## What are Factor Models?

Factor Models are financial models that incorporate factors (macroeconomic, fundamental and statistical) to determine the market equilibrium and calculate the required rate of return. Such models associate the return of a security to single or multiple risk factors in a linear model and can be used as alternatives to Modern Portfolio Theory.

Below are some of the functions related to factor models

- Maximization of the excess return i.e., Alpha (α) (to be dealt in the later part of this article) of the portfolio.
- Minimization of the volatility of the portfolio i.e., the Beta (β) of the portfolio.
- Ensure sufficient diversification to cancel out the firm-specific risk.

### Types of Factor Model

There are primarily two types of factor models –

- Single Factor
- Multiple Factor

#### #1 – Single Factor Model

The most common application of this model is the Capital Asset Pricing Model (CAPM).

The CAPM is a model that precisely communicates the relationship between the systematic risk and expected return of the stocks. It calculates the required return based on the risk measurement. To do this, it relies on a risk multiplier called the Beta coefficient (β).

##### Formula/structure

**E(R)**

_{i }= R_{f}+ β(E(R_{m})- R_{f})Where** E(R) _{I}** is the Expected return of investment

**R**is the Risk-Free Rate of Return defined is a theoretical rate of return with zero risks._{f }**β**is the Beta of the Investment that represents the volatility of the investment as compared to the overall market**E(R**is the Expected return of the market_{m})**E(R**is the Market Risk Premium._{m})- R_{f}

##### Example

Consider the following example:

The Beta of a particular stock is 2.The market return is 8%, Risk-free rate 4%.

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The Expected return as per the above formula would be:

- Expected return E(R)
_{i}= 4+2(8-4) **= 12%**

The CAPM is a simple model and is most commonly used in the finance industry. It is used in the calculation of the Weighted Average Cost of Capital/ Cost of equity.

But this model is based on a few slightly unreasonable assumptions such as ‘the riskier the investment, the higher the return’ which might not be necessarily true in all the scenarios, an assumption that historical data accurately predicts the future performance of the asset/stocks, etc.

And, what if there are many factors and not just one which determines the rate of return? Hence, we move on to the financial Models and discuss such models in depth.

#### #2 – Multiple Factor Model

Multiple factor models are adjunctions to single financial models. **Arbitrage Pricing Theory** is one of its predominant application.

##### Formula/structure

**R**

_{s,t }= R_{f }+α+ β_{1}×F_{1,t}+ β_{2}×F_{2,t }+ β_{3}×F_{3,t}+ …….β_{n}×F_{n,t}+ ĚWhere **R _{s,t}** is the Return of security s at Time t

**R**is the Risk-Free Rate of Return_{f }**α**is the Alpha of the security -Alpha is the constant term of the factor model. It represents the excess return of the investment relative to the return of the benchmark index. It is the value by which the investment outperforms the index. Higher the alpha, the better it is for investors**F**are the factors – Macroeconomic factors like exchange rate, Inflation rate, Foreign Institutional Investors, GDP, etc. Fundamental factors P/E ratio, Market capitalization, etc._{1,t}, F_{2,t}, F_{3,t }**β**are the factor loadings. – The factor loadings, also known as component loadings, are coefficients of the factors as mentioned above. For example, Beta calculation assists the investors to analyze the magnitude by which a stock moves in relation to change in the market._{1}, β_{2}, β_{3}**Ě**represents the error term – The equation contains an error term which is used to give further precision to the calculation. It can be sometimes used to define the security specific news that becomes available to the investors.

##### Example

Consider the following example:

Assume the Risk-free Rate of Return to be 4%.

The Return as calculated for the above example using factor Model is as follows:

- R= R
_{f }+ β_{1}×F_{1,t}+ β_{2}×F_{2,t }+ Ě - = 4% + 0.6(5) + 0.54(8)
**= 11.32%**

The arbitrage pricing theory being one of the common types of Financial models is based on the following assumptions:

- Asset returns can be described by a linear factor model
- Asset/Firm-specific risk shall possibly be eliminated by diversification.
- No further arbitrage opportunity exists.

### Advantages

This model allows professionals to

- Understand risk exposures of equity, fixed income, and other asset class returns.
- Ensure that an investor’s aggregate portfolio meets his risk appetite and return expectations.
- Build Portfolios that obtain a consistent result or remodel according to the characteristics of a particular index.
- Estimate cost of equity capital for valuation
- Manage Risk and hedge.

### Disadvantages/Limitations

- It is hard to decide how many factors to include in a model.
- Interpretation of the meaning of the factors is subjective.
- Selecting a good set of questions is complicated, and different researchers will choose different sets of questions.
- An improper inquiry might lead to complicated outcomes.

### Recommended Articles

This has been a guide to what are Factor Models and its definition. Here we discuss the types of factor models in finance including single and multi-factor models along with examples and explanation. You can learn more about Finance from the following articles –