Multiple factor models
What are multiple factor models?
Financial models that uses two or more uncertain variables to calculate the impact of different factors on returns from an individual security or investment portfolio.
Where have you heard about multiple factor models?
Financial analysts use them to estimate risks and returns when valuing assets.
What you need to know about multiple factor models.
Multiple factor models assume that there are a number of systemic variables that may affect the returns from a security or portfolio. These risk factors are non-diversifiable and affect all assets, so an investor is unable to avoid them simply by diversifying their portfolio.
There are three types of multiple factor model:
- Macroeconomic models consider variables such as GDP, inflation or interest rates
- Fundamental models look at the relationship between a security’s return and financial data such as P/E ratio or earnings growth rate
- Statistical models use regression analysis to compare the returns of securities based on historical data
Multiple factor models are often considered more realistic than single-factor models, which only incorporate one cause of uncertainty. As models are based on historical data, they may not accurately predict future returns.