Statistical aspects of the portfolio construction programme

Belgorodski, A

Abstract

The area of finance poses many challenging problems to the decision maker. One of them
is the modelling of the expected return on stocks and the covariance matrix of returns.
This thesis approaches the decision problem of choosing an optimum portfolio of stocks
in which to invest from the point of view of statistical decision theory. We use regression
methods to predict the expected monthly return on stocks and the covariance matrix
between returns, the predictor variables being a company's 'fundamentals', such as
dividend yield and the history of previous returns. Predictions are evaluated out of
sample for shares traded on the London Stock Exchange from 1976 to 2005. Many
modelling and inferential approaches are examined and evaluated, the main ones being
shrinkage of regression coefficients, and transforming predictor variables to near
normality.
It is important to use suitable statistics to make a fair comparison of the out-of-sample
performance of rival methodologies. We review well-known measures of assessing
investment performance, including Sharpe, Sortino and Omega ratios, and derive a new
statistic from the exponential utility function. We also suggest a graphical aid which
could be used as a useful summary of investment performance.

Citation

Belgorodski, A. Statistical aspects of the portfolio construction programme. (Thesis). Salford : University of Salford

• Thesis Type: Thesis
• Deposit Date: Oct 3, 2012
• Award Date: Jan 1, 2007