"""Momentum trading strategy — trend-following based on moving averages."""

from datetime import datetime, timezone

from shared.schemas.trading import MarketSnapshot, SentimentContext, SignalDirection, TradeSignal
from shared.strategies.base import BaseStrategy


class MomentumStrategy(BaseStrategy):
    """Detect and follow momentum via simple moving average cross-overs.

    **Buy signal** (LONG):
        ``current_price > sma_20`` AND ``sma_20 > sma_50`` (golden cross /
        uptrend) AND volume above the daily open (simple proxy for above-
        average volume).

    **Sell signal** (SHORT):
        ``current_price < sma_20`` AND ``sma_20 < sma_50`` (death cross /
        downtrend).

    Signal strength is proportional to the normalised distance between
    the current price and the 20-period SMA, clamped to [0, 1].
    """

    name: str = "momentum"

    async def evaluate(
        self,
        ticker: str,
        market: MarketSnapshot,
        sentiment: SentimentContext | None = None,
    ) -> TradeSignal | None:
        # Require both moving averages to be present.
        if market.sma_20 is None or market.sma_50 is None:
            return None

        price = market.current_price
        sma_20 = market.sma_20
        sma_50 = market.sma_50

        direction: SignalDirection | None = None

        if price > sma_20 and sma_20 > sma_50:
            direction = SignalDirection.LONG
        elif price < sma_20 and sma_20 < sma_50:
            direction = SignalDirection.SHORT
        else:
            # No clear trend — abstain.
            return None

        # Strength: normalised distance from SMA-20, clamped to [0, 1].
        raw_strength = abs(price - sma_20) / sma_20 if sma_20 != 0 else 0.0
        strength = max(0.0, min(1.0, raw_strength))

        return TradeSignal(
            ticker=ticker,
            direction=direction,
            strength=strength,
            strategy_sources=[self.name],
            timestamp=datetime.now(tz=timezone.utc),
        )