Multi-Factor Strategies

Combine multiple alpha sources for robust performance.

Overview

Multi-factor strategies diversify across different return drivers, reducing dependence on any single factor.

Strategies in This Section

Strategy	Description	Complexity
Classic Multi-Factor	Value + Momentum + Quality	Intermediate
Quality Factor	Profitability and stability	Basic
Factor Timing	Dynamic factor weights	Advanced
Custom Factors	Building your own	Advanced

Quick Example

Text Only

signal multi_factor:
  momentum = zscore(ret(prices, 60))
  value = zscore(book_to_market)
  quality = zscore(roe)

  emit 0.4 * momentum + 0.3 * value + 0.3 * quality

portfolio main:
  weights = rank(multi_factor).long_short(top=0.2, bottom=0.2)
  backtest from 2015-01-01 to 2024-12-31

Why Multi-Factor?

Single Factor	Multi-Factor
Can underperform for years	More consistent
Higher volatility	Diversified risk
Factor timing risk	Reduced timing dependency
Simpler	More robust

Expected Performance

Metric	Typical Range
Sharpe	0.6 - 1.0
Annual Return	6% - 12%
Max Drawdown	12% - 22%