Factor Investing with Everon
Factor premia like Value, Momentum and Quality have been scientifically documented for decades. We explain what lies behind the factors, why they have historically delivered premia, and how Everon combines them in a systematic multifactor strategy.
Factor premia are among the best documented phenomena in modern finance. This article sheds light on the scientific background of Everon’s investment strategy: first the discovery of individual factors, then their concrete application in a portfolio. The focus is on equities, although individual factors can also be applied to other asset classes.
Factor premia, also known as factor investing, refer to additional returns that certain measurable stock characteristics have historically delivered beyond the broad market return. The best-known factors include Value, Size, Momentum and Quality. They rest on economic explanations and long empirical data series, but are time-varying and not a guarantee for future returns.
The essentials at a glance
- Origin: The Capital Asset Pricing Model (Sharpe 1964) explained returns only via market risk; empirically it proved too simple (Fama and French, 2004).
- Three-factor model: Fama and French (1992, 1993) added Size and Value to Market; Carhart (1997) added Momentum.
- Fundamental factors today: Value, Size, Momentum, Volatility, Dividend Yield and Quality rest on a solid research base (Bender et al., 2013).
- Time-varying: Factor premia occur irregularly; a factor can underperform the market for years. Historical premia are not a promise for the future.
- Combination beats single factor: Combining several factors in a portfolio can be more advantageous than investing in each factor individually (S&P Dow Jones Indices, 2018).
What are factor premia?
Factor premia are the portion of stock returns that cannot be explained by general market risk alone, but by systematic characteristics of individual stocks. A favorable valuation style (Value), a small market capitalization (Size) or relative price strength (Momentum) have historically delivered additional returns for which economic explanations exist.
The path there runs through a century of finance research. The Capital Asset Pricing Model (Sharpe 1964, Lintner 1965, Mossin 1966) attributed the expected excess return solely to systematic market risk. Ross (1976) generalized this in the Arbitrage Pricing Model to several factors, without naming them in economic terms. Fama and French (1992, 1993) provided the empirical foundation with the three-factor model (Market, Size, Value), which Carhart (1997) extended with Momentum.
Which factors are considered the best researched?
The best-researched factors today are the fundamental ones: Value (favorable valuation), Size (smaller companies), Momentum (recent relative price strength), Quality (stable, profitable companies), Volatility (less volatile stocks) and Dividend Yield. For each there is an economic rationale for why it has delivered a risk premium in the past (Bender et al., 2013).
Multifactor models can be divided into three groups: macroeconomic factors (for example inflation or interest rate surprises), statistical factors (for example principal component analysis) and fundamental factors, which rest on a company’s key figures. Everon’s strategy places its focus on the fundamental factors.
Do Value, Momentum and Quality still work today?
The economic foundation of the factors continues to hold, but factor premia are time-varying: a factor can lag the broad market for years before delivering a premium again. Value went through a pronounced weak phase in the 2010s before recovering. A historical premium is therefore never a promise for the future.
This has a direct consequence for portfolio construction. Because individual factors deliver at different times, combining several factors reduces dependence on the weak phase of any single one. This is why a multifactor strategy is generally preferred over a concentrated single-factor approach.
How does Everon combine the factors?
Classic factor models construct each factor individually and sort stocks separately by each characteristic. This can lead to conflicting signals: a stock might be a buy on Momentum but not on Quality. Everon addresses this by evaluating each stock simultaneously across all factors considered. Only stocks that rate positively across all factors are included in the portfolio.
Implementing a clean multifactor strategy on a single-stock basis is demanding, and often too costly, for private investors acting alone. Automated, systematic investment processes make it possible to implement this investment style efficiently. Here too, the same principle applies: factor investing manages risk systematically, but it does not eliminate the possibility of losses.
Frequently asked questions about factor premia
What are factor premia?
Factor premia are additional returns that certain scientifically described stock characteristics have historically delivered beyond the broad market, such as a favorable valuation style (Value) or relative price strength (Momentum). They rest on economic explanations and long data series. However, a historical premium is not a guarantee for the future. This does not constitute investment advice.
Do Value, Momentum and Quality still work today?
The economic foundation of these factors continues to hold, but factor premia are time-varying: a factor can lag the market for years before delivering premia again. Value, for example, went through a long weak phase in the 2010s. This is why factors are combined instead of relying on a single one. This does not constitute investment advice.
What is the advantage of a multifactor strategy?
Individual factors deliver their premia at different times and can offset one another. Combining several factors in a portfolio can dampen the risk of long weak phases in individual factors. Studies suggest that the combination can be advantageous compared with investing in each factor individually (S&P Dow Jones Indices, 2018). This does not constitute investment advice.
How does Everon implement factors?
Everon evaluates each stock simultaneously across all factors considered and only includes stocks that rate positively across the factors. This simultaneous evaluation avoids conflicting signals and is implemented through automated, systematic investment processes. This does not constitute investment advice.
References
- W. F. Sharpe. Capital asset prices: A theory of market equilibrium under conditions of risk. The Journal of Finance, 19(3):425–442, 1964.
- J. Lintner. Security prices, risk, and maximal gains from diversification. The Journal of Finance, 20(4):587–615, 1965.
- J. Mossin. Equilibrium in a capital asset market. Econometrica, 34(4):768–783, 1966.
- S. Ross. The arbitrage theory of capital asset pricing. Journal of Economic Theory, 13(3):341–360, 1976.
- E. F. Fama and K. R. French. The cross-section of expected stock returns. The Journal of Finance, 47(2):427–465, 1992.
- E. F. Fama and K. R. French. Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33(1):3–56, 1993.
- M. M. Carhart. On persistence in mutual fund performance. The Journal of Finance, 52(1):57–82, 1997.
- E. F. Fama and K. R. French. The capital asset pricing model: Theory and evidence. Journal of Economic Perspectives, 18(3):25–46, 2004.
- E. F. Fama and K. R. French. A five-factor asset pricing model. Journal of Financial Economics, 116(1):1–22, 2015.
- J. Bender et al. Foundations of Factor Investing. MSCI Research Insight, 2013.
- S&P Dow Jones Indices. The Merits and Methods of Multi-Factor Investing. 2018.
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This article is for general information purposes only and does not constitute investment advice or an offer to buy or sell financial instruments. Everon AG is a wealth manager licensed by FINMA under FinIA. Past performance is not a reliable indicator of future returns.
