable amount for XRP/USD is 20 XRP (given by the exchange), and the price is 0.6$.
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The minimum stake amount to buy this pair is, therefore, `20 * 0.6 ~= 12`.
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Assuming the minimum tradable amount for XRP/USD is 20 XRP (given by the exchange), and the price is 0.6$, the minimum stake amount to buy this pair is `20 * 0.6 ~= 12`.
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This exchange has also a limit on USD - where all orders must be > 10$ - which however does not apply in this case.
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To guarantee safe execution, freqtrade will not allow buying with a stake-amount of 10.1$, instead, it'll make sure that there's enough space to place a stoploss below the pair (+ an offset, defined by `amount_reserve_percent`, which defaults to 5%).
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@ -292,7 +292,7 @@ If the trading range over the last 10 days is <1% or >99%, remove the pair from
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#### VolatilityFilter
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Volatility is the degree of historical variation of a pairs over time, is is measured by the standard deviation of logarithmic daily returns. Returns are assumed to be normally distributed, although actual distribution might be different. In a normal distribution, 68% of observations fall within one standard deviation and 95% of observations fall within two standard deviations. Assuming a volatility of 0.05 means that the expected returns for 20 out of 30 days is expected to be less than 5% (one standard deviation). Volatility is a positive ratio of the expected deviation of return and can be greater than 1.00. Please refer to the wikipedia definition of [`volatility`](https://en.wikipedia.org/wiki/Volatility_(finance)).
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Volatility is the degree of historical variation of a pairs over time, it is measured by the standard deviation of logarithmic daily returns. Returns are assumed to be normally distributed, although actual distribution might be different. In a normal distribution, 68% of observations fall within one standard deviation and 95% of observations fall within two standard deviations. Assuming a volatility of 0.05 means that the expected returns for 20 out of 30 days is expected to be less than 5% (one standard deviation). Volatility is a positive ratio of the expected deviation of return and can be greater than 1.00. Please refer to the wikipedia definition of [`volatility`](https://en.wikipedia.org/wiki/Volatility_(finance)).
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This filter removes pairs if the average volatility over a `lookback_days` days is below `min_volatility` or above `max_volatility`. Since this is a filter that requires additional data, the results are cached for `refresh_period`.
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@ -3,7 +3,7 @@ import json
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import logging
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from datetime import datetime
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from pathlib import Path
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from typing import Any, Dict, List, Optional, Tuple
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from typing import Dict, List, Optional, Tuple
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import arrow
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import ccxt
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@ -119,10 +119,6 @@ class Binance(Exchange):
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except ccxt.BaseError as e:
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raise OperationalException(e) from e
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def market_is_future(self, market: Dict[str, Any]) -> bool:
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# TODO-lev: This should be unified in ccxt to "swap"...
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return market.get('future', False) is True
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@retrier
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def fill_leverage_brackets(self):
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"""
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@ -338,7 +338,7 @@ class Exchange:
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return self.markets.get(pair, {}).get('base', '')
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def market_is_future(self, market: Dict[str, Any]) -> bool:
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return market.get('swap', False) is True
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return market.get(self._ft_has["ccxt_futures_name"], False) is True
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def market_is_spot(self, market: Dict[str, Any]) -> bool:
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return market.get('spot', False) is True
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@ -20,7 +20,8 @@ class Ftx(Exchange):
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_ft_has: Dict = {
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"stoploss_on_exchange": True,
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"ohlcv_candle_limit": 1500,
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"mark_ohlcv_price": "index"
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"mark_ohlcv_price": "index",
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"ccxt_futures_name": "future"
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}
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_supported_trading_mode_collateral_pairs: List[Tuple[TradingMode, Collateral]] = [
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@ -159,7 +160,3 @@ class Ftx(Exchange):
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if order['type'] == 'stop':
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return safe_value_fallback2(order, order, 'id_stop', 'id')
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return order['id']
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def market_is_future(self, market: Dict[str, Any]) -> bool:
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# TODO-lev: This should be unified in ccxt to "swap"...
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return market.get('future', False) is True
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@ -70,7 +70,7 @@ class Backtesting:
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self.all_results: Dict[str, Dict] = {}
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self._exchange_name = self.config['exchange']['name']
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self.exchange = ExchangeResolver.load_exchange(self._exchange_name, self.config)
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self.dataprovider = DataProvider(self.config, None)
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self.dataprovider = DataProvider(self.config, self.exchange)
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if self.config.get('strategy_list', None):
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for strat in list(self.config['strategy_list']):
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@ -144,6 +144,7 @@ class OrderTypes(BaseModel):
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class ShowConfig(BaseModel):
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version: str
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api_version: float
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dry_run: bool
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trading_mode: str
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short_allowed: bool
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@ -26,6 +26,11 @@ from freqtrade.rpc.rpc import RPCException
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logger = logging.getLogger(__name__)
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# API version
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# Pre-1.1, no version was provided
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# Version increments should happen in "small" steps (1.1, 1.12, ...) unless big changes happen.
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API_VERSION = 1.1
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# Public API, requires no auth.
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router_public = APIRouter()
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# Private API, protected by authentication
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@ -117,7 +122,9 @@ def show_config(rpc: Optional[RPC] = Depends(get_rpc_optional), config=Depends(g
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state = ''
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if rpc:
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state = rpc._freqtrade.state
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return RPC._rpc_show_config(config, state)
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resp = RPC._rpc_show_config(config, state)
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resp['api_version'] = API_VERSION
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return resp
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@router.post('/forcebuy', response_model=ForceBuyResponse, tags=['trading'])
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@ -274,11 +274,11 @@ class Telegram(RPCHandler):
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f"*Buy Tag:* `{msg['buy_tag']}`\n"
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f"*Sell Reason:* `{msg['sell_reason']}`\n"
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f"*Duration:* `{msg['duration']} ({msg['duration_min']:.1f} min)`\n"
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f"*Amount:* `{msg['amount']:.8f}`\n")
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f"*Amount:* `{msg['amount']:.8f}`\n"
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f"*Open Rate:* `{msg['open_rate']:.8f}`\n")
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if msg['type'] == RPCMessageType.SELL:
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message += (f"*Open Rate:* `{msg['open_rate']:.8f}`\n"
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f"*Current Rate:* `{msg['current_rate']:.8f}`\n"
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message += (f"*Current Rate:* `{msg['current_rate']:.8f}`\n"
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f"*Close Rate:* `{msg['limit']:.8f}`")
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elif msg['type'] == RPCMessageType.SELL_FILL:
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@ -81,12 +81,11 @@ def _create_and_merge_informative_pair(strategy, dataframe: DataFrame, metadata:
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# Not specifying an asset will define informative dataframe for current pair.
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asset = metadata['pair']
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if '/' in asset:
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base, quote = asset.split('/')
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else:
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# When futures are supported this may need reevaluation.
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# base, quote = asset, ''
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raise OperationalException('Not implemented.')
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market = strategy.dp.market(asset)
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if market is None:
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raise OperationalException(f'Market {asset} is not available.')
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base = market['base']
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quote = market['quote']
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# Default format. This optimizes for the common case: informative pairs using same stake
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# currency. When quote currency matches stake currency, column name will omit base currency.
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@ -20,7 +20,7 @@ time-machine==2.4.0
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nbconvert==6.3.0
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# mypy types
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types-cachetools==4.2.4
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types-cachetools==4.2.5
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types-filelock==3.2.1
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types-requests==2.26.0
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types-tabulate==0.8.3
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@ -5,7 +5,7 @@
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scipy==1.7.2
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scikit-learn==1.0.1
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scikit-optimize==0.9.0
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filelock==3.3.2
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filelock==3.4.0
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joblib==1.1.0
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psutil==5.8.0
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progressbar2==3.55.0
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@ -1,5 +1,5 @@
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# Include all requirements to run the bot.
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-r requirements.txt
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plotly==5.3.1
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plotly==5.4.0
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@ -2,10 +2,10 @@ numpy==1.21.4
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pandas==1.3.4
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pandas-ta==0.3.14b
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ccxt==1.61.24
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ccxt==1.61.92
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# Pin cryptography for now due to rust build errors with piwheels
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cryptography==35.0.0
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aiohttp==3.7.4.post0
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cryptography==36.0.0
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aiohttp==3.8.1
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SQLAlchemy==1.4.27
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python-telegram-bot==13.8.1
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arrow==1.2.1
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@ -3329,7 +3329,7 @@ def test_validate_trading_mode_and_collateral(
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("bibox", "margin", {"has": {"fetchCurrencies": False}, "options": {"defaultType": "margin"}}),
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("bibox", "futures", {"has": {"fetchCurrencies": False}, "options": {"defaultType": "swap"}}),
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("bybit", "futures", {"options": {"defaultType": "linear"}}),
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("ftx", "futures", {"options": {"defaultType": "swap"}}),
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("ftx", "futures", {"options": {"defaultType": "future"}}),
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("gateio", "futures", {"options": {"defaultType": "swap"}}),
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("hitbtc", "futures", {"options": {"defaultType": "swap"}}),
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("kraken", "futures", {"options": {"defaultType": "swap"}}),
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@ -541,6 +541,8 @@ def test_api_show_config(botclient):
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assert 'ask_strategy' in response
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assert 'unfilledtimeout' in response
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assert 'version' in response
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assert 'api_version' in response
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assert 1.1 <= response['api_version'] <= 1.2
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def test_api_daily(botclient, mocker, ticker, fee, markets):
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@ -1847,6 +1847,7 @@ def test_send_msg_sell_fill_notification(default_conf, mocker) -> None:
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'*Sell Reason:* `stop_loss`\n'
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'*Duration:* `1 day, 2:30:00 (1590.0 min)`\n'
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'*Amount:* `1333.33333333`\n'
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'*Open Rate:* `0.00007500`\n'
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'*Close Rate:* `0.00003201`'
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)
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@ -19,7 +19,7 @@ class InformativeDecoratorTest(IStrategy):
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startup_candle_count: int = 20
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def informative_pairs(self):
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return [('BTC/USDT', '5m', '')]
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return [('NEO/USDT', '5m', '')]
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def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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dataframe['buy'] = 0
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@ -37,8 +37,8 @@ class InformativeDecoratorTest(IStrategy):
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return dataframe
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# Simple informative test.
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@informative('1h', 'BTC/{stake}')
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def populate_indicators_btc_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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@informative('1h', 'NEO/{stake}')
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def populate_indicators_neo_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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dataframe['rsi'] = 14
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return dataframe
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@ -49,7 +49,7 @@ class InformativeDecoratorTest(IStrategy):
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return dataframe
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# Formatting test.
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@informative('30m', 'BTC/{stake}', '{column}_{BASE}_{QUOTE}_{base}_{quote}_{asset}_{timeframe}')
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@informative('30m', 'NEO/{stake}', '{column}_{BASE}_{QUOTE}_{base}_{quote}_{asset}_{timeframe}')
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def populate_indicators_btc_1h_2(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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dataframe['rsi'] = 14
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return dataframe
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@ -67,7 +67,7 @@ class InformativeDecoratorTest(IStrategy):
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dataframe['rsi_less'] = dataframe['rsi'] < dataframe['rsi_1h']
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# Mixing manual informative pairs with decorators.
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informative = self.dp.get_pair_dataframe('BTC/USDT', '5m', '')
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informative = self.dp.get_pair_dataframe('NEO/USDT', '5m', '')
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informative['rsi'] = 14
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dataframe = merge_informative_pair(dataframe, informative, self.timeframe, '5m', ffill=True)
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@ -7,6 +7,7 @@ import pytest
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from freqtrade.data.dataprovider import DataProvider
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from freqtrade.strategy import (merge_informative_pair, stoploss_from_absolute, stoploss_from_open,
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timeframe_to_minutes)
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from tests.conftest import get_patched_exchange
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def generate_test_data(timeframe: str, size: int, start: str = '2020-07-05'):
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@ -156,9 +157,9 @@ def test_informative_decorator(mocker, default_conf):
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('LTC/USDT', '5m', ''): test_data_5m,
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('LTC/USDT', '30m', ''): test_data_30m,
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('LTC/USDT', '1h', ''): test_data_1h,
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('BTC/USDT', '30m', ''): test_data_30m,
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('BTC/USDT', '5m', ''): test_data_5m,
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('BTC/USDT', '1h', ''): test_data_1h,
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('NEO/USDT', '30m', ''): test_data_30m,
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('NEO/USDT', '5m', ''): test_data_5m,
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('NEO/USDT', '1h', ''): test_data_1h,
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('ETH/USDT', '1h', ''): test_data_1h,
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('ETH/USDT', '30m', ''): test_data_30m,
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('ETH/BTC', '1h', ''): test_data_1h,
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@ -166,15 +167,16 @@ def test_informative_decorator(mocker, default_conf):
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from .strats.informative_decorator_strategy import InformativeDecoratorTest
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default_conf['stake_currency'] = 'USDT'
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strategy = InformativeDecoratorTest(config=default_conf)
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strategy.dp = DataProvider({}, None, None)
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exchange = get_patched_exchange(mocker, default_conf)
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strategy.dp = DataProvider({}, exchange, None)
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mocker.patch.object(strategy.dp, 'current_whitelist', return_value=[
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'XRP/USDT', 'LTC/USDT', 'BTC/USDT'
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'XRP/USDT', 'LTC/USDT', 'NEO/USDT'
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])
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assert len(strategy._ft_informative) == 6 # Equal to number of decorators used
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informative_pairs = [('XRP/USDT', '1h', ''), ('LTC/USDT', '1h', ''), ('XRP/USDT', '30m', ''),
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('LTC/USDT', '30m', ''), ('BTC/USDT', '1h', ''), ('BTC/USDT', '30m', ''),
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('BTC/USDT', '5m', ''), ('ETH/BTC', '1h', ''), ('ETH/USDT', '30m', '')]
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('LTC/USDT', '30m', ''), ('NEO/USDT', '1h', ''), ('NEO/USDT', '30m', ''),
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('NEO/USDT', '5m', ''), ('ETH/BTC', '1h', ''), ('ETH/USDT', '30m', '')]
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for inf_pair in informative_pairs:
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assert inf_pair in strategy.gather_informative_pairs()
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@ -187,8 +189,8 @@ def test_informative_decorator(mocker, default_conf):
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{p: data[(p, strategy.timeframe, '')] for p in ('XRP/USDT', 'LTC/USDT')})
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expected_columns = [
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'rsi_1h', 'rsi_30m', # Stacked informative decorators
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'btc_usdt_rsi_1h', # BTC 1h informative
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'rsi_BTC_USDT_btc_usdt_BTC/USDT_30m', # Column formatting
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'neo_usdt_rsi_1h', # NEO 1h informative
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'rsi_NEO_USDT_neo_usdt_NEO/USDT_30m', # Column formatting
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'rsi_from_callable', # Custom column formatter
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'eth_btc_rsi_1h', # Quote currency not matching stake currency
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'rsi', 'rsi_less', # Non-informative columns
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