Merge pull request #3975 from freqtrade/volatility_filter

RangeStabilityFilter filter - filter for pairs without much movement
This commit is contained in:
Matthias
2020-11-25 19:17:06 +01:00
committed by GitHub
8 changed files with 261 additions and 9 deletions

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@@ -25,7 +25,7 @@ HYPEROPT_LOSS_BUILTIN = ['ShortTradeDurHyperOptLoss', 'OnlyProfitHyperOptLoss',
'SortinoHyperOptLoss', 'SortinoHyperOptLossDaily']
AVAILABLE_PAIRLISTS = ['StaticPairList', 'VolumePairList',
'AgeFilter', 'PrecisionFilter', 'PriceFilter',
'ShuffleFilter', 'SpreadFilter']
'RangeStabilityFilter', 'ShuffleFilter', 'SpreadFilter']
AVAILABLE_DATAHANDLERS = ['json', 'jsongz', 'hdf5']
DRY_RUN_WALLET = 1000
DATETIME_PRINT_FORMAT = '%Y-%m-%d %H:%M:%S'

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@@ -679,12 +679,25 @@ class Exchange:
:param pair: Pair to download
:param timeframe: Timeframe to get data for
:param since_ms: Timestamp in milliseconds to get history from
:returns List with candle (OHLCV) data
:return: List with candle (OHLCV) data
"""
return asyncio.get_event_loop().run_until_complete(
self._async_get_historic_ohlcv(pair=pair, timeframe=timeframe,
since_ms=since_ms))
def get_historic_ohlcv_as_df(self, pair: str, timeframe: str,
since_ms: int) -> DataFrame:
"""
Minimal wrapper around get_historic_ohlcv - converting the result into a dataframe
:param pair: Pair to download
:param timeframe: Timeframe to get data for
:param since_ms: Timestamp in milliseconds to get history from
:return: OHLCV DataFrame
"""
ticks = self.get_historic_ohlcv(pair, timeframe, since_ms=since_ms)
return ohlcv_to_dataframe(ticks, timeframe, pair=pair, fill_missing=True,
drop_incomplete=self._ohlcv_partial_candle)
async def _async_get_historic_ohlcv(self, pair: str,
timeframe: str,
since_ms: int) -> List:

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@@ -49,7 +49,7 @@ class AgeFilter(IPairList):
return (f"{self.name} - Filtering pairs with age less than "
f"{self._min_days_listed} {plural(self._min_days_listed, 'day')}.")
def _validate_pair(self, ticker: dict) -> bool:
def _validate_pair(self, ticker: Dict) -> bool:
"""
Validate age for the ticker
:param ticker: ticker dict as returned from ccxt.load_markets()

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@@ -0,0 +1,89 @@
"""
Rate of change pairlist filter
"""
import logging
from typing import Any, Dict
import arrow
from cachetools.ttl import TTLCache
from freqtrade.exceptions import OperationalException
from freqtrade.misc import plural
from freqtrade.pairlist.IPairList import IPairList
logger = logging.getLogger(__name__)
class RangeStabilityFilter(IPairList):
def __init__(self, exchange, pairlistmanager,
config: Dict[str, Any], pairlistconfig: Dict[str, Any],
pairlist_pos: int) -> None:
super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
self._days = pairlistconfig.get('lookback_days', 10)
self._min_rate_of_change = pairlistconfig.get('min_rate_of_change', 0.01)
self._refresh_period = pairlistconfig.get('refresh_period', 1440)
self._pair_cache: TTLCache = TTLCache(maxsize=100, ttl=self._refresh_period)
if self._days < 1:
raise OperationalException("RangeStabilityFilter requires lookback_days to be >= 1")
if self._days > exchange.ohlcv_candle_limit:
raise OperationalException("RangeStabilityFilter requires lookback_days to not "
"exceed exchange max request size "
f"({exchange.ohlcv_candle_limit})")
@property
def needstickers(self) -> bool:
"""
Boolean property defining if tickers are necessary.
If no Pairlist requires tickers, an empty List is passed
as tickers argument to filter_pairlist
"""
return True
def short_desc(self) -> str:
"""
Short whitelist method description - used for startup-messages
"""
return (f"{self.name} - Filtering pairs with rate of change below "
f"{self._min_rate_of_change} over the last {plural(self._days, 'day')}.")
def _validate_pair(self, ticker: Dict) -> bool:
"""
Validate trading range
:param ticker: ticker dict as returned from ccxt.load_markets()
:return: True if the pair can stay, False if it should be removed
"""
pair = ticker['symbol']
# Check symbol in cache
if pair in self._pair_cache:
return self._pair_cache[pair]
since_ms = int(arrow.utcnow()
.floor('day')
.shift(days=-self._days)
.float_timestamp) * 1000
daily_candles = self._exchange.get_historic_ohlcv_as_df(pair=pair,
timeframe='1d',
since_ms=since_ms)
result = False
if daily_candles is not None and not daily_candles.empty:
highest_high = daily_candles['high'].max()
lowest_low = daily_candles['low'].min()
pct_change = ((highest_high - lowest_low) / lowest_low) if lowest_low > 0 else 0
if pct_change >= self._min_rate_of_change:
result = True
else:
self.log_on_refresh(logger.info,
f"Removed {pair} from whitelist, "
f"because rate of change over {plural(self._days, 'day')} is "
f"{pct_change:.3f}, which is below the "
f"threshold of {self._min_rate_of_change}.")
result = False
self._pair_cache[pair] = result
return result