Quant Strategy Schools
Quantitative strategies organized by school: principles, trade-offs, code, references and regimes.
8 strategies
Cross-Sectional Momentum
Rank assets by past returns and hold recent winners while shorting recent losers.
🌦️ 板块/个股分化明显、动量效应持续的市场（风格轮动、行业景气分化、风险偏好趋势化）。
Market Making / High-Frequency
Quote on both sides, earn the spread — profits come from turnover and inventory control.
🌦️ 高流动性、低单边趋势、买卖价差丰厚的横盘市（大盘蓝筹、ETF、低波动品种）。
Mean Reversion (Bollinger / Z-Score)
Prices stretched too far tend to snap back to their average — buy the dip, fade the spike.
🌦️ 区间震荡、波动率收敛、价格围绕中枢稳定回归的市场（成熟蓝筹横盘、价差回归、低波动环境）。
Machine Learning Strategies
Let models learn non-linear patterns from data — powerful, but easy to overfit.
🌦️ 数据量大、模式稳定或可学习非线性结构、非制度突变的市场（中高频量价、跨资产融合）。
Multi-Factor Stock Selection
Score stocks on several factors (value, quality, momentum…) and hold the best-ranked basket.
🌦️ 基本面分化、因子溢价稳定、非极端情绪的市场（慢牛、价值/质量风格占优、低尾部风险）。
Options Volatility Strategies
Trade implied vs realized volatility rather than direction — events are your playing field.
🌦️ 波动率定价偏差明显、隐含波动率与实际波动率错配的市场（事件前后IV异常、期限结构扭曲）。
Statistical Arbitrage / Pairs Trading
Two historically co-moving assets: short the strong leg, buy the weak leg, profit when the spread closes.
🌦️ 两标的协整关系稳定、相关性高、价差均值回复的市场（指数ETF配对、同行业龙头、跨期价差）。
Trend Following (Dual MA / Turtle)
Follow the trend: buy strength, sell weakness, cut losses fast and let winners run.
🌦️ 单边趋势明确、波动率持续放大、鲜有频繁反转的市场（强牛/强熊、商品周期、宏观驱动行情）。