OPTION PRICING AND THE ARBITRAGE PRICING THEORY

This paper applies the arbitrage pricing theory to option pricing. Under certain distribution assumptions or the assumption that there is only one common factor, the underlying asset of an option is the sole risky factor that explains its expected return. Based upon this relationship, a new and simple option-pricing formula is derived, and some important existing option-pricing formulae are reproduced. Empirical results show that the new formula performs as well as the Black-Scholes formula.     

THE PRICING OF FUTURES CONTRACTS AND THE ARBITRAGE PRICING THEORY

When interest rates are stochastic, the cash flows of futures and forward contracts differ because of the marking-to-market requirement of futures contracts. The price effect of this difference is examined here by applying the risk and return model of the arbitrage pricing theory. The resulting futures pricing equation is preference free, and is obtainable using other no-arbitrage approaches. The pricing equation suggests that the price difference is due to the covariance of spot asset returns and interest rates. An empirical study is conducted on the Major Market Index futures from October 1, 1984 to September 27, 1985. Results indicate that the covariance, extracted by the Kalman filter according to the pricing equation, is significant in the pricing of futures contracts.     

BOOTSTRAPPING THE NUMBER OF FACTORS IN THE ARBITRAGE PRICING THEORY

The number of factors in the APT are re-examined through a new methodology called the bootstrap, which provides a nonparametric alternative to the chi-square test used in prior research. Results suggest that the number of statistically significant factors does not increase when the number of firms increases. Moreover, only the first factor is consistently significant across sample sizes of thirty, sixty, and ninety firms.     

THE MAGNITUDE OF PRICING ERRORS IN THE ARBITRAGE PRICING THEORY

In this paper the arbitrage pricing theory (APT) pricing errors for individual securities are estimated employing maximum likelihood factor analysis and Fama-MacBeth style aggregation. Results show that the pricing errors are large and statistically significant and that there is a high degree of variability in pricing errors across securities. This evidence contradicts the prevailing APT intuition that the pricing errors can be ignored as negligible. Pricing errors are also found to be related to residual variance and firm size.     

AN EMPIRICAL TEST OF THE ARBITRAGE PRICING THEORY

This paper provides an ex-post analysis of a multifactor return-generating model using the factor scores obtained from a common factor analysis of industry-based portfolios. For the 1975–1980 time period, the correlations among common stock returns can be adequately explained by a three-factor model. Furthermore, ex post, at least three factors are priced in the stock market. A brief economic interpretation of the proposed common factor is also presented.     

ARBITRAGE PRICING MODELS: THE SUFFICIENT NUMBER OF FACTORS AND EQUILIBRIUM CONDITIONS

The typical methodology for estimating an Arbitrage Pricing Model is inadequate with respect to two issues. First, the statistical tests used to determine the sufficient number of factors are inappropriate and may actually overstate the relevant number of factors. Second, the methodology fails to determine whether the estimated model satisfies equilibrium conditions. A simple test that corrects both deficiencies is developed in this paper.     

MACRO-ECONOMIC FACTORS AND STOCK RETURNS

This paper explores the economic nature of return factors by incorporating a multifactor return generating process into the traditional CAPM. It attempts to remedy the arbitrage pricing theory, which is not capable of assigning proper economic meanings to return factors. There are at least three significant factors associated with general production, investment, financial, and employment variables. These economic factors explain the risk-return relationship as well as those obtained by the arbitrage pricing theory.     

THE ARBITRAGE PRICING THEORY AND COST-OF-CAPITAL ESTIMATION: THE CASE OF ELECTRIC UTILITIES

Capital asset pricing model (CAPM) and alternative arbitrage pricing theory (APT) methodologies are used to estimate the cost of capital for a sample of electric utilities. The statistical factors APT method is found to produce significantly different estimates depending on the number of factors specified and the set of firms factor analyzed. The use of macroeconomic factors is explored, and it is shown that this methodology has advantages over the statistical factors APT and the market model.     

AN ARBITRAGE PRICING APPROACH TO EVALUATING MUTUAL FUND PERFORMANCE

A test procedure, derived from arbitrage pricing theory, that permits the measurement of the security selection performance of professional portfolio managers is developed and applied to a sample of mutual funds over the period of the 1970's. The evidence indicates that more than one factor was present in the market during that interval as a systematic influence on the profile of securities returns. Consistent with prior studies, the evidence also suggests that mutual fund portfolios did not outperform a passive buy-and-hold investment strategy. A comparative analysis of the same data, using performance measures based on the single-factor market model, produces similar but less powerful results, both in the aggregate and at the individual fund level.