local strategy

AGENTS.md

@@ -41,10 +41,13 @@ src/
 │   ├── custom_timeframe_generator.py  # 37m, 148m, 1d aggregation
 │   ├── indicator_engine.py      # SMA/EMA computation & storage
 │   ├── brain.py                 # Strategy evaluation & decision logging
-│   └── backtester.py            # Historical replay driver
-└── api/
-    ├── server.py                # FastAPI app, endpoints for data/backtests
-    └── dashboard/static/index.html  # Real-time web dashboard
+│   └── backtester.py            # Historical replay driver (server-side)
+├── api/
+│   ├── server.py                # FastAPI app, endpoints for data/backtests
+│   └── dashboard/static/index.html  # Real-time web dashboard with client-side simulation
+└── strategies/
+    ├── base.py                  # Base strategy interface
+    └── ma_strategy.py           # Configurable MA strategy (period: 5-500)
 config/data_config.yaml          # Operational config & indicator settings
 docker/                          # Docker orchestration & init-scripts
 scripts/                         # Deploy, backup, & utility scripts
@@ -52,17 +55,30 @@ scripts/                         # Deploy, backup, & utility scripts
 
 ## Architecture & Data Flow
 
+### Live Trading (Server-Side)
 ```
 Live: WS -> Buffer -> DB -> CustomTF -> IndicatorEngine -> Brain -> Decisions
                                               │             │
 Backtest: DB (History) -> Backtester ─────────┴─────────────┘
 ```
 
+### Client-Side Simulation (Dashboard)
+```
+User Input -> API /candles/bulk -> Browser (ClientStrategyEngine) -> Chart Visualization
+                    ↓                                              ↓
+            Historical Data                                Buy/Sell Markers
+```
+
 - **Stateless Logic**: `IndicatorEngine` and `Brain` are driver-agnostic. They read from DB
   and write to DB, unaware if the trigger is live WS or backtest replay.
 - **Consistency**: Indicators are computed exactly the same way for live and backtest.
 - **Visualization**: Dashboard queries `indicators` and `decisions` tables directly.
   Decisions contain a JSON snapshot of indicators at the moment of decision.
+- **Client-Side Simulation**: All strategy simulations run in the browser using `ClientStrategyEngine`.
+  The server only provides historical candle data via API. This minimizes server load and allows
+  interactive backtesting with configurable parameters (MA period 5-500).
+- **Full Historical Display**: After simulation, the chart displays the complete date range used,
+  not just the default 1000 recent candles.
 
 ## Key Dataclasses
 
@@ -109,6 +125,32 @@ class Decision:                  # Brain output
 - **Logging**: Use `logger = logging.getLogger(__name__)`.
 - **Config**: Load from `config/data_config.yaml` or env vars.
 
+## Strategy Configuration
+
+The system uses a single configurable Moving Average strategy (`ma_strategy`) with a dynamic period (5-500).
+
+### Strategy Files
+- `src/strategies/base.py` - Base strategy interface with `SignalType` enum
+- `src/strategies/ma_strategy.py` - Configurable MA strategy implementation
+
+### Client-Side vs Server-Side
+
+| Feature | Client-Side (Dashboard) | Server-Side (CLI/API) |
+|---------|------------------------|----------------------|
+| **Purpose** | Interactive simulation | Production backtesting |
+| **Strategy** | Single configurable MA (period 5-500) | Configurable via strategy registry |
+| **Indicators** | Calculated in browser (SMA, RSI, etc.) | Pre-computed in database |
+| **Data Flow** | API → Browser → Chart | DB → Backtester → DB |
+| **Performance** | Fast, interactive | Thorough, historical |
+
+### Simulation Workflow
+1. User selects date range and MA period (5-500) in dashboard sidebar
+2. Browser fetches full historical data from `/api/v1/candles/bulk`
+3. `ClientStrategyEngine` calculates indicators client-side using JavaScript
+4. Simulation runs on complete dataset, generating buy/sell signals
+5. Chart updates to show full historical range with trade markers
+6. Results displayed in sidebar (win rate, P&L, profit factor)
+
 ## Common Tasks
 
 ### Add New Indicator

src/api/dashboard/static/index.html

@@ -1483,54 +1483,37 @@
                     return tfCandles[pointers[tf]].close;
                 };
                 
-                // Debug logging for first evaluation
-                if (index === 1) {
-                    console.log('First candle time:', candles[index].time, 'Date:', new Date(candles[index].time * 1000));
-                    console.log('MA44 value:', getVal('ma44', primaryTF));
-                }
+                // Simple logic for MA Trend strategy
+                if (config.id === 'ma_trend') {
+                    const period = config.params?.period || 44;
                     
-                // Simple logic for MVP strategies
-                if (config.id === 'ma44_strategy') {
-                    const ma44 = getVal('ma44', primaryTF);
+                    // Debug logging for first evaluation
+                    if (index === 1) {
+                        console.log('First candle time:', candles[index].time, 'Date:', new Date(candles[index].time * 1000));
+                        console.log(`MA${period} value:`, getVal(`ma${period}`, primaryTF));
+                    }
+                    const maValue = getVal(`ma${period}`, primaryTF);
                     const price = candles[index].close;
                     
-                    // Optional: Multi-TF trend filter
+                    // Optional: Multi-TF trend filter (must align for both entry and exit)
                     const secondaryTF = config.timeframes?.secondary?.[0];
-                    let trendOk = true;
+                    let secondaryBullish = true;
+                    let secondaryBearish = true;
                     if (secondaryTF) {
                         const secondaryPrice = getPrice(secondaryTF);
-                        const secondaryMA = getVal(`ma44_${secondaryTF}`, secondaryTF);
-                        trendOk = secondaryPrice > secondaryMA;
+                        const secondaryMA = getVal(`ma${period}_${secondaryTF}`, secondaryTF);
+                        if (secondaryPrice !== null && secondaryMA !== null) {
+                            secondaryBullish = secondaryPrice > secondaryMA;
+                            secondaryBearish = secondaryPrice < secondaryMA;
+                        }
                         if (index === 1) {
-                            console.log(`Trend check: ${secondaryTF} price=${secondaryPrice}, MA=${secondaryMA}, trendOk=${trendOk}`);
+                            console.log(`Trend check: ${secondaryTF} price=${secondaryPrice}, MA=${secondaryMA}, bullish=${secondaryBullish}, bearish=${secondaryBearish}`);
                         }
                     }
 
-                    if (ma44) {
-                        if (price > ma44 && trendOk) return 'BUY';
-                        if (price < ma44) return 'SELL';
-                    }
-                }
-                
-                if (config.id === 'ma125_strategy') {
-                    const ma125 = getVal('ma125', primaryTF);
-                    const price = candles[index].close;
-                    
-                    // Optional: Multi-TF trend filter
-                    const secondaryTF = config.timeframes?.secondary?.[0];
-                    let trendOk = true;
-                    if (secondaryTF) {
-                        const secondaryPrice = getPrice(secondaryTF);
-                        const secondaryMA = getVal(`ma125_${secondaryTF}`, secondaryTF);
-                        trendOk = secondaryPrice > secondaryMA;
-                        if (index === 1) {
-                            console.log(`Trend check: ${secondaryTF} price=${secondaryPrice}, MA=${secondaryMA}, trendOk=${trendOk}`);
-                        }
-                    }
-                    
-                    if (ma125) {
-                        if (price > ma125 && trendOk) return 'BUY';
-                        if (price < ma125) return 'SELL';
+                    if (maValue) {
+                        if (price > maValue && secondaryBullish) return 'BUY';
+                        if (price < maValue && secondaryBearish) return 'SELL';
                     }
                 }
 
@@ -2131,6 +2114,9 @@
                 this.loadInitialData();
                 this.loadTA();
                 
+                // Clear simulation results when changing timeframe
+                clearSimulationResults();
+                
                 // Update simulation panel timeframe display
                 updateTimeframeDisplay();
             }
@@ -2313,6 +2299,36 @@
             }
         }
         
+        function clearSimulationResults() {
+            // Clear markers from chart
+            clearSimulationMarkers();
+            
+            // Clear simulation data
+            window.lastSimulationResults = null;
+            
+            // Hide results section
+            const resultsSection = document.getElementById('resultsSection');
+            if (resultsSection) {
+                resultsSection.style.display = 'none';
+            }
+            
+            // Reset results display
+            const simTrades = document.getElementById('simTrades');
+            const simWinRate = document.getElementById('simWinRate');
+            const simPnL = document.getElementById('simPnL');
+            const simProfitFactor = document.getElementById('simProfitFactor');
+            const equitySparkline = document.getElementById('equitySparkline');
+            
+            if (simTrades) simTrades.textContent = '0';
+            if (simWinRate) simWinRate.textContent = '0%';
+            if (simPnL) {
+                simPnL.textContent = '$0.00';
+                simPnL.style.color = '';
+            }
+            if (simProfitFactor) simProfitFactor.textContent = '0';
+            if (equitySparkline) equitySparkline.innerHTML = '';
+        }
+
         // Set default start date (7 days ago)
         function setDefaultStartDate() {
             const startDateInput = document.getElementById('simStartDate');
@@ -2398,11 +2414,8 @@
         
         // Strategy parameter definitions
         const StrategyParams = {
-            ma44_strategy: [
-                { name: 'maPeriod', label: 'MA Period', type: 'number', default: 44, min: 5, max: 500 }
-            ],
-            ma125_strategy: [
-                { name: 'maPeriod', label: 'MA Period', type: 'number', default: 125, min: 5, max: 500 }
+            ma_trend: [
+                { name: 'period', label: 'MA Period', type: 'number', default: 44, min: 5, max: 500 }
             ]
         };
         
@@ -2462,7 +2475,8 @@
                            value="${param.default}"
                            ${param.min !== undefined ? `min="${param.min}"` : ''}
                            ${param.max !== undefined ? `max="${param.max}"` : ''}
-                           ${param.step !== undefined ? `step="${param.step}"` : ''}>
+                           ${param.step !== undefined ? `step="${param.step}"` : ''}
+                           >
                 </div>
             `).join('');
         }
@@ -2571,6 +2585,7 @@
                 // Build strategy config
                 const engineConfig = {
                     id: strategyConfig.id,
+                    params: strategyConfig.params,
                     timeframes: { primary: interval, secondary: secondaryTF ? [secondaryTF] : [] },
                     indicators: []
                 };
@@ -2581,37 +2596,21 @@
                 console.log('  Available candles:', Object.keys(candlesMap));
                 
                 // Add indicator based on strategy
-                if (strategyConfig.id === 'ma44_strategy') {
+                if (strategyConfig.id === 'ma_trend') {
+                    const period = strategyConfig.params?.period || 44;
                     // Primary timeframe indicator
                     engineConfig.indicators.push({
-                        name: 'ma44',
+                        name: `ma${period}`,
                         type: 'sma',
-                        params: { period: strategyConfig.params.maPeriod || 44 },
+                        params: { period: period },
                         timeframe: interval
                     });
                     // Confirmation timeframe indicator (for trend filter)
                     if (secondaryTF) {
                         engineConfig.indicators.push({
-                            name: `ma44_${secondaryTF}`,
+                            name: `ma${period}_${secondaryTF}`,
                             type: 'sma',
-                            params: { period: strategyConfig.params.maPeriod || 44 },
-                            timeframe: secondaryTF
-                        });
-                    }
-                } else if (strategyConfig.id === 'ma125_strategy') {
-                    // Primary timeframe indicator
-                    engineConfig.indicators.push({
-                        name: 'ma125',
-                        type: 'sma',
-                        params: { period: strategyConfig.params.maPeriod || 125 },
-                        timeframe: interval
-                    });
-                    // Confirmation timeframe indicator (for trend filter)
-                    if (secondaryTF) {
-                        engineConfig.indicators.push({
-                            name: `ma125_${secondaryTF}`,
-                            type: 'sma',
-                            params: { period: strategyConfig.params.maPeriod || 125 },
+                            params: { period: period },
                             timeframe: secondaryTF
                         });
                     }
@@ -2652,6 +2651,23 @@
                 // Show results section
                 document.getElementById('resultsSection').style.display = 'block';
                 
+                // Update chart with full historical data from simulation
+                if (window.dashboard && candlesMap[interval]) {
+                    const chartData = candlesMap[interval].map(c => ({
+                        time: c.time,
+                        open: c.open,
+                        high: c.high,
+                        low: c.low,
+                        close: c.close
+                    }));
+                    window.dashboard.candleSeries.setData(chartData);
+                    window.dashboard.allData.set(interval, chartData);
+                    console.log(`Chart updated with ${chartData.length} candles from simulation range`);
+                }
+                
+                // Show simulation markers on chart
+                showSimulationMarkers();
+                
             } catch (error) {
                 console.error('Simulation error:', error);
                 alert('Simulation error: ' + error.message);
@@ -3112,7 +3128,7 @@
                 const controller = new AbortController();
                 const timeoutId = setTimeout(() => controller.abort(), 5000);
                 
-                const response = await fetch('/api/v1/strategies', {
+                const response = await fetch('/api/v1/strategies?_=' + Date.now(), {
                     signal: controller.signal
                 });
                 clearTimeout(timeoutId);

src/api/server.py

@@ -10,7 +10,7 @@ from datetime import datetime, timedelta, timezone
 from typing import Optional, List
 from contextlib import asynccontextmanager
 
-from fastapi import FastAPI, HTTPException, Query, BackgroundTasks
+from fastapi import FastAPI, HTTPException, Query, BackgroundTasks, Response
 from fastapi.staticfiles import StaticFiles
 from fastapi.responses import StreamingResponse
 from fastapi.middleware.cors import CORSMiddleware
@@ -100,12 +100,16 @@ async def root():
 
 
 @app.get("/api/v1/strategies")
-async def list_strategies():
+async def list_strategies(response: Response):
     """List all available trading strategies with metadata"""
+    # Prevent caching
+    response.headers["Cache-Control"] = "no-cache, no-store, must-revalidate"
+    response.headers["Pragma"] = "no-cache"
+    response.headers["Expires"] = "0"
+    
     # Strategy registry from brain.py
     strategy_registry = {
-        "ma44_strategy": "src.strategies.ma44_strategy.MA44Strategy",
-        "ma125_strategy": "src.strategies.ma125_strategy.MA125Strategy",
+        "ma_trend": "src.strategies.ma_strategy.MAStrategy",
     }
     
     strategies = []

src/data_collector/backfill.py

@@ -28,7 +28,9 @@ class HyperliquidBackfill:
     
     API_URL = "https://api.hyperliquid.xyz/info"
     MAX_CANDLES_PER_REQUEST = 500
-    MAX_TOTAL_CANDLES = 5000
+    # Hyperliquid API might limit total history, but we'll set a high limit 
+    # and stop when no more data is returned
+    MAX_TOTAL_CANDLES = 500000
     
     # Standard timeframes supported by Hyperliquid
     INTERVALS = [

src/strategies/ma125_strategy.py

@@ -1,63 +0,0 @@
-"""
-MA125 Strategy
-Simple trend following strategy.
-- Long when Price > MA125
-- Short when Price < MA125
-"""
-
-from typing import Dict, Any, List, Optional
-from .base import BaseStrategy, StrategySignal, SignalType
-
-class MA125Strategy(BaseStrategy):
-    @property
-    def name(self) -> str:
-        return "ma125_strategy"
-
-    @property
-    def required_indicators(self) -> List[str]:
-        return ["ma125"]
-
-    @property
-    def display_name(self) -> str:
-        return "MA125 Strategy"
-
-    @property
-    def description(self) -> str:
-        return "Long-term trend following using 125-period moving average. Better for identifying major trends."
-
-    def analyze(
-        self, 
-        candle: Dict[str, Any], 
-        indicators: Dict[str, float], 
-        current_position: Optional[Dict[str, Any]] = None
-    ) -> StrategySignal:
-        
-        price = candle['close']
-        ma125 = indicators.get('ma125')
-        
-        if ma125 is None:
-            return StrategySignal(SignalType.HOLD, 0.0, "MA125 not available")
-            
-        # Current position state
-        is_long = current_position and current_position.get('type') == 'long'
-        is_short = current_position and current_position.get('type') == 'short'
-        
-        # Logic: Price > MA125 -> Bullish
-        if price > ma125:
-            if is_long:
-                return StrategySignal(SignalType.HOLD, 1.0, f"Price {price:.2f} > MA125 {ma125:.2f}. Stay Long.")
-            elif is_short:
-                return StrategySignal(SignalType.CLOSE_SHORT, 1.0, f"Price {price:.2f} crossed above MA125 {ma125:.2f}. Close Short.")
-            else:
-                return StrategySignal(SignalType.OPEN_LONG, 1.0, f"Price {price:.2f} > MA125 {ma125:.2f}. Open Long.")
-                
-        # Logic: Price < MA125 -> Bearish
-        elif price < ma125:
-            if is_short:
-                return StrategySignal(SignalType.HOLD, 1.0, f"Price {price:.2f} < MA125 {ma125:.2f}. Stay Short.")
-            elif is_long:
-                return StrategySignal(SignalType.CLOSE_LONG, 1.0, f"Price {price:.2f} crossed below MA125 {ma125:.2f}. Close Long.")
-            else:
-                return StrategySignal(SignalType.OPEN_SHORT, 1.0, f"Price {price:.2f} < MA125 {ma125:.2f}. Open Short.")
-                
-        return StrategySignal(SignalType.HOLD, 0.0, "Price == MA125")

src/strategies/ma44_strategy.py

@@ -1,63 +0,0 @@
-"""
-MA44 Strategy
-Simple trend following strategy.
-- Long when Price > MA44
-- Short when Price < MA44
-"""
-
-from typing import Dict, Any, List, Optional
-from .base import BaseStrategy, StrategySignal, SignalType
-
-class MA44Strategy(BaseStrategy):
-    @property
-    def name(self) -> str:
-        return "ma44_strategy"
-
-    @property
-    def required_indicators(self) -> List[str]:
-        return ["ma44"]
-
-    @property
-    def display_name(self) -> str:
-        return "MA44 Strategy"
-
-    @property
-    def description(self) -> str:
-        return "Buy when price crosses above MA44, sell when below. Good for trending markets."
-
-    def analyze(
-        self, 
-        candle: Dict[str, Any], 
-        indicators: Dict[str, float], 
-        current_position: Optional[Dict[str, Any]] = None
-    ) -> StrategySignal:
-        
-        price = candle['close']
-        ma44 = indicators.get('ma44')
-        
-        if ma44 is None:
-            return StrategySignal(SignalType.HOLD, 0.0, "MA44 not available")
-            
-        # Current position state
-        is_long = current_position and current_position.get('type') == 'long'
-        is_short = current_position and current_position.get('type') == 'short'
-        
-        # Logic: Price > MA44 -> Bullish
-        if price > ma44:
-            if is_long:
-                return StrategySignal(SignalType.HOLD, 1.0, f"Price {price:.2f} > MA44 {ma44:.2f}. Stay Long.")
-            elif is_short:
-                return StrategySignal(SignalType.CLOSE_SHORT, 1.0, f"Price {price:.2f} crossed above MA44 {ma44:.2f}. Close Short.")
-            else:
-                return StrategySignal(SignalType.OPEN_LONG, 1.0, f"Price {price:.2f} > MA44 {ma44:.2f}. Open Long.")
-                
-        # Logic: Price < MA44 -> Bearish
-        elif price < ma44:
-            if is_short:
-                return StrategySignal(SignalType.HOLD, 1.0, f"Price {price:.2f} < MA44 {ma44:.2f}. Stay Short.")
-            elif is_long:
-                return StrategySignal(SignalType.CLOSE_LONG, 1.0, f"Price {price:.2f} crossed below MA44 {ma44:.2f}. Close Long.")
-            else:
-                return StrategySignal(SignalType.OPEN_SHORT, 1.0, f"Price {price:.2f} < MA44 {ma44:.2f}. Open Short.")
-                
-        return StrategySignal(SignalType.HOLD, 0.0, "Price == MA44")

src/strategies/ma_strategy.py

@@ -0,0 +1,77 @@
+"""
+Moving Average Strategy
+Configurable trend following strategy.
+- Long when Price > MA(period)
+- Short when Price < MA(period)
+"""
+
+from typing import Dict, Any, List, Optional
+from .base import BaseStrategy, StrategySignal, SignalType
+
+class MAStrategy(BaseStrategy):
+    """
+    Configurable Moving Average Strategy.
+    
+    Config:
+        - period: int - MA period (default: 44)
+    """
+    
+    DEFAULT_PERIOD = 44
+    
+    @property
+    def name(self) -> str:
+        return "ma_trend"
+
+    @property
+    def required_indicators(self) -> List[str]:
+        # Dynamic based on config
+        period = self.config.get('period', self.DEFAULT_PERIOD)
+        return [f"ma{period}"]
+
+    @property
+    def display_name(self) -> str:
+        return "MA Strategy"
+
+    @property
+    def description(self) -> str:
+        return "Configurable Moving Average strategy. Parameters: period (5-500, default: 44). Goes long when price > MA(period), short when price < MA(period). Optional multi-timeframe trend filter available."
+
+    def analyze(
+        self, 
+        candle: Dict[str, Any], 
+        indicators: Dict[str, float], 
+        current_position: Optional[Dict[str, Any]] = None
+    ) -> StrategySignal:
+        
+        period = self.config.get('period', self.DEFAULT_PERIOD)
+        ma_key = f"ma{period}"
+        
+        price = candle['close']
+        ma_value = indicators.get(ma_key)
+        
+        if ma_value is None:
+            return StrategySignal(SignalType.HOLD, 0.0, f"MA{period} not available")
+            
+        # Current position state
+        is_long = current_position and current_position.get('type') == 'long'
+        is_short = current_position and current_position.get('type') == 'short'
+        
+        # Logic: Price > MA -> Bullish
+        if price > ma_value:
+            if is_long:
+                return StrategySignal(SignalType.HOLD, 1.0, f"Price {price:.2f} > MA{period} {ma_value:.2f}. Stay Long.")
+            elif is_short:
+                return StrategySignal(SignalType.CLOSE_SHORT, 1.0, f"Price {price:.2f} crossed above MA{period} {ma_value:.2f}. Close Short.")
+            else:
+                return StrategySignal(SignalType.OPEN_LONG, 1.0, f"Price {price:.2f} > MA{period} {ma_value:.2f}. Open Long.")
+                
+        # Logic: Price < MA -> Bearish
+        elif price < ma_value:
+            if is_short:
+                return StrategySignal(SignalType.HOLD, 1.0, f"Price {price:.2f} < MA{period} {ma_value:.2f}. Stay Short.")
+            elif is_long:
+                return StrategySignal(SignalType.CLOSE_LONG, 1.0, f"Price {price:.2f} crossed below MA{period} {ma_value:.2f}. Close Long.")
+            else:
+                return StrategySignal(SignalType.OPEN_SHORT, 1.0, f"Price {price:.2f} < MA{period} {ma_value:.2f}. Open Short.")
+                
+        return StrategySignal(SignalType.HOLD, 0.0, f"Price == MA{period}")