Factor Investing 101: Using Value, Momentum, and Other Factors to Pick Stocks

Introduction

Factor investing organizes stocks by shared, measurable traits that have historically driven returns. These traits, or factors, include value, momentum, growth, quality, size, and low volatility, and they give you repeatable ways to think about stock selection beyond individual company stories.

Why should you care about factors? Because they help explain why some stocks outperform or lag the market over time, and they let you build rules-based screens and portfolios. Do you want a more systematic way to hunt for opportunities, or a tool to diversify sources of return?

This article explains the major factors, shows how to screen for them using common metrics, introduces smart-beta ETFs that package factors for you, and explains how to combine factors into a balanced strategy. You will get practical examples using real tickers and step by step guidance you can apply with your stock screener or brokerage tools.

Key Takeaways

• Factors are measurable characteristics like low price-to-earnings for value, multi-month price trends for momentum, or strong returns on equity for quality.
• Value, momentum, and size historically earned premiums, but each works in different market environments and can underperform for years.
• You can screen for factors with simple metrics: P/E or P/B for value, 6-12 month returns for momentum, ROE and low debt for quality, market cap for size, and standard deviation for low volatility.
• Smart-beta ETFs package factor exposures and simplify implementation, but they differ by index rules, rebalancing frequency, and factor definitions.
• Combining factors lowers single-factor risk, but you should manage turnover, transaction costs, and rebalance rules to avoid eroding returns.

What Are Investment Factors?

Investment factors are broad, persistent drivers of returns that apply across many stocks. They are not company-specific fundamentals or macro forecasts. Instead, factors capture cross-sectional differences in returns that recur over time.

Academics and practitioners typically split factors into two groups. Common factors explain risk premia like market, size, value, and momentum. Fundamental factors like quality or low volatility reflect firm characteristics that investors reward or penalize.

Why factors matter for you

Factors give you repeatable rules to find stocks that share desirable traits. If you invest based on a well-defined value screen, you avoid hunting low-quality bargains. If you use momentum, you follow price-based trends rather than trying to predict earnings surprises.

At the end of the day factors are tools, not guarantees. You should understand their historical behavior and which market environments favor each factor.

Core Factors Explained

This section breaks down the most widely used factors, the common metrics to measure them, and brief notes on historical performance patterns. Each factor description includes an actionable screen you can apply with a stock screener.

Value

Value captures stocks that are cheap relative to fundamentals. Common metrics are price-to-earnings P/E, price-to-book P/B, and enterprise value-to-EBITDA EV/EBITDA. Historically, value stocks have tended to outperform growth over long periods, though they can lag for extended cycles.

Practical screen: look for a trailing P/E in the lowest quintile of your universe or a P/B below 1.5. For US large caps, you might screen $AAPL, $MSFT and then identify those with unusually low P/E relative to sector peers.

Momentum

Momentum measures recent price performance. A standard definition is the total return over the past 6 to 12 months, excluding the most recent month to avoid short-term reversal. Momentum has strong empirical support but can crash when market sentiment reverses.

Practical screen: rank stocks by 12-month return, drop the last month, and pick the top decile. For example, you could rank returns for $TSLA, $NVDA, and $AMZN to see which show sustained upward trends.

Quality

Quality captures profitability, earnings stability, and sound balance sheets. Metrics include return on equity ROE, gross margins, accruals, and debt-to-equity. Quality tends to outperform during downturns and contributes to lower drawdowns.

Practical screen: require ROE above 15 percent, positive free cash flow for several years, and a debt-to-equity below the sector median. Stocks like $MSFT often score highly on quality metrics.

Size

Size is simply market capitalization. Small-cap stocks have historically produced higher average returns than large caps, although they come with higher volatility and liquidity risk.

Practical screen: define small caps as the bottom 20 percent of your investable universe by market cap. Be mindful that very small names can have wide bid-ask spreads and limited institutional interest.

Low Volatility

Low-volatility or minimum-volatility strategies favor stocks with lower historical price volatility. These stocks often produce better risk-adjusted returns and suffer smaller drawdowns, but their absolute returns can trail during strong bull markets.

Practical screen: sort stocks by trailing 1-year standard deviation of daily returns and select the lowest volatility quintile. Utilities and consumer staples often populate this list.

How to Screen for Factors

Stock screeners let you translate factor definitions into concrete filters. The key is to pick robust metrics, decide time horizons, and control for sector biases. You should also test on historical data before committing capital.

Step-by-step screening process

1. Define the universe, for example the S&P 500 or Russell 2000.
2. Choose the factor metric and look-back period, such as 12-month returns for momentum or trailing twelve-month P/E for value.
3. Apply sector-neutral filters if you want pure factor exposure. For example, compare P/E within sectors to avoid overweighting cheap cyclical sectors.
4. Rank the universe by the chosen metric and select the top or bottom percentile that fits your risk tolerance.
5. Backtest the screen over multiple market regimes and track turnover and transaction costs.

Example: screening for value in the S&P 500. Limit the universe to $SPY constituents, compute trailing P/E, then pick the 20 lowest P/E names. Next, check sector weights and apply sector caps to avoid concentration.

Smart-Beta ETFs and Factor Funds

Smart-beta ETFs offer ready-made factor exposures. They implement transparent index rules that tilt toward value, momentum, quality, or combinations. They remove stock-level research work but differ in methodology and costs.

Common smart-beta examples

Examples include single-factor ETFs and multi-factor ETFs. Single-factor funds track indices that rank stocks solely on one metric. Multi-factor funds combine metrics to smooth performance and reduce single-factor drawdowns.

Real tickers you might evaluate are $VLUE for a value ETF, $MTUM for momentum exposure, and $QUAL for quality. Multi-factor ETFs like $AOR or other providers offer blended exposures. Always read the index methodology to see how factors are defined and rebalanced.

What to watch in smart-beta ETFs

Pay attention to index construction, turnover, and tracking error. Some funds rebalance quarterly, others annually. Higher turnover can mean bigger tax and trading costs, which reduce net returns. Fees and liquidity matter too, especially for smaller factor ETFs.

Combining Factors: Diversification and Design

No single factor wins every market. Combining complementary factors can reduce volatility and improve risk-adjusted returns. For example, momentum can boost short-term gains while quality cushions drawdowns.

Simple combination approaches

1. Equal-weight blending, where you allocate equally to each factor sleeve or ETF.
2. Volatility scaling, which increases weight to lower-volatility factor sleeves to balance risk contributions.
3. Signal-based weighting, which adjusts exposures when factor signals strengthen or weaken based on rules.

Example allocation: split capital equally between a value ETF $VLUE, a momentum ETF $MTUM, and a quality ETF $QUAL. Rebalance quarterly and review turnover. This simple mix can smooth long-term returns compared with holding any single factor.

Implementation, Risks, and Practical Tips

Implementing factor strategies requires attention to turnover, taxes, and execution costs. Momentum strategies especially can generate high turnover. Value strategies can underperform for long stretches, requiring investor patience.

Practical tips

• Backtest across multiple decades and market regimes, not just recent years.
• Use sector-neutralization when screening to avoid unintended bets, unless you want sector exposure.
• Monitor turnover and rebalance on a schedule that balances responsiveness with trading costs.
• Consider smart-beta ETFs for simpler implementation if you prefer lower operational overhead.

Finally, combine factor analysis with fundamental checks. A low P/E can be a value trap if the company has deteriorating fundamentals. Use quality metrics as a secondary filter to avoid obvious pitfalls.

Real-World Examples

Example 1, pure value screen. Suppose you screen the S&P 500 for trailing P/E in the lowest 20 percent and apply a cap so no sector is above 30 percent weight. Over a 10-year backtest, you might see higher average returns than the benchmark but periods of multi-year underperformance during growth-led rallies.

Example 2, momentum plus quality. Rank Russell 1000 stocks by 12-month price return and require ROE above 10 percent. The combined screen can reduce the number of high-turnover momentum picks that lack profitability, lowering drawdowns during reversals.

Example 3, smart-beta ETF blend. An investor wanting a hands-off approach might split capital equally across $VLUE, $MTUM, and $QUAL, rebalance quarterly, and review performance annually. This approach reduces single-factor risk and keeps turnover manageable.

Common Mistakes to Avoid

• Chasing recent winners: Buying a factor after it has just outperformed often leads to buying at the end of the cycle. Avoid switching continually based on short-term performance.
• Ignoring sector concentration: Many factor screens naturally tilt to certain sectors. Use sector-neutral filters or caps to prevent unintended bets.
• Overfitting screens: Creating complex rules that only work in-sample will fail in live markets. Keep screens simple and test across multiple periods.
• Neglecting transaction costs and taxes: High-turnover factor strategies can lose edge once costs are included. Model realistic costs in your backtests.
• Relying on a single factor forever: Factors can fall out of favor. Combine complementary factors to reduce the chance of extended underperformance.

FAQ

Q: How long do I need to hold a factor strategy to expect it to work?

A: Factor premiums often materialize over multi-year horizons. Many studies suggest holding periods of 3 to 10 years to realize expected benefits, because factors can underperform in the short term.

Q: Can retail investors implement factor strategies with individual stocks?

A: Yes, retail investors can implement factor screens using stock screeners but should watch liquidity, diversification, and transaction costs. For lower operational overhead, smart-beta ETFs provide ready-made exposure.

Q: Do factors work in all markets and regions?

A: Factors show varying strength across regions and time. Value and momentum have been documented globally, but performance and implementation details differ by market. Test factors in the target market before deploying capital.

Q: Should I use fundamental or price-based factors?

A: Both have merits. Price-based factors like momentum capture market behavior while fundamental factors like value and quality capture company traits. Combining both types often yields more stable outcomes.

Bottom Line

Factor investing gives you a structured, repeatable way to select stocks and build portfolios. Value, momentum, quality, size, and low volatility each deliver different risk and return characteristics. You can screen for these factors using simple, well-defined metrics or use smart-beta ETFs to implement them at scale.

Before you deploy capital, backtest across multiple regimes, account for turnover and costs, and consider blending complementary factors to reduce single-factor risk. With a sound process and disciplined execution, factor investing can be a powerful addition to your toolkit, helping you pursue more consistent, explainable outcomes over the long run.