matitos
d1f66c95c4
- New indicators: vwap (rolling/cumulative) and supertrend (line + direction), exposed on StrategyContext. - New strategies: supertrend (flip-based, optional shorts), vwap_reversion (mean reversion below a rolling VWAP) and ema_cross_short (short-side example, mirroring the long EMA cross). 10 strategies total. - Adds indicator and strategy tests; smoke-tested all three on live BTC/USDT 5m data.
240 lines
7.5 KiB
Python
240 lines
7.5 KiB
Python
from __future__ import annotations
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from collections.abc import Sequence
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from app.schemas import Candle
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Number = float | None
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def sma(values: Sequence[float], period: int) -> list[Number]:
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if period <= 0:
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raise ValueError("period must be positive")
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out: list[Number] = [None] * len(values)
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window_sum = 0.0
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for i, value in enumerate(values):
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window_sum += value
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if i >= period:
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window_sum -= values[i - period]
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if i >= period - 1:
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out[i] = window_sum / period
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return out
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def ema(values: Sequence[float], period: int) -> list[Number]:
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if period <= 0:
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raise ValueError("period must be positive")
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out: list[Number] = [None] * len(values)
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if len(values) < period:
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return out
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multiplier = 2 / (period + 1)
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seed = sum(values[:period]) / period
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out[period - 1] = seed
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prev = seed
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for i in range(period, len(values)):
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prev = (values[i] - prev) * multiplier + prev
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out[i] = prev
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return out
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def rsi(values: Sequence[float], period: int = 14) -> list[Number]:
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if period <= 0:
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raise ValueError("period must be positive")
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out: list[Number] = [None] * len(values)
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if len(values) <= period:
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return out
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gains = 0.0
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losses = 0.0
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for i in range(1, period + 1):
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change = values[i] - values[i - 1]
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gains += max(change, 0.0)
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losses += max(-change, 0.0)
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avg_gain = gains / period
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avg_loss = losses / period
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out[period] = _rsi_value(avg_gain, avg_loss)
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for i in range(period + 1, len(values)):
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change = values[i] - values[i - 1]
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gain = max(change, 0.0)
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loss = max(-change, 0.0)
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avg_gain = (avg_gain * (period - 1) + gain) / period
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avg_loss = (avg_loss * (period - 1) + loss) / period
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out[i] = _rsi_value(avg_gain, avg_loss)
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return out
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def _rsi_value(avg_gain: float, avg_loss: float) -> float:
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if avg_loss == 0:
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return 100.0
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rs = avg_gain / avg_loss
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return 100 - (100 / (1 + rs))
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def true_range(candles: Sequence[Candle]) -> list[float]:
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out: list[float] = []
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for i, candle in enumerate(candles):
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if i == 0:
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out.append(candle.high - candle.low)
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continue
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prev_close = candles[i - 1].close
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out.append(
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max(
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candle.high - candle.low,
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abs(candle.high - prev_close),
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abs(candle.low - prev_close),
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)
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)
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return out
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def atr(candles: Sequence[Candle], period: int = 14) -> list[Number]:
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if period <= 0:
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raise ValueError("period must be positive")
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tr = true_range(candles)
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out: list[Number] = [None] * len(tr)
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if len(tr) < period:
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return out
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prev = sum(tr[:period]) / period
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out[period - 1] = prev
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for i in range(period, len(tr)):
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prev = (prev * (period - 1) + tr[i]) / period
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out[i] = prev
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return out
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def rolling_std(values: Sequence[float], period: int) -> list[Number]:
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if period <= 0:
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raise ValueError("period must be positive")
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out: list[Number] = [None] * len(values)
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for i in range(period - 1, len(values)):
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window = values[i - period + 1 : i + 1]
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mean = sum(window) / period
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variance = sum((x - mean) ** 2 for x in window) / period
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out[i] = variance**0.5
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return out
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def macd(
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values: Sequence[float],
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fast: int = 12,
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slow: int = 26,
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signal: int = 9,
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) -> tuple[list[Number], list[Number], list[Number]]:
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"""Return (macd line, signal line, histogram), each aligned with ``values``."""
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ema_fast = ema(values, fast)
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ema_slow = ema(values, slow)
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macd_line: list[Number] = [
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(f - s) if f is not None and s is not None else None
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for f, s in zip(ema_fast, ema_slow, strict=True)
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]
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signal_line: list[Number] = [None] * len(values)
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start = next((i for i, value in enumerate(macd_line) if value is not None), None)
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if start is not None:
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valid = [value for value in macd_line[start:] if value is not None]
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for offset, value in enumerate(ema(valid, signal)):
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signal_line[start + offset] = value
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histogram: list[Number] = [
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(m - s) if m is not None and s is not None else None
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for m, s in zip(macd_line, signal_line, strict=True)
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]
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return macd_line, signal_line, histogram
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def roc(values: Sequence[float], period: int = 10) -> list[Number]:
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"""Rate of change over ``period`` bars, as a fraction (0.02 = +2%)."""
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if period <= 0:
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raise ValueError("period must be positive")
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out: list[Number] = [None] * len(values)
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for i in range(period, len(values)):
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previous = values[i - period]
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if previous:
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out[i] = (values[i] - previous) / previous
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return out
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def typical_price(candle: Candle) -> float:
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return (candle.high + candle.low + candle.close) / 3
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def vwap(candles: Sequence[Candle], period: int | None = None) -> list[Number]:
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"""Volume-weighted average price, rolling over ``period`` bars.
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With ``period=None`` it is cumulative from the first candle.
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"""
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out: list[Number] = [None] * len(candles)
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pv_sum = 0.0
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volume_sum = 0.0
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window: list[tuple[float, float]] = []
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for i, candle in enumerate(candles):
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price = typical_price(candle)
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volume = candle.volume
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pv_sum += price * volume
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volume_sum += volume
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if period is not None:
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window.append((price, volume))
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if len(window) > period:
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old_price, old_volume = window.pop(0)
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pv_sum -= old_price * old_volume
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volume_sum -= old_volume
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if len(window) < period:
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continue
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if volume_sum:
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out[i] = pv_sum / volume_sum
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return out
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def supertrend(
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candles: Sequence[Candle],
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period: int = 10,
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multiplier: float = 3.0,
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) -> tuple[list[float | None], list[bool | None]]:
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"""Supertrend line and trend direction (True = uptrend) per candle."""
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atr_series = atr(candles, period)
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line: list[float | None] = [None] * len(candles)
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up: list[bool | None] = [None] * len(candles)
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final_upper: float | None = None
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final_lower: float | None = None
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prev_close: float | None = None
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direction_up = True
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for i, candle in enumerate(candles):
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atr_value = atr_series[i]
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if atr_value is None:
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continue
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midpoint = (candle.high + candle.low) / 2
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basic_upper = midpoint + multiplier * atr_value
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basic_lower = midpoint - multiplier * atr_value
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if final_upper is None or final_lower is None:
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final_upper, final_lower = basic_upper, basic_lower
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direction_up = candle.close >= midpoint
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else:
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assert prev_close is not None
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final_upper = (
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basic_upper
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if basic_upper < final_upper or prev_close > final_upper
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else final_upper
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)
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final_lower = (
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basic_lower
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if basic_lower > final_lower or prev_close < final_lower
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else final_lower
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)
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if direction_up:
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direction_up = candle.close >= final_lower
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else:
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direction_up = candle.close > final_upper
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prev_close = candle.close
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line[i] = final_lower if direction_up else final_upper
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up[i] = direction_up
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return line, up
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def last(series: Sequence[Number]) -> Number:
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for value in reversed(series):
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if value is not None:
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return value
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return None
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