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 08:11:59 +02:00
committed by GitHub
parent ecaa82f69f
commit 34ab3b4ff3
1 changed files with 62 additions and 43 deletions
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mt5-xau-lstm-ppo-stoch-adx-bot.py
+62 -43
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@@ -177,14 +177,23 @@ def Indecision(df, threshold=0.2):
return (body / candle_range < threshold).astype(int)
def RejectionBlock(df, wick_ratio=2.0):
def RejectionBlocks(df, wick_ratio=2.0):
body = (df["Close"] - df["Open"]).abs()
upper = df["High"] - df[["Open","Close"]].max(axis=1)
lower = df[["Open","Close"]].min(axis=1) - df["Low"]
upper = df["High"] - df[["Open", "Close"]].max(axis=1)
lower = df[["Open", "Close"]].min(axis=1) - df["Low"]
return ((upper > body * wick_ratio) |
(lower > body * wick_ratio)).astype(int)
bullish_rb = (
(lower > body * wick_ratio) &
(lower > upper)
).astype(int)
bearish_rb = (
(upper > body * wick_ratio) &
(upper > lower)
).astype(int)
return bullish_rb, bearish_rb
def BullishOB(df, multiplier=1.5):
body = (df["Close"] - df["Open"]).abs()
@@ -288,7 +297,8 @@ def BuyScore(df):
df["bullish_mb"] * 1 +
df["bullish_fvg"] * 1 +
df["eql"] * 1 +
df["rb"] * 1 -
df["bullish_rb"] * 1 -
df["bearish_rb"] * 1 -
df["bearish_ob"] * 2 -
df["bearish_fvg"] * 1 -
df["eqh"] * 1
@@ -306,7 +316,8 @@ def SellScore(df):
df["bearish_mb"] * 1 +
df["bearish_fvg"] * 1 +
df["eqh"] * 1 +
df["rb"] * 1 -
df["bearish_rb"] * 1 -
df["bullish_rb"] * 1 -
df["bullish_ob"] * 2 -
df["bullish_fvg"] * 1 -
df["eql"] * 1
@@ -322,7 +333,6 @@ def add_indicators(df):
df['EMA_DIFF'] = df['EMA7'] - df['EMA21']
df["indecision"] = Indecision(df)
df["rb"] = RejectionBlock(df)
df["bullish_ob"] = BullishOB(df)
df["bearish_ob"] = BearishOB(df)
@@ -336,16 +346,17 @@ def add_indicators(df):
df["bearish_mb"] = BearishMB(df)
df["bullish_mb"] = BullishMB(df)
df["bullish_rb"], df["bearish_rb"] = RejectionBlocks(df)
df["sell_score"] = SellScore(df)
df["buy_score"] = BuyScore(df)
df["asia_high_dist"] = AsiaHighDist(df)
df["asia_low_dist"] = AsiaLowDist(df)
# df["asia_high_dist"] = AsiaHighDist(df)
# df["asia_low_dist"] = AsiaLowDist(df)
df = df[["Open", "High", "Low", "Close", "k", "k_smooth", "adx", "+di", "-di", "EMA7", "EMA21", "EMA_DIFF",
"indecision", "rb", "bullish_ob", "bearish_ob", "bullish_fvg", "bearish_fvg", "eqh", "eql", "bearish_mb", "bullish_mb",
"sell_score", "buy_score",
"asia_high_dist", "asia_low_dist"]].copy()
"indecision", "bullish_ob", "bearish_ob", "bullish_fvg", "bearish_fvg", "eqh", "eql", "bearish_mb", "bullish_mb", "bullish_rb", "bearish_rb",
"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()
df.dropna(inplace=True)
@@ -933,7 +944,6 @@ def train_bot(symbol="XAUUSD"):
"EMA21",
"EMA_DIFF",
"indecision",
"rb",
"bullish_ob",
"bearish_ob",
"bullish_fvg",
@@ -942,10 +952,12 @@ def train_bot(symbol="XAUUSD"):
"eql",
"bearish_mb",
"bullish_mb",
"bullish_rb",
"bearish_rb",
"sell_score",
"buy_score",
"asia_high_dist",
"asia_low_dist"
"buy_score"
# "asia_high_dist",
# "asia_low_dist"
]
agent = LSTMPPOAgent(
@@ -997,7 +1009,7 @@ def train_bot(symbol="XAUUSD"):
trade_returns = []
# STANDARD_SL_PIPS = 100
RR_RATIO = 0.26
RR_RATIO = 0.375
# SPREAD_AND_COMMISSION = 1.2
# SL_PIPS = 50
@@ -1026,8 +1038,8 @@ def train_bot(symbol="XAUUSD"):
high = current["High"]
low = current["Low"]
# SL_PIPS = round(current_price * 0.00125 * 10, 0)
SL_PIPS = 50
TP1_PIPS = round(SL_PIPS * 0.26, 0)
SL_PIPS = 40
TP1_PIPS = round(SL_PIPS * RR_RATIO, 0)
# TP2_PIPS = round(SL_PIPS * 2, 0)
# TP3_PIPS = round(SL_PIPS * 3, 0)
# TP4_PIPS = round(SL_PIPS * 4, 0)
@@ -1165,8 +1177,8 @@ def train_bot(symbol="XAUUSD"):
if not tp1_hit and high >= tp1_price:
# realized_reward += SL_PIPS - SPREAD_AND_COMMISSION
pnl += SL_PIPS * 0.2 - SPREAD_AND_COMMISSION
reward += SL_PIPS * 0.2 - SPREAD_AND_COMMISSION
pnl += SL_PIPS * RR_RATIO - SPREAD_AND_COMMISSION
reward += SL_PIPS * RR_RATIO - SPREAD_AND_COMMISSION
position_size -= 0.25
tp1_hit = True
@@ -1272,8 +1284,8 @@ def train_bot(symbol="XAUUSD"):
if not tp1_hit and low <= tp1_price:
# realized_reward += SL_PIPS * 2 - SPREAD_AND_COMMISSION
reward += SL_PIPS * 0.2 - SPREAD_AND_COMMISSION
pnl += SL_PIPS * 0.2 - SPREAD_AND_COMMISSION
reward += SL_PIPS * RR_RATIO - SPREAD_AND_COMMISSION
pnl += SL_PIPS * RR_RATIO - SPREAD_AND_COMMISSION
# position_size -= 0.25
tp1_hit = True
@@ -1473,6 +1485,7 @@ def train_bot(symbol="XAUUSD"):
)
agent.train()
agent.savecheckpoint(symbol)
print("Finished training PPO")
# ==============================================================
# FINAL TRAINING
@@ -1498,7 +1511,7 @@ def open_long(symbol, lot_size):
sl = entry - 5
tp1 = entry + 1.3
tp1 = entry + 1.5
# tp2 = entry + 10
# tp3 = entry + 15
# tp4 = entry + 20
@@ -1534,7 +1547,7 @@ def open_short(symbol, lot_size):
sl = entry + 5
tp1 = entry - 1.3
tp1 = entry - 1.5
# tp2 = entry - 10
# tp3 = entry - 15
# tp4 = entry - 20
@@ -1654,7 +1667,7 @@ def test_bot(symbol="XAUUSD"):
# print(mt5.last_error())
# return
balance = account.balance
RISK = 0.02
RISK = 0.005
# risk_per_position = max(balance * RISK / 500 / 4, 0.01)
# tick = mt5.symbol_info_tick(symbol)
@@ -1681,7 +1694,6 @@ def test_bot(symbol="XAUUSD"):
"EMA21",
"EMA_DIFF",
"indecision",
"rb",
"bullish_ob",
"bearish_ob",
"bullish_fvg",
@@ -1690,10 +1702,12 @@ def test_bot(symbol="XAUUSD"):
"eql",
"bearish_mb",
"bullish_mb",
"bullish_rb",
"bearish_rb",
"sell_score",
"buy_score",
"asia_high_dist",
"asia_low_dist"
"buy_score"
# "asia_high_dist",
# "asia_low_dist"
]
# last_m15 = None
@@ -1737,6 +1751,9 @@ def test_bot(symbol="XAUUSD"):
'time': 'Date'
}, inplace=True)
df["Date"] = pd.to_datetime(df["Date"], unit="s")
df.set_index("Date", inplace=True)
raw_df = df
df = add_indicators(df)
@@ -1769,7 +1786,7 @@ def test_bot(symbol="XAUUSD"):
tick = mt5.symbol_info_tick(symbol)
# SL_PIPS = round(tick.bid * 0.00125 * 10, 0)
SL_PIPS = 50
SL_PIPS = 40
risk_per_position = min(
max((balance * RISK) / (SL_PIPS * 10), 0.01),
100.0
@@ -1834,21 +1851,23 @@ def test_bot(symbol="XAUUSD"):
ignore_index=True
)
df.set_index("Date", inplace=True)
df = (
df.tail(200)
.reset_index(drop=True)
# .reset_index(drop=True)
)
"""
raw_df = pd.concat(
[raw_df, new_row],
ignore_index=True
)
raw_df = raw_df.tail(200).reset_index(drop=True)
"""
# raw_df = raw_df.tail(200).reset_index(drop=True)
raw_df = raw_df.tail(200)
# print("Before indicators:", len(df))
# df = add_indicators(raw_df.copy())
df = add_indicators(raw_df.copy())
# print("After indicators:", len(df))
# print(df.tail())
@@ -1897,7 +1916,7 @@ def test_bot(symbol="XAUUSD"):
action, _, _ = agent.select_action(
state_seq,
open_pos > 0,
training=True
training=False
)
if df["adx"].iloc[-1] < 20:
@@ -1922,9 +1941,9 @@ 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:
print(
f"[{symbol}] PPO BUY"
)
# print(
# f"[{symbol}] PPO BUY"
# )
open_long(
symbol,
@@ -1933,9 +1952,9 @@ 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:
print(
f"[{symbol}] PPO SELL"
)
# print(
# f"[{symbol}] PPO SELL"
# )
open_short(
symbol,