Security Market Data Research Articles

Conducting Long-Run Event Studies in Asia-Pacific Security Markets

This paper investigates the robustness of existing long-run event study methodologies using the Asia-Pacific security market data. In doing so, the study employs the buy-and-hold abnormal return approach and the calendar time portfolio method to measure the return anomalies. Since each of these two widely used approaches has a number of potential pitfalls, we also use standardized calendar time approach (SCTA) of Dutta (2015). The empirical analysis shows that all the employed methods are effective in the selected Asia-Pacific security markets. Simulations also show that SCTA documents better specification and power than the conventional methodologies.

Tests of the Consumption-Based Capital Asset Pricing Model Using Korean Security Market Data

Tests of the Consumption-Based Capital Asset Pricing Model Using Korean Security Market Data

Discussions on Securities Software Expert System MA and RSI

Based on the public and actual massive data of securities market, through testing the MA and RSI expert system of securities trading software by simulation experiment method, with the winning percentage, the annual rate of return, and the net profit margin as the management objectives, and with the theory of mathematical statistics as the research basis, the article carried out the comparative analysis of strength and weakness of these two systems. Except the annual transaction number, RSI expert system is comprehensively superior to MA expert system.

Can consumption-based asset pricing models explain the cross-section of investment funds returns?

Using the parametric Generalized Method of Moments (GMM) methodology of Hansen (1982 Hansen, LP. 1982. Large sample properties of generalized method of moments estimators. Econometrica, 50: 1029–54. [Crossref], [Web of Science ®] , [Google Scholar]) and the nonparametric approach of Hansen and Jagannathan (1991 Hansen, LP and Jagannathan, R. 1991. Implications of security market data for models of dynamic economies. Journal of Political Economy, 99: 225–62. [Crossref], [Web of Science ®] , [Google Scholar]), this note investigates the ability of Consumption-based Asset Pricing Models (CCAPMs) to explain the cross-section of investment funds returns in the German market. The parametric analysis shows that both the classic power utility model of Hansen and Singleton (1982 Hansen, LP and Singleton, KJ. 1982. Generalized instrumental variables estimation of nonlinear rational expectations models. Econometrica, 50: 1269–86. [Crossref], [Web of Science ®] , [Google Scholar]) and the habit formation extension of Campbell and Cochrane (1999 Campbell, JY and Cochrane, JH. 1999. By force of habit: a consumption-based explanation of aggregate stock market behavior. Journal of Political Economy, 107: 205–51. [Crossref], [Web of Science ®] , [Google Scholar]) are not rejected, but require high risk-aversion to be consistent with the data. Furthermore, only the power utility model suffers from a risk-free rate puzzle. The nonparametric results are not accompanied by a risk-free rate puzzle for both models but the models still show high risk aversion. So using adequate test assets and evaluation methods, this note fully supports Cochrane (2006 Cochrane, JH. 2006. “Financial markets and the real economy”. In Financial Markets and the Real Economy, Edited by: Cochrane, JH. XI–LXIX. London: Edward Elgar. [Google Scholar]) saying that work explaining asset returns with consumption-based models should be dying out since there are preferences that can coherently describe the data with high risk-aversion.

Conducting event studies with Asia-Pacific security market data

We investigate the effectiveness of several well-known parametric and non-parametric event study test statistics with security price data from the major Asia-Pacific security markets. Extensive Monte Carlo simulation experiments with actual daily security returns data reveal that the parametric test statistics are prone to misspecification with Asia-Pacific returns data. Two non-parametric tests, a rank test [Corrado and Zivney (Corrado, C.J., Zivney, T.L., 1992, The specification and power of the sign test in event study hypothesis tests using daily stock returns, Journal of Financial and Quantitative Analysis 27(3), 465-478)] and a sign test [Cowan (Cowan, A.R., 1992, Non-parametric event study tests, Review of Quantitative Finance and Accounting 1(4), 343–358)] were the best performers overall with market model excess returns computed using an equal weight index.

Conducting Event Studies With Asia-Pacific Security Market Data

We investigate the effectiveness of several well-known parametric and nonparametric event study test statistics with security price data from the major Asia-Pacific security markets. Extensive Monte Carlo simulation experiments with actual daily security returns data reveal that the parametric test statistics are prone to misspecification with Asia-Pacific returns data. Two nonparametric tests, a rank test [Corrado and Zivney (1993)] and a sign test [Cowan (1992)] performed the best overall with market model excess returns computed using an equal weight index.

An empirical investigation of asset pricing models using Japanese stock market data

This article examines the empirical performance of the following asset pricing models: (i) a time-separable model; (ii) Abel's model with a consumption externality; (iii) the time non-separable model; (iv) the consumption-based recursive utility model; and (v) the ad-hoc factor pricing model. The testing framework includes the Hansen-Jagannathan volatility bounds test, the Hansen-Jagannathan specification error test and Euler equation-based generalized method of moments estimation. The test evidence indicates that habit forming preferences are empirically supportable and provide a good characterization of the Japanese security market data.

Implications of Security Market Data for Models of Dynamic Economies

We show how to use security market data to restrict the admissible region for means and standard deviations of intertemporal marginal rates of substitution (IMRSs) of consumers. Our approach (i) is nonparametric and applies to a rich class of models of dynamic economies, (ii) characterizes the duality between the mean--standard deviation frontier for IMRSs and the familiear mean- standard deviation frontier for asset returns, and (iii) exploits the restriction that IMRSs are positive random variables. The region provides a convenient summary of the sense in which asset market data are anaomalous from the vantage point of intertemporal asset pricing theory.