Equity portfolio management problems require fund managers to make decisions about what portfolio to hold (ex ante) without knowing what future equity returns will be. Though these returns are uncertain, market participants try to understand the nature of the uncertainty and make decisions based on their beliefs about the market environment.

Traditionally, portfolio managers have used variants of the Markowitz Mean Variance Analysis to determine the optimal portfolio to hold, and this is still fairly standard practise in industry. Mean variance portfolio decision models fall into the more general group of mean risk models, where portfolio risk and expected return are traded off when making asset choices. Variance and standard deviation both measure the spread of a distribution about its mean. Since the variance of a portfolio can be easily calculated from covariances of the pairs of asset returns and asset weights used in the portfolio, variance is predominantly used in portfolio formation.

In contrast to computing asset variances and covariances directly using historical data, multifactor models provide an accurate and efficient way to provide these estimates. They decompose an asset's return into returns derived from exposure to common factors and an asset-specific component. The common factors can be understood as representing different risk (uncertainty) aspects, which all the assets are exposed to in varying degrees (factor sensitivities). ...

Get The Handbook of News Analytics in Finance now with O’Reilly online learning.

O’Reilly members experience live online training, plus books, videos, and digital content from 200+ publishers.