gavindiaz/LSTM-PPO-Reinforcement-Learning-Trading-Bot-for-MetaTrader-5-XAUUSD-
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Update mt5-xau-lstm-ppo-stoch-adx-bot.py

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This commit is contained in:
Vittus Mikiassen
2026-06-19 16:48:40 +02:00
committed by GitHub
parent 57578c9c3c
commit db131dd5b9
1 changed files with 76 additions and 55 deletions
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mt5-xau-lstm-ppo-stoch-adx-bot.py
+76 -55
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@@ -7,20 +7,9 @@ import random
from collections import deque
from datetime import datetime, timedelta
import subprocess
# import requests
# import threading
# from multiprocessing import Process
import time
# from time import timezone
# from decimal import Decimal
# from pybit.unified_trading import HTTP
# from pybit.unified_trading import WebSocket
# from sklearn.neighbors import NearestNeighbors
# from sklearn.metrics.pairwise import cosine_similarity
# from concurrent.futures import ThreadPoolExecutor, as_completed
# import subprocess
# import glob
# import shutil
import argparse
import threading
import MetaTrader5 as mt5
import torch
import torch.nn as nn
@@ -253,12 +242,12 @@ def BearishMB(df, multiplier=1.5):
return ((df["Low"] <= ob_high) &
(df["High"] >= ob_low)).astype(int)
def AsiaHighDist(df):
def AsiaHigh(df):
# Asia session: 23:00-06:59 GMT
asia = (df.index.hour >= 2) | (df.index.hour < 9)
asia = (df.index.hour >= 1) | (df.index.hour < 9)
# Trading day starts at 23:00
trade_day = (df.index - pd.Timedelta(hours=23)).date
trade_day = (df.index - pd.Timedelta(hours=24)).date
asia_high = (
df["High"]
@@ -268,12 +257,12 @@ def AsiaHighDist(df):
.ffill()
)
return asia_high - df["Close"]
return asia_high
def AsiaLowDist(df):
asia = (df.index.hour >= 2) | (df.index.hour < 9)
def AsiaLow(df):
asia = (df.index.hour >= 1) | (df.index.hour < 9)
trade_day = (df.index - pd.Timedelta(hours=23)).date
trade_day = (df.index - pd.Timedelta(hours=24)).date
asia_low = (
df["Low"]
@@ -283,7 +272,7 @@ def AsiaLowDist(df):
.ffill()
)
return asia_low - df["Close"]
return asia_low
def VWAP(df, atr_period=14, atr_multiplier=1.0):
@@ -338,7 +327,7 @@ def VWAP(df, atr_period=14, atr_multiplier=1.0):
# --------------------------------------------------
# Derived features
# --------------------------------------------------
dist = df["Close"] - vwap
# dist = df["Close"] - vwap
above = (df["Close"] > vwap).astype(int)
below = (df["Close"] < vwap).astype(int)
@@ -352,7 +341,7 @@ def VWAP(df, atr_period=14, atr_multiplier=1.0):
vwap,
upper,
lower,
dist,
# dist,
above,
below,
above_upper,
@@ -449,22 +438,22 @@ def add_indicators(df):
df["bullish_rb"], df["bearish_rb"] = RejectionBlocks(df)
df["vwap"], df["vwap_upper"], df["vwap_lower"], df["vwap_dist"], df["above_vwap"], df["below_vwap"], df["vwap_above_upper"], df["vwap_below_lower"], df["vwap_slope"] = VWAP(df)
df["vwap"], df["vwap_upper"], df["vwap_lower"], df["above_vwap"], df["below_vwap"], df["vwap_above_upper"], df["vwap_below_lower"], df["vwap_slope"] = VWAP(df)
df["sell_score"] = SellScore(df)
df["buy_score"] = BuyScore(df)
df["volume_ma"] = VolumeMA(df)
# df["asia_high_dist"] = AsiaHighDist(df)
# df["asia_low_dist"] = AsiaLowDist(df)
df["asia_high"] = AsiaHigh(df)
df["asia_low"] = AsiaLow(df)
df = df[["Open", "High", "Low", "Close",
"k", "k_smooth", "adx", "+di", "-di", "EMA7", "EMA21", "EMA_DIFF",
"k", "k_smooth", "adx", "+di", "-di", "EMA7", "EMA21", "EMA_DIFF",
"indecision", "bullish_ob", "bearish_ob", "bullish_fvg", "bearish_fvg", "eqh", "eql", "bearish_mb", "bullish_mb", "bullish_rb", "bearish_rb",
"vwap", "vwap_upper", "vwap_lower", "vwap_dist", "above_vwap", "below_vwap", "vwap_above_upper", "vwap_below_lower", "vwap_slope",
"vwap", "vwap_upper", "vwap_lower", "above_vwap", "below_vwap", "vwap_above_upper", "vwap_below_lower", "vwap_slope",
"volume_ma",
# "asia_high_dist", "asia_low_dist",
"asia_high", "asia_low",
"sell_score", "buy_score"]].copy()
# df = df[["Open", "High", "Low", "Close", "EMA_crossover", "macd_zone", "macd_line", "macd_signal", "macd_line_diff", "macd_signal_diff", "macd_line_slope", "macd_signal_line_slope" , "macd_osma", "macd_crossover", "bb_sma", "bb_upper", "bb_lower", "RSI_zone", "ADX_zone", "+DI_val", "-DI_val", "ATR", "order_block_type"]].copy()
@@ -1072,8 +1061,8 @@ def train_bot(symbol="XAUUSD"):
"vwap_below_lower",
"vwap_slope",
"volume_ma",
# "asia_high_dist",
# "asia_low_dist",
"asia_high",
"asia_low",
"sell_score",
"buy_score"
]
@@ -1198,8 +1187,8 @@ def train_bot(symbol="XAUUSD"):
# ==============================================================
# if action == 1 and not in_position and df["+di"].iloc[i] > df["-di"].iloc[i] and df["EMA_DIFF"].iloc[i] > 0 and df["k"].iloc[i] < 80:
# if action == 1 and not in_position and df["EMA7"].iloc[i] > df["EMA21"].iloc[i] and df["k"].iloc[i] < 80:
if action == 1:
if action == 1 and not in_position and df["EMA7"].iloc[i] > df["EMA21"].iloc[i] and df["k"].iloc[i] < 80:
# if action == 1:
in_position = True
position_type = "long"
@@ -1241,8 +1230,8 @@ def train_bot(symbol="XAUUSD"):
# elif action == 2 and not in_position and df["-di"].iloc[i] > df["+di"].iloc[i] and df["EMA_DIFF"].iloc[i] < 0 and df["k"].iloc[i] > 20:
# elif action == 2 and not in_position and df["buy_score"].iloc[i] < df["sell_score"].iloc[i]:
# elif action == 2 and not in_position and df["EMA7"].iloc[i] < df["EMA21"].iloc[i] and df["k"].iloc[i] > 20:
elif action == 2:
elif action == 2 and not in_position and df["EMA7"].iloc[i] < df["EMA21"].iloc[i] and df["k"].iloc[i] > 20:
# elif action == 2:
in_position = True
position_type = "short"
@@ -1352,10 +1341,10 @@ def train_bot(symbol="XAUUSD"):
)
# realized_reward += (
# reward += (
# # remaining_pips * (position_size / 0.25) - SPREAD_AND_COMMISSION * (position_size / 0.25)
# remaining_pips - SPREAD_AND_COMMISSION * (position_size / 0.25)
# )
reward += (
# remaining_pips * (position_size / 0.25) - SPREAD_AND_COMMISSION * (position_size / 0.25)
remaining_pips - SPREAD_AND_COMMISSION
)
pnl += (
remaining_pips * (position_size) - SPREAD_AND_COMMISSION * (position_size)
# remaining_pips - SPREAD_AND_COMMISSION * (position_size / 0.25)
@@ -1457,9 +1446,9 @@ def train_bot(symbol="XAUUSD"):
)
# realized_reward += (
# reward += (
# remaining_pips - SPREAD_AND_COMMISSION * (position_size / 0.25)
# )
reward += (
remaining_pips - SPREAD_AND_COMMISSION
)
pnl += (
remaining_pips * (position_size) - SPREAD_AND_COMMISSION * (position_size)
)
@@ -1833,8 +1822,8 @@ def test_bot(symbol="XAUUSD"):
"vwap_below_lower",
"vwap_slope",
"volume_ma",
# "asia_high_dist",
# "asia_low_dist",
"asia_high",
"asia_low",
"sell_score",
"buy_score"
]
@@ -1849,8 +1838,11 @@ def test_bot(symbol="XAUUSD"):
)
# agent.model.debug = True
agent.loadcheckpoint("XAUUSD")
try:
agent.loadcheckpoint("XAUUSD")
except:
print("No file for prior training, cancelling test.")
return
# ==========================================================
# INITIAL LOAD
@@ -1860,7 +1852,7 @@ def test_bot(symbol="XAUUSD"):
symbol,
mt5.TIMEFRAME_M5,
0,
200
300
)
# rates_m1 = mt5.copy_rates_from_pos(
@@ -1996,7 +1988,7 @@ def test_bot(symbol="XAUUSD"):
)
# raw_df = raw_df.tail(200).reset_index(drop=True)
raw_df = raw_df.tail(200)
raw_df = raw_df.tail(300)
# print("Before indicators:", len(df))
# df = add_indicators(raw_df.copy())
@@ -2056,7 +2048,7 @@ def test_bot(symbol="XAUUSD"):
if df["adx"].iloc[-1] < 20:
action = 0
print(f"action: {action}")
print(f"Test action: {action}")
# ==================================================
# OPEN NEW TRADE
@@ -2075,7 +2067,8 @@ def test_bot(symbol="XAUUSD"):
# if action == 1 and df["adx"].iloc[-1] > 20 and df["+di"].iloc[-1] > df["-di"].iloc[-1] and df["EMA_DIFF"].iloc[-1] > 0 and df["k"].iloc[-1] < 80:
# if action == 1 and df["buy_score"].iloc[-1] > df["sell_score"].iloc[-1]:
if action == 1:
if action == 1 and df["EMA7"].iloc[-1] > df["EMA21"].iloc[-1] and df["k"].iloc[-1] < 80:
# if action == 1:
# print(
# f"[{symbol}] PPO BUY"
# )
@@ -2087,7 +2080,8 @@ def test_bot(symbol="XAUUSD"):
# elif action == 2 and df["adx"].iloc[-1] > 20 and df["-di"].iloc[-1] > df["+di"].iloc[-1] and df["EMA_DIFF"].iloc[-1] < 0 and df["k"].iloc[-1] > 20:
# elif action == 2 and df["buy_score"].iloc[-1] < df["sell_score"].iloc[-1]:
elif action == 2:
elif action == 2 and df["EMA7"].iloc[-1] < df["EMA21"].iloc[-1] and df["k"].iloc[-1] > 20:
# elif action == 2:
# print(
# f"[{symbol}] PPO SELL"
# )
@@ -2284,9 +2278,36 @@ def update_xauusd_data():
)
def main():
# update_xauusd_data()
train_bot("XAUUSD")
# test_bot(symbol="XAUUSD-VIP")
parser = argparse.ArgumentParser()
parser.add_argument("--train", action="store_true")
parser.add_argument("--test", action="store_true")
parser.add_argument("--symbol", default="XAUUSD-VIP")
args = parser.parse_args()
threads = []
if args.train:
t = threading.Thread(
target=train_bot,
# args=(args.symbol),
daemon=True
)
t.start()
threads.append(t)
if args.test:
t = threading.Thread(
target=test_bot,
args=(args.symbol,),
daemon=True
)
t.start()
threads.append(t)
for t in threads:
t.join()
main()