Faslnāmah-i Pizhūhish/Nāmah-i Iqtisādī (Sep 2009)
The Study of Accounting Variable Power for Forecasting of Arbitrage Pricing Model’s Risks
Abstract
According to the Arbitrage Pricing Theory (APT) actual returns depend on a variety of pervasive economic and financial risk factors ; as well as firm or industry specific influences. The sensitivity of an asset’s returns to unanticipated changes in the perspective risk factors reflects the security’s measure of systematic risk. In equilibrium, the expected security return is a linear function of the sensitivities of actual security returns to unanticipated changes in the pervasive risk factors. The APT does not specify the number or the nature. Factor analysis of stock returns can be used to determine sensitivities of individual securities to pervasive risk factors without having to identify these risk factors. In this paper, we imperially tested following question; ‘Can we used traditional accounting risk measures from the current period to explain cross-sectional variations of the APT risk measures (sensitivities) in the next period? The empirical analysis was carried out using a sample include 42 firms from Tehran Stock Exchange and covered 1999-2005. The dependent variables were the APT risk measures, derived from principal factor analysis of monthly stock returns. The set of independent variables was an extensive list of traditional accounting risk measures associated with a firm’s operating and financial activities. The accounting risk measures used in this study represented the firm’s liquidity, dept management, profitability and efficiency, business risk and market value (hybrid ratio), as well as the size of the company. Relying on predictive correlation and multiple regression analysis and application of panel data models, an association was established between independent and dependent variables. the model significance was tested by F statisticand observed significant association in case of accounting variables. Traditional accounting variables some deal can explain cross-sectional variations of the APT risk measures in next period.