.env.example

@@ -16,7 +16,7 @@ DATABASE_URL=sqlite:///./data/trader.db
 MODE=paper
 EXCHANGE=binance
 SYMBOL=BTC/USDT
-TIMEFRAME=1m
+TIMEFRAME=5m
 # How often the engine polls for new candles, in seconds
 POLL_INTERVAL=5
 # Candles fetched per tick and kept for indicators

.gitea/workflows/deploy.yml

@@ -109,7 +109,7 @@ jobs:
       CRYPTO_MODE: ${{ vars.CRYPTO_MODE || 'paper' }}
       CRYPTO_EXCHANGE: ${{ vars.CRYPTO_EXCHANGE || 'binance' }}
       CRYPTO_SYMBOL: ${{ vars.CRYPTO_SYMBOL || 'BTC/USDT' }}
-      CRYPTO_TIMEFRAME: ${{ vars.CRYPTO_TIMEFRAME || '1m' }}
+      CRYPTO_TIMEFRAME: ${{ vars.CRYPTO_TIMEFRAME || '5m' }}
       CRYPTO_POLL_INTERVAL: ${{ vars.CRYPTO_POLL_INTERVAL || '5' }}
       CRYPTO_STARTING_BALANCE: ${{ vars.CRYPTO_STARTING_BALANCE || '10000' }}
       CRYPTO_CORS_ORIGINS: ${{ vars.CRYPTO_CORS_ORIGINS || format('https://crypto.{0}', secrets.BASE_DOMAIN || 'matitos.org') }}

README.md

@@ -101,7 +101,7 @@ All settings are environment variables (see `.env.example`):
 | `MODE` | `paper` | `paper` or `live` |
 | `EXCHANGE` | `binance` | Market data / execution venue |
 | `SYMBOL` | `BTC/USDT` | Default trading pair |
-| `TIMEFRAME` | `1m` | Candle interval |
+| `TIMEFRAME` | `5m` | Candle interval |
 | `POLL_INTERVAL` | `5` | Seconds between ticks |
 | `STARTING_BALANCE` | `10000` | Paper account size |
 | `FEE_BPS` / `SLIPPAGE_BPS` | `10` / `5` | Paper fill model |
@@ -159,8 +159,10 @@ from `https://api.telegram.org/bot<token>/getUpdates`.
 
 Drop a file in `backend/app/engine/strategies/` — it is auto-discovered and
 appears in the UI immediately. See **[AGENTS.md](AGENTS.md)** for the full
-template and the `StrategyContext` API. Two examples ship in the repo:
+template and the `StrategyContext` API.
-`sma_cross` and `rsi_reversion`.
+
+Bundled strategies: `sma_cross`, `ema_cross`, `macd_trend`,
+`bollinger_reversion`, `donchian_breakout`, `momentum`, `rsi_reversion`.
 
 ## API
 

backend/app/config.py

@@ -27,7 +27,7 @@ class Settings(BaseSettings):
     mode: str = "paper"
     exchange: str = "binance"
     symbol: str = "BTC/USDT"
-    timeframe: str = "1m"
+    timeframe: str = "5m"
     poll_interval: float = 5.0
     candle_limit: int = 200
 

backend/app/engine/indicators.py

@@ -113,6 +113,44 @@ def rolling_std(values: Sequence[float], period: int) -> list[Number]:
     return out
 
 
+def macd(
+    values: Sequence[float],
+    fast: int = 12,
+    slow: int = 26,
+    signal: int = 9,
+) -> tuple[list[Number], list[Number], list[Number]]:
+    """Return (macd line, signal line, histogram), each aligned with ``values``."""
+    ema_fast = ema(values, fast)
+    ema_slow = ema(values, slow)
+    macd_line: list[Number] = [
+        (f - s) if f is not None and s is not None else None
+        for f, s in zip(ema_fast, ema_slow, strict=True)
+    ]
+    signal_line: list[Number] = [None] * len(values)
+    start = next((i for i, value in enumerate(macd_line) if value is not None), None)
+    if start is not None:
+        valid = [value for value in macd_line[start:] if value is not None]
+        for offset, value in enumerate(ema(valid, signal)):
+            signal_line[start + offset] = value
+    histogram: list[Number] = [
+        (m - s) if m is not None and s is not None else None
+        for m, s in zip(macd_line, signal_line, strict=True)
+    ]
+    return macd_line, signal_line, histogram
+
+
+def roc(values: Sequence[float], period: int = 10) -> list[Number]:
+    """Rate of change over ``period`` bars, as a fraction (0.02 = +2%)."""
+    if period <= 0:
+        raise ValueError("period must be positive")
+    out: list[Number] = [None] * len(values)
+    for i in range(period, len(values)):
+        previous = values[i - period]
+        if previous:
+            out[i] = (values[i] - previous) / previous
+    return out
+
+
 def last(series: Sequence[Number]) -> Number:
     for value in reversed(series):
         if value is not None:

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")

backend/tests/test_indicators.py

@@ -2,7 +2,7 @@ from __future__ import annotations
 
 import pytest
 
-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.schemas import Candle
 
 
@@ -38,3 +38,25 @@ def test_atr_flat_market_is_zero() -> None:
 def test_rolling_std() -> None:
     result = rolling_std([1, 1, 1, 1], 2)
     assert result[-1] == pytest.approx(0.0)
+
+
+def test_roc() -> None:
+    values = [100.0, 110.0, 121.0, 100.0]
+    out = roc(values, 2)
+    assert out[0] is None and out[1] is None
+    assert out[2] == pytest.approx(0.21)
+    assert out[3] == pytest.approx(-0.09090909, rel=1e-4)
+
+
+def test_macd_shapes_and_crossover_sign() -> None:
+    rising = [float(i) for i in range(1, 80)]
+    macd_line, signal_line, histogram = macd(rising, 12, 26, 9)
+    assert len(macd_line) == len(rising)
+    assert macd_line[-1] is not None and signal_line[-1] is not None
+    # In a steady uptrend MACD is positive (but can be below its signal after lag).
+    assert macd_line[-1] > 0
+    assert histogram[-1] == pytest.approx(macd_line[-1] - signal_line[-1])
+
+    falling = [float(i) for i in range(80, 0, -1)]
+    macd_falling, _, _ = macd(falling, 12, 26, 9)
+    assert macd_falling[-1] < 0

backend/tests/test_new_strategies.py

@@ -0,0 +1,99 @@
+from __future__ import annotations
+
+from collections.abc import Sequence
+
+from app.engine.strategies.base import StrategyContext
+from app.schemas import Candle
+
+
+def make_candles(closes: Sequence[float]) -> list[Candle]:
+    return [Candle(ts=i, open=c, high=c, low=c, close=c, volume=1.0) for i, c in enumerate(closes)]
+
+
+def context(closes: Sequence[float], position=None) -> StrategyContext:
+    candles = make_candles(closes)
+    return StrategyContext(candles=candles, position=position, equity=1000.0, cash=1000.0)
+
+
+def test_all_strategies_discovered() -> None:
+    from app.engine.strategies import list_strategies
+
+    keys = {cls.key for cls in list_strategies()}
+    assert {
+        "sma_cross",
+        "rsi_reversion",
+        "macd_trend",
+        "bollinger_reversion",
+        "donchian_breakout",
+        "ema_cross",
+        "momentum",
+    } <= keys
+
+
+def test_every_strategy_has_spec_and_params() -> None:
+    from app.engine.strategies import list_strategies, strategy_spec
+
+    for cls in list_strategies():
+        spec = strategy_spec(cls)
+        assert spec.key and spec.name and spec.description
+        # Defaults must round-trip through the constructor and be constructible.
+        instance = cls({})
+        assert instance.key == cls.key
+        # A short synthetic series must never raise for a registered strategy.
+        ctx = context([100, 101, 100, 102, 99, 103, 98, 104, 97, 105])
+        instance.on_candle(ctx)
+
+
+def test_ema_cross_enters_on_cross_up() -> None:
+    from app.engine.strategies import get_strategy
+
+    strategy = get_strategy("ema_cross")({"fast": 2, "slow": 4, "trend_filter": 0, "size": 0.5})
+    # Fast EMA dips below the slow EMA, then crosses back above.
+    ctx = context([10, 10, 10, 10, 10, 10, 10, 10, 7, 9, 12])
+    strategy.on_candle(ctx)
+    intents = ctx.take_intents()
+    assert intents and intents[0].action == "enter_long"
+
+
+def test_momentum_enters_on_positive_roc() -> None:
+    from app.engine.strategies import get_strategy
+
+    strategy = get_strategy("momentum")({"period": 3, "entry_threshold": 0.01, "atr_stop_mult": 0})
+    ctx = context([100, 100, 100, 105])
+    strategy.on_candle(ctx)
+    intents = ctx.take_intents()
+    assert intents and intents[0].action == "enter_long"
+
+
+def test_macd_trend_no_intent_when_flat_short_history() -> None:
+    from app.engine.strategies import get_strategy
+
+    strategy = get_strategy("macd_trend")({})
+    ctx = context([100, 101, 102])
+    strategy.on_candle(ctx)
+    assert ctx.take_intents() == []
+
+
+def test_bollinger_enters_below_lower_band() -> None:
+    from app.engine.strategies import get_strategy
+
+    strategy = get_strategy("bollinger_reversion")(
+        {"period": 5, "num_std": 1.0, "atr_stop_mult": 0}
+    )
+    # Flat then a sharp drop below the lower band.
+    ctx = context([100, 100, 100, 100, 80])
+    strategy.on_candle(ctx)
+    intents = ctx.take_intents()
+    assert intents and intents[0].action == "enter_long"
+
+
+def test_donchian_enters_on_breakout() -> None:
+    from app.engine.strategies import get_strategy
+
+    strategy = get_strategy("donchian_breakout")(
+        {"entry_period": 5, "exit_period": 3, "atr_stop_mult": 0}
+    )
+    ctx = context([100, 100, 100, 100, 100, 110])
+    strategy.on_candle(ctx)
+    intents = ctx.take_intents()
+    assert intents and intents[0].action == "enter_long"

docker-compose.local.yml

@@ -12,7 +12,7 @@ services:
       - MODE=${MODE:-paper}
       - EXCHANGE=${EXCHANGE:-binance}
       - SYMBOL=${SYMBOL:-BTC/USDT}
-      - TIMEFRAME=${TIMEFRAME:-1m}
+      - TIMEFRAME=${TIMEFRAME:-5m}
       - POLL_INTERVAL=${POLL_INTERVAL:-5}
       - STARTING_BALANCE=${STARTING_BALANCE:-10000}
       - FEE_BPS=${FEE_BPS:-10}

docker-compose.yml

@@ -22,7 +22,7 @@ services:
       - MODE=${CRYPTO_MODE:-paper}
       - EXCHANGE=${CRYPTO_EXCHANGE:-binance}
       - SYMBOL=${CRYPTO_SYMBOL:-BTC/USDT}
-      - TIMEFRAME=${CRYPTO_TIMEFRAME:-1m}
+      - TIMEFRAME=${CRYPTO_TIMEFRAME:-5m}
       - POLL_INTERVAL=${CRYPTO_POLL_INTERVAL:-5}
       - STARTING_BALANCE=${CRYPTO_STARTING_BALANCE:-10000}
       - FEE_BPS=${CRYPTO_FEE_BPS:-10}

frontend/index.html

@@ -3,6 +3,9 @@
   <head>
     <meta charset="UTF-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+    <link rel="icon" type="image/svg+xml" href="/favicon.svg" />
+    <link rel="apple-touch-icon" href="/favicon.svg" />
+    <meta name="theme-color" content="#F7931A" />
     <title>Crypto Trader</title>
   </head>
   <body class="bg-surface text-slate-100">

frontend/public/favicon.svg

@@ -0,0 +1,9 @@
+<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 32 32" width="32" height="32">
+  <circle cx="16" cy="16" r="16" fill="#F7931A"/>
+  <text x="16" y="23.5" text-anchor="middle" font-family="Arial, Helvetica, sans-serif"
+        font-size="21" font-weight="bold" fill="#ffffff">B</text>
+  <rect x="13.9" y="4.2" width="2.2" height="4.6" rx="1.1" fill="#ffffff"/>
+  <rect x="17.6" y="4.2" width="2.2" height="4.6" rx="1.1" fill="#ffffff"/>
+  <rect x="13.9" y="23.2" width="2.2" height="4.6" rx="1.1" fill="#ffffff"/>
+  <rect x="17.6" y="23.2" width="2.2" height="4.6" rx="1.1" fill="#ffffff"/>
+</svg>

frontend/src/components/StrategyForm.vue

@@ -8,7 +8,7 @@ const props = defineProps({
   submitLabel: { type: String, default: 'Run' },
   submitClass: { type: String, default: 'btn-primary' },
   symbol: { type: String, default: 'BTC/USDT' },
-  timeframe: { type: String, default: '1m' },
+  timeframe: { type: String, default: '5m' },
   presets: { type: Array, default: () => [] },
 })
 const emit = defineEmits(['submit', 'save-preset', 'delete-preset', 'load-preset'])