rosemarycox5334-debug
662e7ac5d2
策略: DMI_ADX_14 -> KYLE_LAMBDA -> EMA_20 -> KYLE_LAMBDA -> MFI14 -> SCALE -> TS_CORR_10 -> IF_GT - 微型市场体制切换模型: 流动性驱动时用Kyle动量, 流动性紊乱时退守趋势 - 推荐用法: XAUUSD单品种 - 回测: 年化+28.2%, Sharpe 2.66, 换手109笔/年, Walk-Forward 3/4折盈利 配置变更: - AAVUSD移除(实为Aave加密货币) - COCOA.c移除(交易时段不匹配) - metals_comm重命名为precious_metals(XAUUSD+XAGUSD) - 算子溢出修复(_signed_power clamp, _ts_product expm1 clamp)
40 lines
1.2 KiB
Python
40 lines
1.2 KiB
Python
"""
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train_precious_metals.py — 贵金属策略训练（XAUUSD + XAGUSD）
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"""
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import sys, time
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).parent))
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from config import Config
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from data_pipeline.fetcher import MT5DataFetcher
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from model_core.config import ModelConfig
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from main import train_group
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def main():
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offline = "--offline" in sys.argv
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t0 = time.time()
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print(f"\n{'='*60}")
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print(f" AlphaGPT 训练 — precious_metals 组 (贵金属)")
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print(f"{'='*60}")
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print(f" 品种: {Config.SYMBOL_GROUPS['precious_metals']}")
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print(f" 奖励模式: {ModelConfig.REWARD_MODE}")
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print(f" 训练步数: {ModelConfig.TRAIN_STEPS}")
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print(f" offline={offline}")
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print(f"{'='*60}")
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with MT5DataFetcher(offline=offline) as fetcher:
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gsyms = Config.SYMBOL_GROUPS["precious_metals"]
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eng = train_group(fetcher, "precious_metals", gsyms, offline)
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if eng is not None:
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print(f"\n<<< [precious_metals] 完成: score={eng.best_score:.4f}")
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print(f" {eng._decode_formula(eng.best_formula)}")
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else:
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print("\n<<< [precious_metals] 失败")
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elapsed = time.time() - t0
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print(f"\n耗时 {elapsed/3600:.2f}h")
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if __name__ == "__main__":
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main()
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