Mathematical profile measuring the extent a portfolio of stocks is influenced by a range of economic factors such as changes in interest rates, inflation, and/or oil prices. There are several types of factor models, including a few proprietary ones, but they all are constructed using factor analysis techniques and can be divided into three basic categories: statistical, macroeconomic, and fundamental. Statistical factor models attempt to explain returns from an investment in terms of risk factors such as cash flow risk, currency risk, and purchasing power risk.

Macroeconomic factor models attempt to do the same in terms of factors that affect the economy as a whole. And fundamental factor models focus on economic factors that affect a particular industry or market.

A multi-factor model is a financial model that employs multiple factors in its calculations to explain market phenomena and/or equilibrium asset prices. The multi-factor model can be used to explain either an individual security or a portfolio of securities. It does so by comparing two or more factors to analyze relationships between variables and the resulting performance.

Multi-factor models are used to construct portfolios with certain characteristics, such as risk, or to track indexes. When constructing a multi-factor model, it is difficult to decide how many and which factors to include. Also, models are judged on historical numbers, which might not accurately predict future values.

### Categories of Multi-Factor Models

Multi-factor models can be divided into three categories: macroeconomic models, fundamental models and statistical models. Macroeconomic models compare a security’s return to such factors as employment, inflation and interest. Fundamental models analyze the relationship between a security’s return and its underlying financials, such as earnings. Statistical models are used to compare the returns of different securities based on the statistical performance of each security in and of itself.

### Beta

The beta of a security measures the systemic risk of the security in relation to the overall market. A beta of 1 indicates that the security theoretically experiences the same degree of volatility as the market and moves in tandem with the market. A beta greater than 1 indicates the security is theoretically more volatile than the market. Conversely, a beta less than 1 indicates the security is theoretically less volatile than the market.

### Multi-Factor Model Formula

Factors are compared using 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 i

**Rm** is the market return

**F**(1, 2, 3 … N) is each of the factors used

**_** is the beta with respect to each factor including the market (m)

**e** is the error term

**a** is the intercept

### Fama and French Three-Factor Model

One widely used multi-factor model is the Fama and French three-factor model. The Fama and French model has three factors: size of firms, book-to-market values and excess return on the market. In other words, the three factors used are SMB (small minus big), HML (high minus low) and the portfolio’s return less the risk free rate of return. SMB accounts for publicly traded companies with small market caps 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.

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