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This paper demonstrates an application of the Arbitrage Pricing Theory using canonical analysis as an alternative to the conventional factor analysis. Following the traditional view that asset prices are influenced by unanticipated economic events, the systematic effects of the major composite economic indices on a wide spectrum of industry returns are explored. The main conclusion is that profitability may be considered as the single most important factor that influences security returns. Also, the composite lagging economic indicators appear to be more useful to investors in forming market expectations than the composite leading economic indicators. Finally, it is argued that the composite index of coincident economic indicators do not exhibit any significant influence in the pricing of capital assets.

The purpose of this paper is to investigate the strategy that a turnaround in the USA will portend a turnaround in the UK's economy and property market. For this strategy to operate, it is assumed that the capital and property markets in and between the two nations are highly integrated with endogenous pricing functions.

Given the endogenous assumptions of the conjectured research statement, tests of integration (or segmentation) between two capital and property markets are conducted. Correlation, tracking error analysis, and a multiple systematic risk factor model are used to test the pricing relationships. The methodological form employs variant macroeconomic variable pricing models (MVM) of alternative combinations of systematic affects operating across and between the national markets.

Pricing integration is noted between the UK and US capital markets, while the property markets are economically and statistically segmented. Opportunities for arbitrage based on different prices/returns for equivalent risk exposures are statistically observed between the UK and USA. The effect is that systematic pricing between the two markets cannot be addressed solely by diversification options. This infers a potential for arbitrage (statistically, strategically or in practice) is possible, given that systematic risk exposures between the two markets are not equivalently priced across cyclical phases. In this context it is inferred that the probable measure of pricing differences across the two markets is more than a cyclical lag effect.

The paper delineates the degrees of integration/segmentation in the UK and US property and capital markets as a function of systematic risks in changing economic conditions. These differences support the existence of statistical arbitrage and the specification of investment behaviour as a function of differencing pricing expectations. These findings can assist in the formulation of investment and hedging strategies to assist in managing international portfolios subject to cyclical market exposures. This paper contributes to an understanding of and foundation for testing the nature and impact of cycles on property investment performance as a function of pricing changes.

This study explores the nature of the spot foreign exchange risk premium. Employing Ross's Arbitrage Pricing Theory (APT) as a vehicle, it tests the hypothesis that cross‐sectional differences in pure currency returns depend on measures of systematic (covariance) risk. These tests have greater power, in the sense of an enhanced ability to reject the hypothesis, since they explicitly allow for the possibility that idiosyncratic risk is priced. A battery of tests is unable to reject the hypothesis that expected exchange returns can be explained by a single‐factor APT. One implication of these results is that official intervention in exchange markets is unnecessary and undesirable.

This paper presents a new research design to test the efficacy of the Arbitrage Pricing Theory of Ross [1976], similar to that applied by Christofi, Christofi and Philippatos [1993]. In particular, we use a combination of factor analysis and canonical correlation to test the underlying relationships between APT factors developed using factor analysis and unanticipated changes in five macro‐economic variables that have been shown to be related to stock returns. The results of this paper indicate that the first factor of industry returns is strongly related to the S&P 500 while the remaining four factors are highly correlated with the term structure of interest rates, the rate of inflation, the default premium, and the industrial production, respectively.

This essay provides a non‐technical account of the development of thinking about the ways in which financial markets work. The account is organized by distinguishing between the “financial approach” and the “monetary approach” to the study of financial markets. The financial approach emphasizes the importance of arbitrage in determining financial asset prices. The monetary approach utilizes the more traditional tools of supply and demand, and places greater emphasis on the role of market imperfections. The essay evaluates the contribution of each approach to improving our understanding of financial markets. It concludes that the central problem in financial market research remains that of providing a satisfactory explanation of the determination of asset prices. In the emerging regime of liberalized, competitive financial markets both the financial approach and the monetary approach have a distinctive contribution to make in understanding how these markets work. This paper is based on research funded by the Economic and Social Research Council under grant No. B0023‐2151.

The purpose of this paper is to propose a new and improved version of arbitrage pricing theory (APT), namely, downside APT (D-APT) using the concepts of factors’ downside beta and semi-variance.

This study includes 163 stocks traded on the Malaysian stock market and uses eight macroeconomic variables as the dependent and independent variables to investigate the relationship between the adjusted returns and the downside factors’ betas over the whole period 1990-2010, and sub-periods 1990-1998 and 1999-2010. It proposes a new version of the APT, namely, the D-APT to replace two deficient measures of factor's beta and variance with more efficient measures of factors’ downside betas and semi-variance to improve and dispel the APT deficiency.

The paper finds that the pricing restrictions of the D-APT, in the context of an unrestricted linear factor model, cannot be rejected over the sample period. This means that all of the identified factors are able to price stock returns in the D-APT model. The robustness control model supports the results reported for the D-APT as well. In addition, all of the empirical tests provide support the D-APT as a new asset pricing model, especially during a crisis.

It may be worthwhile explaining the autocorrelation limitation between variables when applying the D-APT.

The framework can be useful to investors, portfolio managers, and economists in predicting expected stock returns driven by macroeconomic and financial variables. Moreover, the results are important to corporate managers who undertake the cost of capital computations, fund managers who make investment decisions and, investors who assess the performance of managed funds.

This paper is the first study to apply the concepts of semi-variance and downside beta in the conventional APT model to propose a new model, namely, the D-APT.

This paper proposes a discrete time real options model with time‐dependent and serial correlated return process for a real estate development problem with waiting options. Based on a Martingale condition, the paper claims to be able to relax many unrealistic assumptions made in the typical real option pricing methodology. Our real option model is a new one without assuming the return process as “Ito Process”, specifically, without assuming a geometric Brownian motion. We apply the model to the condominium market in Tokyo metropolitan area in the period 1971‐1997 and estimate the value of waiting to invest in 1998‐2007. The results partly provide realistic estimates of the parameters and show the applicability of our model.

The purpose of this paper is to generalize the one‐factor mortgage‐backed securities (MBS)‐pricing model proposed by Kariya and Kobayashi to a three‐factor model. The authors describe prepayment behavior due to refinancing and rising housing prices by discrete‐time, no‐arbitrage pricing theory, making an association between prepayment behavior and cash flow patterns.

The structure, rationality and potential for practical use of our model is demonstrated by valuing an MBS via Monte Carlo simulation and then conducting a comparative static analysis.

The proposed model is found to be effective for analysing MBS cash flow patterns, making a decision for bond investments and risk management due to prepayment.

While the one‐factor valuation model Kariya and Kobayashi treated is a basic framework, the generalized model presented in this paper is much more effective for analysing MBS cash flow patterns, making a decision for bond investments and risk management due to prepayment.