fix: timezone bugs

alpaca_trader/config.json

@@ -1,12 +1,12 @@
 {
     "DEBUG_MODE": true,
     "SYMBOL": "SPY",
-    "BAR_TIMEFRAME": "15Min",
+    "BAR_TIMEFRAME": "1Day",
     "RISK_PER_TRADE": 0.01,
     "SHORT_WINDOW": 20,
     "LONG_WINDOW": 50,
     "MIN_NOTIONAL": 1.0,
-    "POLL_INTERVAL": 300,
+    "POLL_INTERVAL": 3600,
     "MAX_DRAWDOWN": 0.08,
     "PDT_RULE": true,
     "USE_TRAILING_STOP": true,
@@ -23,10 +23,10 @@
     "LIMIT_ORDER_TIMEOUT": 60,
     "ADX_THRESHOLD": 25,
     "VOLUME_MULTIPLIER": 0.7,
-    "ATR_STOP_MULTIPLIER": 2.0,
-    "MAX_HOLD_TIME": 10800,
+    "ATR_STOP_MULTIPLIER": 2.5,
+    "MAX_HOLD_TIME": 86400,
     "REGIME_DETECTION": true,
-    "MULTIFRAME_FILTER": true,
+    "MULTIFRAME_FILTER": false,
     "BB_WINDOW": 20,
     "BB_STD": 2.0,
     "USE_EMA": true,
@@ -35,15 +35,15 @@
     "VIX_THRESHOLD": 30,
     "USE_VIX_FILTER": false,
     "USE_FIBONACCI": false,
-    "MAX_TRADES_PER_DAY": 3,
+    "MAX_TRADES_PER_DAY": 2,
     "SKIP_MONDAYS_FRIDAYS": false,
-    "USE_200_SMA_FILTER": true,
+    "USE_200_SMA_FILTER": false,
     "REQUIRE_MACD_CONFIRMATION": false,
     "MIN_RISK_REWARD": 2.0,
     "PULLBACK_PERCENTAGE": 0.382,
     "ENABLE_SHORT_SELLING": false,
-    "RSI_BUY_MAX": 65,
-    "RSI_SELL_MIN": 35,
+    "RSI_BUY_MAX": 60,
+    "RSI_SELL_MIN": 20,
     "RSI_SELL_MAX": 70,
     "RSI_RANGE_OVERSOLD": 30,
     "RSI_RANGE_OVERBOUGHT": 70,

alpaca_trader/engine.py

@@ -3,7 +3,7 @@ import sys
 import logging
 import json
 import time
-from datetime import datetime, timedelta
+from datetime import datetime, timedelta, timezone
 from pathlib import Path
 from dotenv import load_dotenv
 import pandas as pd
@@ -163,6 +163,7 @@ BAR_TIMEFRAME = config.get("BAR_TIMEFRAME", "5Min")
 RISK_PER_TRADE = float(config["RISK_PER_TRADE"])
 SHORT_WINDOW = int(config["SHORT_WINDOW"])
 LONG_WINDOW = int(config["LONG_WINDOW"])
+ENABLE_SHORT_SELLING = bool(config.get("ENABLE_SHORT_SELLING", False))
 
 STRATEGY_MODE = config.get("STRATEGY_MODE", "ma_crossover")
 OR_FVG_ENABLED = bool(config.get("OR_FVG_ENABLED", False))
@@ -291,7 +292,6 @@ USE_200_SMA_FILTER = bool(config["USE_200_SMA_FILTER"])
 REQUIRE_MACD_CONFIRMATION = bool(config["REQUIRE_MACD_CONFIRMATION"])
 MIN_RISK_REWARD = float(config["MIN_RISK_REWARD"])
 PULLBACK_PERCENTAGE = float(config["PULLBACK_PERCENTAGE"])
-ENABLE_SHORT_SELLING = bool(config.get("ENABLE_SHORT_SELLING", False))
 RSI_BUY_MAX = float(config.get("RSI_BUY_MAX", 55))
 RSI_SELL_MIN = float(config.get("RSI_SELL_MIN", 45))
 RSI_SELL_MAX = float(config.get("RSI_SELL_MAX", 70))
@@ -561,8 +561,8 @@ def log_missed_signal(timestamp, signal_type, reject_reason, price_at_signal, sy
         if SIGNALS_PATH.exists():
             existing = pd.read_csv(SIGNALS_PATH)
             df = pd.concat([existing, df], ignore_index=True)
-            cutoff_date = datetime.now(EASTERN) - timedelta(days=30)
-            df['timestamp'] = pd.to_datetime(df['timestamp'], format='ISO8601')
+            cutoff_date = datetime.now(timezone.utc) - timedelta(days=30)
+            df['timestamp'] = pd.to_datetime(df['timestamp'], format='mixed', utc=True)
             df = df[df['timestamp'] > cutoff_date]
         
         df.to_csv(SIGNALS_PATH, index=False)
@@ -621,8 +621,8 @@ def log_indicators(timestamp, symbol, price, volume, rsi_val, adx_val, atr_val,
         if INDICATORS_PATH.exists():
             existing = pd.read_csv(INDICATORS_PATH)
             df = pd.concat([existing, df], ignore_index=True)
-            cutoff_date = datetime.now(EASTERN) - timedelta(days=7)
-            df['timestamp'] = pd.to_datetime(df['timestamp'], format='ISO8601')
+            df['timestamp'] = pd.to_datetime(df['timestamp'], format='ISO8601', utc=True)
+            cutoff_date = pd.Timestamp.now(tz='UTC') - timedelta(days=7)
             df = df[df['timestamp'] > cutoff_date]
         
         df.to_csv(INDICATORS_PATH, index=False)
@@ -632,7 +632,7 @@ def log_indicators(timestamp, symbol, price, volume, rsi_val, adx_val, atr_val,
 def debug_print(message):
     if DEBUG_MODE:
         debug_logger.debug(f"🔎  {message}")
-        print(f"{datetime.now(EASTERN).strftime('%Y-%m-%d %H:%M:%S,%f')[:-3]} - DEBUG - 🔎  {message}", flush=True)
+        print(f"{datetime.now().strftime('%Y-%m-%d %H:%M:%S,%f')[:-3]} - DEBUG - 🔎  {message}", flush=True)
 
 def fetch_equity():
     debug_print("Fetching account equity")
@@ -664,7 +664,9 @@ def fetch_buying_power(settlement_tracker=None):
 def get_recent_bars(symbol, limit=100):
     debug_print(f"Fetching {limit} bars for {symbol} ({BAR_TIMEFRAME})")
     try:
-        bars = api.get_bars(symbol, BAR_TIMEFRAME, limit=limit)
+        buffer = int(limit * 1.5)
+        start = (datetime.now(EASTERN) - timedelta(days=buffer)).strftime("%Y-%m-%d")
+        bars = api.get_bars(symbol, BAR_TIMEFRAME, limit=limit, start=start)
         if bars is None or len(bars) == 0:
             debug_print(f"No bars returned for {symbol}")
             return None
@@ -874,6 +876,10 @@ def calculate_position_size(equity, stop_loss, current_price):
     if position_value > max_position:
         position_value = max_position
         debug_print(f"Position capped at 25% equity: ${position_value:.2f}")
+    if position_value < MIN_NOTIONAL:
+        position_value = MIN_NOTIONAL
+        debug_print(f"Position set to minimum: ${position_value:.2f}")
+    debug_print(f"Calculated position size: ${position_value:.2f}")
     return position_value
 
 class ORFVGState:
@@ -916,18 +922,18 @@ def detect_fair_value_gap(bars, min_gap_pct=0.05):
         if bullish_gap:
             gap_size = candle_3_low - candle_1_high
             if candle_2_high > 0:
-                gap_pct = (gap_size / candle_2_high) * 100
+                gap_pct = gap_size / candle_2_high
                 if gap_pct >= min_gap_pct:
-                    debug_print(f"Bullish FVG detected: gap={gap_size:.2f} ({gap_pct:.2f}%)")
+                    debug_print(f"Bullish FVG detected: gap={gap_size:.2f} ({gap_pct*100:.2f}%)")
                     return "bullish", i + 2
         
         bearish_gap = candle_3_high < candle_1_low
         if bearish_gap:
             gap_size = candle_1_low - candle_3_high
             if candle_2_low > 0:
-                gap_pct = (gap_size / candle_2_low) * 100
+                gap_pct = gap_size / candle_2_low
                 if gap_pct >= min_gap_pct:
-                    debug_print(f"Bearish FVG detected: gap={gap_size:.2f} ({gap_pct:.2f}%)")
+                    debug_print(f"Bearish FVG detected: gap={gap_size:.2f} ({gap_pct*100:.2f}%)")
                     return "bearish", i + 2
     
     return None, None
@@ -1058,12 +1064,6 @@ def or_fvg_signal_generator(symbol):
     
     return signal, strength, stop_loss, position_type
 
-    if position_value < MIN_NOTIONAL:
-        position_value = MIN_NOTIONAL
-        debug_print(f"Position set to minimum: ${position_value:.2f}")
-    debug_print(f"Calculated position size: ${position_value:.2f}")
-    return position_value
-
 def advanced_signal_generator(symbol):
     debug_print(f"Generating signal for {symbol}")
     bars = get_recent_bars(symbol, BARS_FOR_SIGNAL)
@@ -1159,7 +1159,11 @@ def advanced_signal_generator(symbol):
     stop = 0
     position_type = None
     
-    if regime == "trend":
+    effective_regime = regime
+    if regime in ("high_vol", "low_vol"):
+        effective_regime = "trend"
+    
+    if effective_regime == "trend":
         if short_ma > long_ma and rsi_val < RSI_BUY_MAX:
             if REQUIRE_MA_CROSSOVER and not bullish_crossover:
                 debug_print("Bullish signal rejected: no recent crossover")
@@ -1188,7 +1192,7 @@ def advanced_signal_generator(symbol):
                 position_type = "short"
                 debug_print(f"SELL signal: strength={strength:.2f}, stop=${stop:.2f}")
     
-    elif regime == "range":
+    elif effective_regime == "range":
         if current_price <= lower.iloc[-1] and rsi_val < RSI_RANGE_OVERSOLD:
             if REQUIRE_CANDLE_PATTERN and not bullish_pattern:
                 debug_print("Range buy rejected: candle pattern required")
@@ -1224,7 +1228,7 @@ def scale_out_profit_taking(symbol, entry_price, current_price, stop_loss, posit
     
     if entry_price <= 0:
         debug_print("Invalid entry_price, skipping scale out")
-        return False
+        return False, None
     
     if position_type == 'long':
         profit_pct = ((current_price - entry_price) / entry_price) * 100
@@ -1336,12 +1340,20 @@ def main():
         while True:
             try:
                 clock = api.get_clock()
-                if not clock.is_open:
+                now_et = datetime.now(EASTERN)
+                market_open_time = now_et.replace(hour=9, minute=30, second=0, microsecond=0)
+                market_close_time = now_et.replace(hour=16, minute=0, second=0, microsecond=0)
+                time_based_open = now_et.weekday() < 5 and market_open_time <= now_et < market_close_time
+                if not clock.is_open and not time_based_open:
                     next_open = clock.next_open.astimezone(EASTERN)
                     wait_time = (next_open - datetime.now(EASTERN)).total_seconds()
                     logger.info(f"🌙  Market closed. Next open: {next_open.strftime('%I:%M %p ET on %A, %B %d')}")
-                    debug_print(f"Market closed, waiting {seconds_to_human_readable(int(wait_time))} until next open")
-                    time.sleep(min(wait_time, 3600))
+                    debug_print(f"Market closed, waiting {seconds_to_human_readable(int(max(wait_time, 0)))} until next open")
+                    while True:
+                        remaining = (next_open - datetime.now(EASTERN)).total_seconds()
+                        if remaining <= 0:
+                            break
+                        time.sleep(min(remaining, 3600))
                     continue
                 
                 logger.info("🔔  Market open - session starting")
@@ -1849,7 +1861,7 @@ def main():
                             pnl_pct = 0
                         status_msg += f" | PnL: {pnl_pct:+.2f}%"
                     
-                    status_msg += f" | H:{hourly_trend} | VIX:{vix_level:.1f} | {trades_today}/{MAX_TRADES_PER_DAY}"
+                    status_msg += f" | Hourly:{hourly_trend} | VIX:{vix_level:.1f} | Trades: {trades_today}/{MAX_TRADES_PER_DAY}"
                     logger.info(status_msg)
                     
                     vix_readings.append(vix_level)
@@ -1991,7 +2003,11 @@ def main():
                         logger.info(f"⏰  Next session: {next_open.strftime('%Y-%m-%d %I:%M %p ET')}")
                         logger.info(f"⏳  Sleeping {seconds_to_human_readable(int(wait_seconds))}")
                         debug_print(f"Sleeping until next market open: {seconds_to_human_readable(int(wait_seconds))}")
-                        time.sleep(wait_seconds)
+                        while True:
+                            remaining = (next_open - datetime.now(EASTERN)).total_seconds()
+                            if remaining <= 0:
+                                break
+                            time.sleep(min(remaining, 3600))
                     else:
                         time.sleep(60)
                 else:

alpaca_trader/filters.py

@@ -36,18 +36,16 @@ def check_macd_confirmation(bars: pd.DataFrame):
 def check_200_sma_filter(symbol: str, client: AlpacaClient):
     daily = client.get_bars(symbol, "1Day", limit=210)
     if len(daily) < 200:
-        return "neutral"
+        return True
     sma_200 = sma(daily["close"], 200).iloc[-1]
     price = daily["close"].iloc[-1]
-    if price > sma_200 * 1.01:
-        return "bullish"
     if price < sma_200 * 0.99:
-        return "bearish"
-    return "neutral"
+        return False
+    return True
 
 def check_multiframe_confluence(symbol: str, use_ema: bool, client: AlpacaClient = None):
     if client is None:
-        from .engine import api as client
+        return "neutral"
     hourly = client.get_bars(symbol, "1Hour", limit=50)
     if len(hourly) < 50:
         return "neutral"
@@ -99,3 +97,4 @@ def get_vix(client: AlpacaClient, symbol: str, use_vix_filter: bool):
         logger.warning(f"Could not calculate volatility: {e}")
     logger.warning("VIX data unavailable, skipping VIX filter for this iteration")
     return 0
+