Simon
73d191b43a
- 新增 finance/tests/ 6 个测试套件（agents/backtest/dao_upsert/factors/features/fundamental_lookahead） - 数据层: data_manager / dao 优化，新增 upsert 逻辑 - 因子层: 基本面因子抽象定位 _mapping、ROE/PE/PB 重构 - 回测层: vectorbt/engine 大改动（251 行），report 增强 - ML 层: features/backtest_integration 特征工程与回测优化 - CLI: agent_cli 重构 - config/settings 扩充配置项
132 lines
5.2 KiB
Python
132 lines
5.2 KiB
Python
"""
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因子注册表。
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通过名称获取因子实例，方便回测和策略配置时引用。
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"""
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from factors.base import BaseFactor
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from factors.technical.momentum import MomentumFactor
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from factors.technical.rsi import RSIFactor
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from factors.technical.macd import MACDFactor
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from factors.technical.volume import VolumeFactor, VolumeChangeFactor
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from factors.technical.bollinger import BollingerFactor, BollingerWidthFactor
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from factors.technical.atr import ATRFactor, ATRRatioFactor
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from factors.technical.ma_cross import MACrossFactor, MADeviationFactor
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from factors.technical.volatility import VolatilityFactor, DownsideVolatilityFactor
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from factors.technical.turnover import TurnoverFactor, TurnoverChangeFactor
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from factors.technical.amplitude import AmplitudeFactor
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from factors.fundamental.roe import ROEFactor
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from factors.fundamental.pe_pb import PEFactor, PBFactor, EPFactor
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from factors.sentiment.sentiment_factor import (
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NewsSentimentFactor,
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SentimentMomentumFactor,
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SentimentConfidenceFactor,
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)
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# ── 内置因子工厂函数 ──────────────────────────────────────
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_BUILTIN_FACTORIES: dict[str, callable] = { # type: ignore
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# 动量
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"momentum_5": lambda: MomentumFactor(period=5),
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"momentum_10": lambda: MomentumFactor(period=10),
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"momentum_20": lambda: MomentumFactor(period=20),
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"momentum_60": lambda: MomentumFactor(period=60),
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# RSI
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"rsi_7": lambda: RSIFactor(period=7),
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"rsi_14": lambda: RSIFactor(period=14),
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# MACD
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"macd": lambda: MACDFactor(),
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"macd_5_35_5": lambda: MACDFactor(fast=5, slow=35, signal=5),
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# 量价
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"vol_ratio_5": lambda: VolumeFactor(period=5),
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"vol_ratio_20": lambda: VolumeFactor(period=20),
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"vol_chg_5": lambda: VolumeChangeFactor(period=5),
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# 布林
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"boll": lambda: BollingerFactor(),
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"boll_width": lambda: BollingerWidthFactor(),
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# ATR
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"atr_14": lambda: ATRFactor(period=14),
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"atr_ratio_14": lambda: ATRRatioFactor(period=14),
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# 均线
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"ma_cross_5_20": lambda: MACrossFactor(fast=5, slow=20),
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"ma_cross_10_60": lambda: MACrossFactor(fast=10, slow=60),
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"ma_dev_20": lambda: MADeviationFactor(period=20),
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"ma_dev_60": lambda: MADeviationFactor(period=60),
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# 波动率
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"volatility_20": lambda: VolatilityFactor(period=20),
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"volatility_60": lambda: VolatilityFactor(period=60),
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"down_vol_20": lambda: DownsideVolatilityFactor(period=20),
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# 换手率
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"turnover_5": lambda: TurnoverFactor(period=5),
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"turnover_chg_5": lambda: TurnoverChangeFactor(period=5),
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# 振幅
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"amplitude_5": lambda: AmplitudeFactor(period=5),
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"amplitude_20": lambda: AmplitudeFactor(period=20),
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# 基本面
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"roe": lambda: ROEFactor(),
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"pe": lambda: PEFactor(),
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"pb": lambda: PBFactor(),
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"ep": lambda: EPFactor(),
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# 情绪
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"news_sent_5": lambda: NewsSentimentFactor(window=5),
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"news_sent_20": lambda: NewsSentimentFactor(window=20),
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"news_conf_5": lambda: SentimentConfidenceFactor(window=5),
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"sent_delta_5": lambda: SentimentMomentumFactor(period=5),
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}
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# ── 分类映射 ──────────────────────────────────────────────
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FACTOR_CATEGORIES: dict[str, list[str]] = {
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"动量": ["momentum_5", "momentum_10", "momentum_20", "momentum_60"],
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"RSI": ["rsi_7", "rsi_14"],
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"MACD": ["macd", "macd_5_35_5"],
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"量价": ["vol_ratio_5", "vol_ratio_20", "vol_chg_5"],
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"布林": ["boll", "boll_width"],
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"ATR": ["atr_14", "atr_ratio_14"],
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"均线": ["ma_cross_5_20", "ma_cross_10_60", "ma_dev_20", "ma_dev_60"],
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"波动率": ["volatility_20", "volatility_60", "down_vol_20"],
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"换手率": ["turnover_5", "turnover_chg_5"],
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"振幅": ["amplitude_5", "amplitude_20"],
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"基本面": ["roe", "pe", "pb", "ep"],
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"情绪": ["news_sent_5", "news_sent_20", "news_conf_5", "sent_delta_5"],
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}
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def get_factor(name: str, **overrides) -> BaseFactor:
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"""按名称获取因子实例。
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参数:
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name: 因子名称（如 'momentum_20'）
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**overrides: 覆盖默认参数
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返回:
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BaseFactor 实例
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说明: 返回实例的 .name 恒等于注册键 name，即使构造器默认生成的
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.name 与注册键不同（如 boll 的构造器默认 .name='boll_20'）——
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注册键是列名的唯一事实源，避免 FactorEngine.compute 的列名漂移。
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"""
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if name not in _BUILTIN_FACTORIES:
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raise KeyError(f"未知因子: '{name}'。可用: {list(_BUILTIN_FACTORIES)}")
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factor = _BUILTIN_FACTORIES[name]()
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if overrides:
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for k, v in overrides.items():
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if hasattr(factor, k):
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setattr(factor, k, v)
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# 无论是否覆盖参数，都强制 .name = 注册键，保证与分类/策略的引用一致
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if hasattr(factor, "name"):
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factor.name = name
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return factor
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def list_factors(category: str | None = None) -> list[str]:
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"""列出所有可用因子名称。"""
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if category and category in FACTOR_CATEGORIES:
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return FACTOR_CATEGORIES[category]
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return list(_BUILTIN_FACTORIES)
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def list_categories() -> list[str]:
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"""列出所有因子分类。"""
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return list(FACTOR_CATEGORIES)
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