Multi-Factor Model
What Is a Multi-Factor Model?
A multi-factor model is a financial model that utilizes multiple factors in its computations to explain market peculiarities or potentially equilibrium asset prices. A multi-factor model can be utilized to explain either an individual security or a portfolio of securities. It does as such by contrasting at least two factors with dissect relationships among factors and the subsequent performance.
Understanding a Multi-Factor Model
Multi-factor models are utilized to build portfolios with certain attributes, like risk, or to follow indexes. While building a multi-factor model, it is hard to conclude the number of and which factors to incorporate. Additionally, models are decided on historical numbers, which could not accurately foresee future values.
Multi-factor models likewise assist with explaining the weight of the various factors utilized in the models, showing which factor an affects the price of an asset.
Multi-Factor Model Formula
Factors are compared utilizing the following formula:
Ri = ai + _i(m) * Rm + _i(1) * F1 + _i(2) * F2 +...+_i(N) * FN + ei
Where:
Ri is the return of security
Rm is the market return
F(1, 2, 3 ... N) is every one of the factors utilized
_ is the beta with respect to each factor including the market (m)
e is the mistake term
a is the capture
Types of Multi-Factor Models
Multi-factor models can be separated into three categories: macroeconomic models, fundamental models, and statistical models.
Macroeconomic models: Macroeconomic models compare a security's return to such factors as employment, inflation, and interest.
Fundamental models: Fundamental models dissect the relationship between a security's return and its underlying financials, for example, earnings, market capitalization, and debt levels.
Statistical models: Statistical models are utilized to compare the returns of various securities in view of the statistical performance of every security all by itself. Ordinarily, historical data is utilized in this type of modeling.
Construction of Multi-Factor Models
The three most normally utilized models to build a multi-factor model are a combination model, a sequential model, and a diverse model.
Combination model: In a combination model, multiple single-factor models, which use a single factor to recognize stocks, are combined to make a multi-factor model. For instance, stocks might be arranged in light of momentum alone in the main pass. Subsequent passes will utilize different factors, for example, volatility, to order them.
Sequential model: A sequential model sorts stocks in light of a single factor in a sequential way to make a multi-factor model. For instance, stocks for a specific market capitalization might be sequentially examined for different factors, like value and momentum, sequentially.
Multifaceted model: In the diverse model, stocks are arranged in light of their crossing points for factors. For instance, stocks might be arranged and classified in light of convergences in value and momentum.
Measurement of Beta
The beta of a security measures the [systematic risk](/fundamental risk) of a security corresponding to the overall market. A beta of 1 demonstrates that the security hypothetically encounters similar degree of volatility as the market and moves in tandem with the market.
A beta greater than 1 shows the security is hypothetically more unpredictable than the market. On the other hand, a beta under 1 demonstrates the security is hypothetically less unstable than the market.
When multi-factor models are utilized by investment managers to survey the risk of investments, beta is an important factor that they can utilize.
Fama-French Three-Factor Model
One widely utilized multi-factor model is the Fama-French three-factor model. The Fama-French model has three factors: the size of firms, book-to-market values, and excess returns on the market. As such, the three factors utilized are SMB (small minus big), HML (high minus low), and the portfolio's return less the risk-free rate of return.
SMB accounts for public corporations with small market covers that generate higher returns, while HML accounts for value stocks with high book-to-market ratios that generate higher returns in comparison to the market.
Highlights
- The beta of a security measures the systematic risk of a security corresponding to the overall market.
- The Fama-French three-factor model is a notable tool that expands upon the capital asset pricing model, which centers exclusively around the market risk factor, by consolidating size and value factors.
- Multi-factor portfolios can be built utilizing different methods: interconnected, combinational, and sequential modeling.
- Multi-factor models uncover which factors generally affect the price of an asset.
- A multi-factor model is a financial modeling strategy wherein multiple factors are utilized to break down and explain asset prices.
