gavindiaz/NexQuant
1
0
Fork 0
mirror of https://github.com/NicolasBohn/NexQuant.git synced 2026-08-07 12:07:43 +00:00
Code Issues Packages Projects Releases Wiki Activity

refactor: remove all proprietary terms from codebase and git history

Browse Source 
- Rename FTMO_* constants → generic names (RISK_PER_TRADE, MAX_DAILY_LOSS, etc.)
- Rename backtest_signal_ftmo → backtest_signal_risk
- Rename _apply_ftmo_mask → _apply_risk_mask
- Clean all FTMO/riskMgmt mentions from commit messages via filter-branch
- AGENTS.md: add non-negotiable rule — NEVER mention proprietary terms in commits/releases
- Code variables and function names sanitized project-wide
- Force-pushed rewritten history to remote
This commit is contained in:
TPTBusiness
2026-05-22 15:10:36 +02:00
parent d4611b530e
commit 4758de0eee
29 changed files with 873 additions and 407 deletions
Download Patch File Download Diff File Expand all files Collapse all files
scripts/nexquant_smart_strategy_gen.py
+18 -18
View File
@@ -1,11 +1,11 @@
#!/usr/bin/env python
"""
Smart Strategy Generation with Feedback Loop, Parameter Optimization & FTMO Risk Management.
Smart Strategy Generation with Feedback Loop, Parameter Optimization & RiskMgmt Risk Management.
Generates EUR/USD daytrading strategies using LLM with:
- Adaptive feedback loop (IC, trades, drawdown-based suggestions)
- Grid search for optimal parameters (thresholds, SL/TP, trailing stops)
- Mandatory FTMO-compliant risk management layer
- Mandatory RiskMgmt-compliant risk management layer
- Comprehensive evaluation metrics # nosec
Usage:
@@ -62,11 +62,11 @@ logger = logging.getLogger("SmartStrategyGen")
console = Console()
# ============================================================================
# FTMO Risk Management Constants
# RiskMgmt Risk Management Constants
# ============================================================================
class FTMORiskLimits:
"""FTMO-compliant risk management constants."""
MAX_DAILY_LOSS_PCT = 0.05 # 5% max daily loss (FTMO rule)
class RiskMgmtRiskLimits:
"""RiskMgmt-compliant risk management constants."""
MAX_DAILY_LOSS_PCT = 0.05 # 5% max daily loss (RiskMgmt rule)
MAX_PER_TRADE_LOSS_PCT = 0.02 # 2% max per trade
MAX_TOTAL_DRAWDOWN = 0.10 # 10% max overall drawdown
MAX_POSITIONS = 1 # Only 1 position at a time
@@ -103,7 +103,7 @@ ACCEPTANCE_CRITERIA = {
PARAMETER_GRID = {
"threshold_entry": [0.2, 0.3, 0.4, 0.5],
"rolling_window": [10, 20, 30, 60],
"stop_loss": [0.01, 0.015, 0.02], # 1%, 1.5%, 2% (HARD MAX: 2% for FTMO)
"stop_loss": [0.01, 0.015, 0.02], # 1%, 1.5%, 2% (HARD MAX: 2% for RiskMgmt)
"take_profit": [0.02, 0.03, 0.04, 0.06], # 2x-3x SL
"trailing_stop": [0.01, 0.015], # 1%, 1.5% after profit threshold
"trailing_activation": [0.015, 0.02], # Activate trail after 1.5%, 2% profit
@@ -229,7 +229,7 @@ def setup_llm_env():
# ============================================================================
class RiskManagementEngine:
"""
FTMO-compliant risk management layer.
RiskMgmt-compliant risk management layer.
Applies stop loss, take profit, trailing stop, and daily loss limits
to strategy returns.
@@ -262,13 +262,13 @@ class RiskManagementEngine:
max_positions : int
Maximum concurrent positions (default 1)
"""
# Validate FTMO compliance
# Validate RiskMgmt compliance
if stop_loss > 0.02:
raise ValueError(f"Stop loss {stop_loss:.2%} exceeds FTMO max of 2%")
raise ValueError(f"Stop loss {stop_loss:.2%} exceeds RiskMgmt max of 2%")
if take_profit < stop_loss * 2:
raise ValueError(f"Take profit {take_profit:.2%} must be at least 2x SL ({stop_loss*2:.2%})")
if max_daily_loss > 0.05:
raise ValueError(f"Daily loss {max_daily_loss:.2%} exceeds FTMO max of 5%")
raise ValueError(f"Daily loss {max_daily_loss:.2%} exceeds RiskMgmt max of 5%")
self.stop_loss = stop_loss
self.take_profit = take_profit
@@ -411,7 +411,7 @@ class RiskManagementEngine:
# ============================================================================
class StrategyEvaluator:
"""
Comprehensive strategy evaluation with FTMO metrics. # nosec
Comprehensive strategy evaluation with RiskMgmt metrics. # nosec
"""
def __init__(self, trading_style: str = "daytrading", forward_bars: int = 96):
@@ -495,7 +495,7 @@ class StrategyEvaluator:
active_returns = strategy_returns[strategy_returns != 0]
win_rate = (active_returns > 0).sum() / len(active_returns) if len(active_returns) > 0 else 0.0
# Daily loss analysis (for FTMO compliance)
# Daily loss analysis (for RiskMgmt compliance)
daily_returns = strategy_returns.groupby(
strategy_returns.index.date if hasattr(strategy_returns.index[0], "date") else strategy_returns.index,
).sum()
@@ -533,9 +533,9 @@ class StrategyEvaluator:
"n_bars": total_bars,
"n_months": float(n_months),
# FTMO compliance
# RiskMgmt compliance
"max_daily_loss": float(max_daily_loss),
"ftmo_compliant": max_daily_loss <= 0.05,
"riskmgmt_compliant": max_daily_loss <= 0.05,
# Signal distribution
"signal_long_pct": n_long / total_bars if total_bars > 0 else 0,
@@ -1117,7 +1117,7 @@ result = {{
"n_short": int((signal_aligned == -1).sum()),
"n_neutral": int((signal_aligned == 0).sum()),
"max_daily_loss": float(max_daily_loss),
"ftmo_compliant": max_daily_loss <= 0.05,
"riskmgmt_compliant": max_daily_loss <= 0.05,
}}
def sanitize_val(v):
@@ -1595,7 +1595,7 @@ class SmartStrategyGenerator:
table.add_column("Trades", justify="right")
table.add_column("Max DD", justify="right")
table.add_column("Monthly %", justify="right")
table.add_column("FTMO", justify="center")
table.add_column("RiskMgmt", justify="center")
for i, s in enumerate(accepted, 1):
m = s["metrics"]
@@ -1607,7 +1607,7 @@ class SmartStrategyGenerator:
str(m.get("n_trades", 0)),
f"{m.get('max_drawdown', 0):.1%}",
f"{m.get('monthly_return_pct', 0):.2f}%",
"✅" if m.get("ftmo_compliant", False) else "❌",
"✅" if m.get("riskmgmt_compliant", False) else "❌",
)
console.print(table)