A Dynamic Asset Pricing Model for the S&P 500 Sector Indices: An Empirical Analysis on the Prices of Market Size Value Profitability and Investment Risk

Abstract

This thesis aims to determine how the prices of risk and their time dynamics for the market, size, value, profitability and investment risk factors explain the variation of expected excess returns on the S&P 500 Sector Indices from 2001 to 2019. The motivation for evaluating these factors is to improve our understanding of both the time series and cross-sectional drivers of asset prices. This is helpful to investors that apply factor-based asset allocation strategies, as it optimizes their knowledge about the risk exposures of the S&P 500 Sector Indices and assists them in predicting returns on these equity portfolios with better accuracy. We employ a three-step linear regression model including dynamic prices of risk and estimate the S&P 500 Sector Indices’ risk exposures, unconditional prices and time-varying contributors to the price of risk functions of each risk factor. With these estimated parameters, we forecast the one-year ahead expected excess returns for all sector indices. We find that the sector indices are generally exposed to market, size, value and profitability risk, yet not to investment risk. Additionally, we observe that the unconditional prices of market, value and investment risk significantly assist in explaining the variation of the excess returns of the S&P 500 Sector Indices, with 4.18%, -5.90% and 8.98% per annum respectively. Moreover, we find evidence for time-varying prices of size, profitability and investment risk. The dividend and 10-year Treasury yields appear to affect the level of the prices of size and profitability risk, whereas the earnings and dividend yields influence the price of investment risk. Last, we predict that the excess returns for all sector indices are lower than their respective historical averages in the period of December 2019 to November 2020.