tika/trader-ml
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity
Files
da30ef19eda11b44889ba17a047a838e39e91494
trader-ml/config/strategy_params.example.yaml
Tika da30ef19ed Initial commit — Trading AI Secure project complet 
Architecture Docker (8 services), FastAPI, TimescaleDB, Redis, Streamlit.
Stratégies : scalping, intraday, swing. MLEngine + RegimeDetector (HMM).
BacktestEngine + WalkForwardAnalyzer + Optuna optimizer.
Routes API complètes dont /optimize async.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-08 17:38:09 +00:00

478 lines
14 KiB
YAML
Raw Blame History

# Configuration Paramètres Stratégies - Trading AI Secure
# Copier ce fichier vers strategy_params.yaml
# ============================================================================
# CONFIGURATION GLOBALE STRATÉGIES
# ============================================================================
global_strategy_config:
# Capital allocation par stratégie (doit totaliser 1.0)
allocation:
scalping: 0.30 # 30% du capital
intraday: 0.50 # 50% du capital
swing: 0.20 # 20% du capital
# Ajustement allocation selon régime de marché
regime_based_allocation:
enabled: true
bull_market:
scalping: 0.20
intraday: 0.50
swing: 0.30 # Favoriser swing en bull
bear_market:
scalping: 0.40 # Favoriser scalping en bear
intraday: 0.40
swing: 0.10
short_bias: 0.10 # Activer short bias
sideways_market:
scalping: 0.50 # Favoriser scalping en sideways
intraday: 0.30
swing: 0.20
# ============================================================================
# STRATÉGIE SCALPING
# ============================================================================
scalping_strategy:
# Informations générales
name: "Scalping Mean Reversion"
description: "Stratégie scalping basée sur retour à la moyenne"
timeframe: "1min" # 1, 5 minutes
enabled: true
# Indicateurs techniques
indicators:
bollinger_bands:
period: 20
std_dev: 2.0
adaptive: true # Ajuster selon volatilité
rsi:
period: 14
oversold: 30
overbought: 70
adaptive: true # Ajuster seuils dynamiquement
macd:
fast_period: 12
slow_period: 26
signal_period: 9
volume:
ma_period: 20
threshold_multiplier: 1.5 # Volume > 1.5x moyenne
atr:
period: 14
multiplier_stop: 2.0 # Stop-loss à 2 ATR
multiplier_target: 3.0 # Take-profit à 3 ATR
# Conditions d'entrée
entry_conditions:
long:
- "bb_position < 0.2" # Prix proche BB lower
- "rsi < rsi_oversold" # RSI oversold
- "macd_hist > 0" # MACD histogram positif
- "volume_ratio > volume_threshold" # Volume confirmation
- "confidence >= min_confidence" # Confiance suffisante
short:
- "bb_position > 0.8" # Prix proche BB upper
- "rsi > rsi_overbought" # RSI overbought
- "macd_hist < 0" # MACD histogram négatif
- "volume_ratio > volume_threshold"
- "confidence >= min_confidence"
# Gestion de position
position_management:
entry_type: "market" # market, limit
exit_type: "market" # market, limit
use_trailing_stop: true
trailing_stop_activation: 0.005 # Activer à +0.5%
trailing_stop_distance: 0.003 # Distance 0.3%
partial_take_profit: true
partial_tp_levels:
- level: 0.003 # 0.3%
size: 0.5 # Fermer 50%
- level: 0.005 # 0.5%
size: 0.3 # Fermer 30%
# Filtres
filters:
time_filter:
enabled: true
trading_hours:
- start: "08:00"
end: "17:00"
timezone: "Europe/London"
spread_filter:
enabled: true
max_spread_pct: 0.001 # 0.1% spread maximum
volatility_filter:
enabled: true
min_volatility: 0.005 # 0.5% minimum
max_volatility: 0.03 # 3% maximum
# Optimisation adaptative
adaptive_optimization:
enabled: true
optimization_frequency: "daily" # daily, weekly
method: "bayesian" # bayesian, grid, random
parameters_to_optimize:
- "bb_period"
- "bb_std"
- "rsi_period"
- "rsi_oversold"
- "rsi_overbought"
- "volume_threshold"
- "min_confidence"
constraints:
bb_period: [10, 30]
bb_std: [1.5, 3.0]
rsi_period: [10, 20]
rsi_oversold: [20, 35]
rsi_overbought: [65, 80]
volume_threshold: [1.2, 2.0]
min_confidence: [0.5, 0.8]
# ============================================================================
# STRATÉGIE INTRADAY
# ============================================================================
intraday_strategy:
# Informations générales
name: "Intraday Trend Following"
description: "Stratégie intraday suivant les tendances"
timeframe: "15min" # 15, 30, 60 minutes
enabled: true
# Indicateurs techniques
indicators:
ema:
fast_period: 9
slow_period: 21
trend_period: 50
adaptive: true
adx:
period: 14
threshold: 25 # ADX > 25 = tendance forte
atr:
period: 14
multiplier_stop: 2.5
multiplier_target: 5.0 # R:R 2:1
volume:
ma_period: 20
confirmation_threshold: 1.2
pivot_points:
type: "standard" # standard, fibonacci, camarilla
lookback_period: 1 # 1 jour
# Conditions d'entrée
entry_conditions:
long:
- "ema_fast > ema_slow" # EMA fast au-dessus slow
- "ema_fast_prev <= ema_slow_prev" # Crossover récent
- "close > ema_trend" # Prix au-dessus tendance
- "adx > adx_threshold" # Tendance forte
- "volume_ratio > volume_confirmation"
- "confidence >= min_confidence"
short:
- "ema_fast < ema_slow"
- "ema_fast_prev >= ema_slow_prev"
- "close < ema_trend"
- "adx > adx_threshold"
- "volume_ratio > volume_confirmation"
- "confidence >= min_confidence"
# Gestion de position
position_management:
entry_type: "market"
exit_type: "market"
use_trailing_stop: true
trailing_stop_activation: 0.01 # Activer à +1%
trailing_stop_distance: 0.005 # Distance 0.5%
partial_take_profit: true
partial_tp_levels:
- level: 0.01 # 1%
size: 0.4 # Fermer 40%
- level: 0.015 # 1.5%
size: 0.3 # Fermer 30%
# Breakeven
move_to_breakeven: true
breakeven_trigger: 0.008 # À +0.8%
breakeven_offset: 0.002 # +0.2% au-dessus entry
# Filtres
filters:
time_filter:
enabled: true
avoid_news_times: true # Éviter annonces économiques
trading_sessions:
- name: "London"
start: "08:00"
end: "16:30"
- name: "New York"
start: "13:30"
end: "20:00"
trend_filter:
enabled: true
min_trend_strength: 0.6 # ADX normalisé
support_resistance_filter:
enabled: true
min_distance_from_sr: 0.005 # 0.5% distance minimum
# Optimisation adaptative
adaptive_optimization:
enabled: true
optimization_frequency: "weekly"
method: "bayesian"
parameters_to_optimize:
- "ema_fast"
- "ema_slow"
- "ema_trend"
- "adx_threshold"
- "atr_multiplier_stop"
- "atr_multiplier_target"
- "min_confidence"
constraints:
ema_fast: [5, 15]
ema_slow: [15, 30]
ema_trend: [40, 60]
adx_threshold: [20, 30]
atr_multiplier_stop: [2.0, 3.5]
atr_multiplier_target: [4.0, 6.0]
min_confidence: [0.5, 0.75]
# ============================================================================
# STRATÉGIE SWING
# ============================================================================
swing_strategy:
# Informations générales
name: "Swing Multi-Timeframe"
description: "Stratégie swing avec analyse multi-timeframe"
timeframe: "4h" # 4h, 1D
enabled: true
# Indicateurs techniques
indicators:
sma:
short_period: 20
long_period: 50
adaptive: true
rsi:
period: 14
neutral_zone: [40, 60] # Zone neutre pour swing
macd:
fast_period: 12
slow_period: 26
signal_period: 9
fibonacci:
lookback_period: 50 # 50 barres pour high/low
key_levels: [0.236, 0.382, 0.5, 0.618, 0.786]
atr:
period: 14
multiplier_stop: 3.0
multiplier_target: 6.0 # R:R 2:1
# Multi-timeframe analysis
multi_timeframe:
enabled: true
higher_timeframe: "1D" # Timeframe supérieur
confirm_trend: true # Confirmer tendance HTF
htf_indicators:
- "sma_50"
- "sma_200"
- "trend_direction"
# Conditions d'entrée
entry_conditions:
long:
- "sma_short > sma_long" # SMA short au-dessus long
- "rsi >= 40 and rsi <= 60" # RSI zone neutre
- "macd > macd_signal" # MACD bullish
- "close_near_fib_support" # Prix près support Fibonacci
- "htf_trend == 'UP'" # Tendance HTF haussière
- "confidence >= min_confidence"
short:
- "sma_short < sma_long"
- "rsi >= 40 and rsi <= 60"
- "macd < macd_signal"
- "close_near_fib_resistance"
- "htf_trend == 'DOWN'"
- "confidence >= min_confidence"
# Gestion de position
position_management:
entry_type: "limit" # Limit orders pour meilleur prix
entry_offset: 0.002 # 0.2% offset
exit_type: "market"
use_trailing_stop: true
trailing_stop_activation: 0.02 # Activer à +2%
trailing_stop_distance: 0.01 # Distance 1%
partial_take_profit: true
partial_tp_levels:
- level: 0.03 # 3%
size: 0.33 # Fermer 33%
- level: 0.05 # 5%
size: 0.33 # Fermer 33%
# Scale in
scale_in: true
scale_in_levels:
- trigger: 0.01 # À +1%
size: 0.5 # Ajouter 50% position initiale
# Filtres
filters:
fundamental_filter:
enabled: true
avoid_earnings: true # Éviter publications résultats
avoid_major_news: true # Éviter news majeures
seasonal_filter:
enabled: false # Optionnel
favorable_months: [1, 2, 3, 10, 11, 12] # Mois favorables
correlation_filter:
enabled: true
max_correlation_with_existing: 0.7
# Optimisation adaptative
adaptive_optimization:
enabled: true
optimization_frequency: "monthly"
method: "bayesian"
parameters_to_optimize:
- "sma_short"
- "sma_long"
- "rsi_period"
- "fibonacci_lookback"
- "atr_multiplier_stop"
- "min_confidence"
constraints:
sma_short: [15, 25]
sma_long: [40, 60]
rsi_period: [10, 20]
fibonacci_lookback: [30, 70]
atr_multiplier_stop: [2.5, 4.0]
min_confidence: [0.5, 0.7]
# ============================================================================
# MACHINE LEARNING CONFIGURATION
# ============================================================================
ml_config:
# Modèles utilisés
models:
- name: "xgboost"
enabled: true
priority: 1
hyperparameters:
n_estimators: 100
max_depth: 6
learning_rate: 0.1
- name: "lightgbm"
enabled: true
priority: 2
hyperparameters:
n_estimators: 100
max_depth: 6
learning_rate: 0.1
- name: "random_forest"
enabled: false
priority: 3
hyperparameters:
n_estimators: 100
max_depth: 10
# Features engineering
features:
technical_indicators: true
price_patterns: true
volume_profile: true
market_microstructure: false # Avancé
sentiment_analysis: false # Nécessite API news
# Training
training:
train_test_split: 0.7 # 70% train, 30% test
validation_method: "walk_forward" # walk_forward, k_fold
retraining_frequency: "weekly" # daily, weekly, monthly
min_samples: 1000 # Minimum échantillons
# Ensemble
ensemble:
enabled: true
method: "stacking" # stacking, voting, blending
meta_learner: "logistic_regression"
# ============================================================================
# BACKTESTING CONFIGURATION
# ============================================================================
backtesting_config:
# Données
data:
start_date: "2020-01-01"
end_date: "2024-01-01"
symbols: ["EURUSD", "GBPUSD", "USDJPY"]
# Coûts de transaction
transaction_costs:
commission_pct: 0.0001 # 0.01% commission
slippage_pct: 0.0005 # 0.05% slippage
spread_pct: 0.0002 # 0.02% spread
# Validation
validation:
walk_forward:
enabled: true
train_window: 252 # 1 an
test_window: 63 # 3 mois
step_size: 21 # 1 mois
monte_carlo:
enabled: true
n_simulations: 10000
confidence_level: 0.95
out_of_sample:
enabled: true
oos_ratio: 0.30 # 30% out-of-sample
# Métriques
metrics:
required:
sharpe_ratio: 1.5
max_drawdown: 0.10
win_rate: 0.55
profit_factor: 1.3
calmar_ratio: 0.5
# ============================================================================
# NOTES
# ============================================================================
# 1. Tous les paramètres sont ADAPTATIFS par défaut
# 2. L'IA ajustera ces valeurs quotidiennement/hebdomadairement
# 3. Les contraintes définissent les limites d'optimisation
# 4. Tester changements en backtest avant paper trading
Reference in New Issue View Git Blame Copy Permalink