SystemTrader
StocksIntermediateLong-Only / Long-Short

Multifactor Portfolio Strategy

Combine multiple factors like value and momentum to harvest diversified risk premiums. Factors are often negatively correlated, providing powerful diversification benefits.

Factors
2-5 factors
Weighting
Equal or Vol-adjusted
Rebalance
Monthly/Quarterly
Holding
1-12 months

Overview

The multifactor portfolio strategy combines multiple return-predicting factors into a single diversified portfolio. Rather than betting on one factor, investors can harvest multiple risk premiums simultaneously.

A key insight: value and momentum are negatively correlated (-0.50 on average). When value underperforms, momentum often outperforms, and vice versa. Combining them smooths returns and reduces drawdowns.

The strategy works by ranking stocks on each factor separately, then combining these rankings into a single composite score. Stocks with the best combined scores are bought; those with the worst are shorted.

Key Insight

Factor Diversification
Multiple premiums, reduced risk
Negative Correlation
Value and momentum offset each other

Quadrants

Top-Right: High value + high momentum (BUY)
Mixed: Strong in one factor only
Bottom-Left: Low value + low momentum (AVOID)

Combined Score

Score = (V + M) / 2

Average of value rank and momentum rank. Select top decile.

Key Insight

Value and momentum are negatively correlated (-0.50). Combining them provides diversification: when value struggles, momentum often compensates.

Research

Key research on factor combination and multifactor portfolio construction.

Recent Research

The Mathematics

In Plain English

The math behind this strategy is straightforward. Here's what you're actually doing:

  1. 1
    Choose your factors: Pick 2-5 factors to combine (e.g., value, momentum, quality). Each factor should have academic backing and low correlation with others.
  2. 2
    Rank stocks on each factor: For each factor, sort all stocks from best to worst. Convert to percentile ranks (0-100) for comparability.
  3. 3
    Combine the rankings: Average each stock's ranks across all factors. The simplest approach: equal weight each factor.
  4. 4
    Select top combined scores: Buy stocks with the best average rank (top decile). Optionally short stocks with the worst average rank.

That's it. The formulas below just express this process precisely.

Technical Formulas

1
Factor Investment Allocation

Formula
I_A = w_A \times I \quad \text{where} \quad \sum_{A=1}^{F} w_A = 1

Total investment I is allocated across F factors with weights w_A. Each factor portfolio receives its weighted share.

2
Equal Factor Weights

Formula
w_A = \frac{1}{F}

The simplest approach: give each of F factors equal weight. For 3 factors, each gets 1/3 weight.

3
Volatility-Adjusted Weights

Formula
w_A \propto \frac{1}{\sigma_A} \quad \text{or} \quad w_A \propto \frac{1}{\sigma_A^2}

Weight factors inversely by their historical volatility. Lower-volatility factors get higher weights, improving risk-adjusted returns.

4
Demeaned Factor Rank

Formula
s_{Ai} = \text{rank}(f_{Ai}) - \frac{1}{N} \sum_{j=1}^{N} \text{rank}(f_{Aj})

Stock i's demeaned rank on factor A. Subtracting the mean rank centers scores around zero.

5
Combined Score

Formula
s_i = \frac{1}{F} \sum_{A=1}^{F} s_{Ai}

Average the demeaned ranks across all F factors to get a single composite score for each stock.

Why Combine Factors?Note

Individual factors have significant drawdowns and periods of underperformance. Combining negatively correlated factors (like value and momentum) smooths returns. When one factor struggles, another often compensates.

Strategy Rules

Factor Selection

  1. Choose 2-5 factors with strong academic backing
  2. Prioritize factors with low or negative correlations for diversification
  3. Common choices: Value (book-to-market), Momentum (12-1 month return), Quality (profitability)
  4. Additional factors: Size (market cap), Low Volatility, Investment (asset growth)
  5. Ensure data availability for all chosen factors

Scoring & Ranking

  1. 1Calculate raw factor values for each stock in your universe
  2. 2Value: book-to-market ratio (higher = cheaper)
  3. 3Momentum: past 12-month return, skip most recent month
  4. 4Quality: gross profit / total assets
  5. 5Convert raw scores to percentile ranks (0-100) for comparability
  6. 6Compute demeaned ranks by subtracting mean rank from each stock

Portfolio Construction

  1. Average percentile ranks across all factors for combined score
  2. Use equal weights (1/F) or volatility-adjusted weights
  3. Long: Buy stocks in top decile of combined scores
  4. Short (optional): Sell stocks in bottom decile
  5. Equal-weight positions or weight by inverse volatility
  6. Target 20-50 stocks for adequate diversification

Rebalancing

  1. 1Re-run full process monthly or quarterly
  2. 2Monthly rebalancing captures momentum better
  3. 3Quarterly rebalancing reduces turnover and costs
  4. 4Sell positions that drop out of top rankings
  5. 5Buy new stocks that enter top combined scores
  6. 6Monitor factor exposures to ensure balance is maintained

Implementation Guide

Building a multifactor portfolio requires calculating multiple metrics and combining them. Here's a practical approach for individual investors.

1

Define Your Factor Universe

Start with well-documented factors. A classic combination is Value + Momentum + Quality. Value: high book-to-market stocks. Momentum: best 12-month performers. Quality: high profitability (ROE or gross margins).

Tips
  • Start with just 2 factors (value + momentum) for simplicity
  • Ensure factors have low or negative correlation for diversification benefit
  • Use established factor definitions from academic literature
2

Gather Factor Data

You'll need fundamental data (for value/quality) and price data (for momentum). Free sources include Yahoo Finance, Finviz, and AAII. For book values and profitability, check company filings or use a screening tool.

Tips
  • Finviz provides P/B ratios (inverse of book-to-market) and performance metrics
  • Yahoo Finance has quarterly financials for profitability calculations
  • Consider a data service like Portfolio123 or AAII for easier screening
3

Calculate and Rank

For each factor, calculate the metric for every stock in your universe. Then rank from 1 to N (where N is the number of stocks). Convert to percentile ranks by dividing by N. A stock ranked 10th out of 500 has percentile rank 2%.

Tips
  • Use Excel or Google Sheets for ranking (RANK function)
  • Higher rank = better for momentum and quality; reverse for value (lower P/B is better)
  • Double-check that all factors are aligned so high rank = attractive

Make sure factor rankings are directionally aligned. For value, rank so LOW P/B (cheap) stocks get HIGH ranks.

4

Combine Scores

Average each stock's percentile ranks across all factors. If using 3 factors and a stock has ranks of 90, 70, and 80, its combined score is (90+70+80)/3 = 80. Select stocks with the highest combined scores.

Tips
  • Equal weighting is the standard academic approach
  • For volatility weighting, calculate each factor's historical volatility first
  • The top decile (top 10%) typically forms the long portfolio
5

Construct Portfolio

Buy the top 10-20 stocks by combined score. Equal-weight positions for simplicity. For a $50,000 portfolio with 20 stocks, that's $2,500 per position. Rebalance monthly or quarterly.

Tips
  • Keep position sizes reasonable (2-5% each) for diversification
  • Consider tax implications of monthly vs. quarterly rebalancing
  • Track factor exposures over time to ensure balance is maintained

Tools for Multifactor Investing

Building multifactor portfolios manually requires spreadsheet work. Alternatively, services like Portfolio123, Equities Lab, or Alpha Architect provide factor screening tools. Some robo-advisors and ETFs (like MTUM, VLUE, QUAL) offer single-factor exposure that can be combined.

Helpful Tools & Resources

Factor Screeners
Portfolio123, Equities Lab, AAII Stock Investor
Data Sources
Yahoo Finance, Finviz, Morningstar, SEC EDGAR
Factor ETFs
MTUM (momentum), VLUE (value), QUAL (quality), USMV (low vol)
Research
SSRN, Ken French Data Library, AQR Factor Data

Strategy Variations

Explore different ways to implement this strategy, each with its own trade-offs and benefits.

Value + Momentum

The classic two-factor combination. Value and momentum have -0.50 correlation, providing excellent diversification.

Three-Factor (Value + Momentum + Quality)

Adds profitability/quality factor. Quality is negatively correlated with value, further improving diversification.

Five-Factor Fama-French

Market, Size, Value, Profitability, Investment. The academic standard for explaining stock returns.

Volatility-Weighted Factors

Weight factors inversely by volatility. Reduces portfolio volatility while maintaining factor exposure.

Consider combining multiple variations or testing them against your specific investment goals and risk tolerance.

Risks & Limitations

High(1)
Medium(4)
Factor Timing RiskHigh

Individual factors can underperform for extended periods (value's 2010-2020 drawdown). Diversification helps but doesn't eliminate this risk.

Impact:
Implementation ComplexityMedium

Requires tracking multiple metrics and regular rebalancing. More complex than single-factor strategies.

Impact:
Data RequirementsMedium

Need reliable fundamental data (for value/quality) and price data (for momentum). Data errors can impact rankings.

Impact:
Factor DecayMedium

Some argue factors are arbitraged away over time as more investors exploit them. Factor premiums may be lower going forward.

Impact:
Correlation InstabilityMedium

Factor correlations can change during market stress. Value and momentum may become more correlated in crashes.

Impact:
Understanding these risks is essential for proper position sizing and portfolio construction. Consider combining with other strategies to mitigate individual risk factors.

References

  • Fama, E. F., & French, K. R. (1993). Common Risk Factors in the Returns on Stocks and Bonds. Journal of Financial Economics, 33(1), 3-56 [Link]
  • Asness, C. S., Moskowitz, T. J., & Pedersen, L. H. (2013). Value and Momentum Everywhere. Journal of Finance, 68(3), 929-985 [Link] [PDF]
  • Novy-Marx, R. (2013). The Other Side of Value: The Gross Profitability Premium. Journal of Financial Economics, 108(1), 1-28 [Link]
  • Frazzini, A., & Pedersen, L. H. (2014). Betting Against Beta. Journal of Financial Economics, 111(1), 1-25 [Link]
  • Fama, E. F., & French, K. R. (2015). A Five-Factor Asset Pricing Model. Journal of Financial Economics, 116(1), 1-22 [Link]
  • Israel, R., Laursen, K., & Richardson, S. (2021). Is (Systematic) Value Investing Dead?. Journal of Portfolio Management, 47(2) [Link]

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