Bitcoin favicon, more strategies, default timeframe 5m

- Add an SVG Bitcoin favicon and link it in index.html.
- New indicators: macd() and roc().
- Five new strategies: macd_trend, bollinger_reversion, donchian_breakout,
  ema_cross, momentum (plus the existing sma_cross, rsi_reversion).
- Default TIMEFRAME is now 5m (config, .env.example, compose, workflow, UI).

backend/app/engine/strategies/base.py

@@ -5,7 +5,7 @@ from collections.abc import Sequence
 from dataclasses import dataclass
 from typing import Any, ClassVar, Literal, Protocol
 
-from app.engine.indicators import atr, ema, rolling_std, rsi, sma
+from app.engine.indicators import atr, ema, macd, roc, rolling_std, rsi, sma
 from app.models import PositionSide
 from app.schemas import Candle, ParamSpec, StrategyOut
 
@@ -106,6 +106,15 @@ class StrategyContext:
     def std(self, period: int = 20) -> float | None:
         return rolling_std(self.closes, period)[-1]
 
+    def macd(
+        self, fast: int = 12, slow: int = 26, signal: int = 9
+    ) -> tuple[float | None, float | None, float | None]:
+        macd_line, signal_line, histogram = macd(self.closes, fast, slow, signal)
+        return macd_line[-1], signal_line[-1], histogram[-1]
+
+    def roc(self, period: int = 10) -> float | None:
+        return roc(self.closes, period)[-1]
+
     # --- order intents ------------------------------------------------
     def enter_long(
         self,

backend/app/engine/strategies/bollinger_reversion.py

@@ -0,0 +1,63 @@
+from __future__ import annotations
+
+from typing import ClassVar
+
+from app.engine.strategies.base import Strategy, StrategyContext, register
+from app.models import PositionSide
+
+
+@register
+class BollingerReversion(Strategy):
+    """Buy the lower Bollinger band, exit at the middle band."""
+
+    key: ClassVar[str] = "bollinger_reversion"
+    name: ClassVar[str] = "Bollinger Reversion"
+    description: ClassVar[str] = (
+        "Enter long when the close falls below the lower Bollinger band and exit "
+        "when it returns to the middle band (SMA). Optional ATR stop."
+    )
+    default_params: ClassVar[dict] = {
+        "period": 20,
+        "num_std": 2.0,
+        "atr_period": 14,
+        "atr_stop_mult": 0.0,
+        "size": 1.0,
+    }
+    param_help: ClassVar[dict] = {
+        "period": "Bollinger lookback",
+        "num_std": "Band width in standard deviations",
+        "atr_period": "ATR lookback for the stop",
+        "atr_stop_mult": "Stop distance in ATRs (0 disables)",
+        "size": "Fraction of equity per trade",
+    }
+    param_bounds: ClassVar[dict] = {
+        "period": (5, 100),
+        "num_std": (0.5, 4.0),
+        "atr_stop_mult": (0.0, 10.0),
+        "size": (0.01, 1.0),
+    }
+
+    def on_candle(self, ctx: StrategyContext) -> None:
+        period = int(self.params["period"])
+        if len(ctx.closes) < period:
+            return
+        middle = ctx.sma(period)
+        deviation = ctx.std(period)
+        if middle is None or deviation is None:
+            return
+        lower = middle - float(self.params["num_std"]) * deviation
+
+        if ctx.is_flat and ctx.price < lower:
+            stop = None
+            mult = float(self.params["atr_stop_mult"])
+            if mult > 0:
+                atr_value = ctx.atr(int(self.params["atr_period"]))
+                if atr_value:
+                    stop = ctx.price - mult * atr_value
+            ctx.enter_long(
+                size=float(self.params["size"]),
+                stop_loss=stop,
+                reason="close below lower band",
+            )
+        elif ctx.side == PositionSide.LONG and ctx.price >= middle:
+            ctx.close(reason="close back at middle band")

backend/app/engine/strategies/donchian_breakout.py

@@ -0,0 +1,64 @@
+from __future__ import annotations
+
+from typing import ClassVar
+
+from app.engine.strategies.base import Strategy, StrategyContext, register
+from app.models import PositionSide
+
+
+@register
+class DonchianBreakout(Strategy):
+    """Breakout of the highest high, exit on the lowest low."""
+
+    key: ClassVar[str] = "donchian_breakout"
+    name: ClassVar[str] = "Donchian Breakout"
+    description: ClassVar[str] = (
+        "Open long when the close breaks above the highest high of the entry "
+        "lookback; exit on a close below the lowest low of the exit lookback. "
+        "Optional ATR stop."
+    )
+    default_params: ClassVar[dict] = {
+        "entry_period": 20,
+        "exit_period": 10,
+        "atr_period": 14,
+        "atr_stop_mult": 2.0,
+        "size": 1.0,
+    }
+    param_help: ClassVar[dict] = {
+        "entry_period": "Breakout lookback for entries",
+        "exit_period": "Lookback for the exit channel",
+        "atr_period": "ATR lookback for the stop",
+        "atr_stop_mult": "Stop distance in ATRs (0 disables)",
+        "size": "Fraction of equity per trade",
+    }
+    param_bounds: ClassVar[dict] = {
+        "entry_period": (2, 200),
+        "exit_period": (2, 200),
+        "atr_stop_mult": (0.0, 10.0),
+        "size": (0.01, 1.0),
+    }
+
+    def on_candle(self, ctx: StrategyContext) -> None:
+        entry_period = int(self.params["entry_period"])
+        exit_period = int(self.params["exit_period"])
+        if len(ctx.candles) < max(entry_period, exit_period) + 1:
+            return
+
+        # Exclude the current candle from the channel.
+        recent_high = max(c.high for c in ctx.candles[-entry_period - 1 : -1])
+        recent_low = min(c.low for c in ctx.candles[-exit_period - 1 : -1])
+
+        if ctx.is_flat and ctx.price > recent_high:
+            stop = None
+            mult = float(self.params["atr_stop_mult"])
+            if mult > 0:
+                atr_value = ctx.atr(int(self.params["atr_period"]))
+                if atr_value:
+                    stop = ctx.price - mult * atr_value
+            ctx.enter_long(
+                size=float(self.params["size"]),
+                stop_loss=stop,
+                reason=f"broke {entry_period}-bar high",
+            )
+        elif ctx.side == PositionSide.LONG and ctx.price < recent_low:
+            ctx.close(reason=f"broke {exit_period}-bar low")

backend/app/engine/strategies/ema_cross.py

@@ -0,0 +1,60 @@
+from __future__ import annotations
+
+from typing import ClassVar
+
+from app.engine.indicators import ema, sma
+from app.engine.strategies.base import Strategy, StrategyContext, register
+from app.models import PositionSide
+
+
+@register
+class EmaCross(Strategy):
+    """EMA crossover with an optional long-term trend filter."""
+
+    key: ClassVar[str] = "ema_cross"
+    name: ClassVar[str] = "EMA Crossover"
+    description: ClassVar[str] = (
+        "Open long when the fast EMA crosses above the slow EMA (and price is "
+        "above the trend filter, if enabled); exit on the opposite cross."
+    )
+    default_params: ClassVar[dict] = {
+        "fast": 9,
+        "slow": 21,
+        "trend_filter": 200,
+        "size": 1.0,
+    }
+    param_help: ClassVar[dict] = {
+        "fast": "Fast EMA period",
+        "slow": "Slow EMA period",
+        "trend_filter": "SMA trend filter period (0 disables)",
+        "size": "Fraction of equity per trade",
+    }
+    param_bounds: ClassVar[dict] = {"fast": (2, 100), "slow": (3, 300), "size": (0.01, 1.0)}
+
+    def on_candle(self, ctx: StrategyContext) -> None:
+        fast_period = int(self.params["fast"])
+        slow_period = int(self.params["slow"])
+        trend_period = int(self.params["trend_filter"])
+        needed = max(slow_period, trend_period) + 2
+        if len(ctx.closes) < needed:
+            return
+
+        fast = ema(ctx.closes, fast_period)
+        slow = ema(ctx.closes, slow_period)
+        f_prev, f_now = fast[-2], fast[-1]
+        s_prev, s_now = slow[-2], slow[-1]
+        if None in (f_prev, f_now, s_prev, s_now):
+            return
+
+        trend_ok = True
+        if trend_period > 0:
+            trend = sma(ctx.closes, trend_period)[-1]
+            trend_ok = trend is not None and ctx.price > trend
+
+        crossed_up = f_prev <= s_prev and f_now > s_now
+        crossed_down = f_prev >= s_prev and f_now < s_now
+
+        if ctx.is_flat and crossed_up and trend_ok:
+            ctx.enter_long(size=float(self.params["size"]), reason="EMA cross up")
+        elif ctx.side == PositionSide.LONG and crossed_down:
+            ctx.close(reason="EMA cross down")

backend/app/engine/strategies/macd_trend.py

@@ -0,0 +1,50 @@
+from __future__ import annotations
+
+from typing import ClassVar
+
+from app.engine.indicators import macd
+from app.engine.strategies.base import Strategy, StrategyContext, register
+from app.models import PositionSide
+
+
+@register
+class MacdTrend(Strategy):
+    """MACD crossover trend following, long-only."""
+
+    key: ClassVar[str] = "macd_trend"
+    name: ClassVar[str] = "MACD Trend"
+    description: ClassVar[str] = (
+        "Open long when the MACD line crosses above its signal line and close when "
+        "it crosses back below."
+    )
+    default_params: ClassVar[dict] = {"fast": 12, "slow": 26, "signal": 9, "size": 1.0}
+    param_help: ClassVar[dict] = {
+        "fast": "Fast EMA period",
+        "slow": "Slow EMA period",
+        "signal": "Signal EMA period",
+        "size": "Fraction of equity per trade",
+    }
+    param_bounds: ClassVar[dict] = {"fast": (2, 100), "slow": (3, 200), "signal": (2, 100)}
+
+    def on_candle(self, ctx: StrategyContext) -> None:
+        closes = ctx.closes
+        if len(closes) < int(self.params["slow"]) + int(self.params["signal"]) + 2:
+            return
+        macd_line, signal_line, _ = macd(
+            closes,
+            int(self.params["fast"]),
+            int(self.params["slow"]),
+            int(self.params["signal"]),
+        )
+        m_prev, m_now = macd_line[-2], macd_line[-1]
+        s_prev, s_now = signal_line[-2], signal_line[-1]
+        if None in (m_prev, m_now, s_prev, s_now):
+            return
+
+        crossed_up = m_prev <= s_prev and m_now > s_now
+        crossed_down = m_prev >= s_prev and m_now < s_now
+
+        if ctx.is_flat and crossed_up:
+            ctx.enter_long(size=float(self.params["size"]), reason="MACD crossed above signal")
+        elif ctx.side == PositionSide.LONG and crossed_down:
+            ctx.close(reason="MACD crossed below signal")

backend/app/engine/strategies/momentum.py

@@ -0,0 +1,58 @@
+from __future__ import annotations
+
+from typing import ClassVar
+
+from app.engine.strategies.base import Strategy, StrategyContext, register
+from app.models import PositionSide
+
+
+@register
+class Momentum(Strategy):
+    """Rate-of-change momentum, long-only."""
+
+    key: ClassVar[str] = "momentum"
+    name: ClassVar[str] = "Momentum (ROC)"
+    description: ClassVar[str] = (
+        "Open long when the rate of change over the lookback exceeds the entry "
+        "threshold; exit when momentum turns negative."
+    )
+    default_params: ClassVar[dict] = {
+        "period": 10,
+        "entry_threshold": 0.01,
+        "atr_period": 14,
+        "atr_stop_mult": 2.0,
+        "size": 1.0,
+    }
+    param_help: ClassVar[dict] = {
+        "period": "ROC lookback in bars",
+        "entry_threshold": "Minimum ROC to enter (0.01 = 1%)",
+        "atr_period": "ATR lookback for the stop",
+        "atr_stop_mult": "Stop distance in ATRs (0 disables)",
+        "size": "Fraction of equity per trade",
+    }
+    param_bounds: ClassVar[dict] = {
+        "period": (2, 200),
+        "entry_threshold": (0.0, 1.0),
+        "atr_stop_mult": (0.0, 10.0),
+        "size": (0.01, 1.0),
+    }
+
+    def on_candle(self, ctx: StrategyContext) -> None:
+        value = ctx.roc(int(self.params["period"]))
+        if value is None:
+            return
+
+        if ctx.is_flat and value > float(self.params["entry_threshold"]):
+            stop = None
+            mult = float(self.params["atr_stop_mult"])
+            if mult > 0:
+                atr_value = ctx.atr(int(self.params["atr_period"]))
+                if atr_value:
+                    stop = ctx.price - mult * atr_value
+            ctx.enter_long(
+                size=float(self.params["size"]),
+                stop_loss=stop,
+                reason=f"ROC {value:.2%} above threshold",
+            )
+        elif ctx.side == PositionSide.LONG and value < 0:
+            ctx.close(reason=f"ROC {value:.2%} turned negative")