Cheng F. Lee

Does Trading Volume Contain Information to Predict Stock Returns? Evidence from China's Stock Markets

This paper examines empirical contemporaneous and causal relationships between trading volume, stock returns and return volatility in Chinas four stock exchanges and across these markets. We find that trading volume does not Granger-cause stock market returns on each of the markets. As for the cross-market causal relationship in Chinas stock markets, there is evidence of a feedback relationship in returns between Shanghai A and Shenzhen B stocks, and between Shanghai B and Shenzhen B stocks. Shanghai B return helps predict the return of Shenzhen A stocks. Shanghai A volume Granger-causes return of Shenzhen B. Shenzhen B volume helps predict the return of Shanghai B stocks. This paper also investigates the causal relationship among these three variables between Chinas stock markets and the US stock market and between China and Hong Kong. We find that US return helps predict returns of Shanghai A and Shanghai B stocks. US and Hong Kong volumes do not Granger-cause either return or volatility in Chinas stock markets. In short, information contained in returns, volatility, and volume from financial markets in the US and Hong Kong has very weak predictive power for Chinese financial market variables.

A Further Empirical Investigation of the Dividend Adjustment Process

Abstract This paper analyzes the dividend adjustment process in the presence of cost of adjustment and information uncertainty. It proposes an integrated model consistent with the practical decision process to characterize the dividend adjustment process. It is analytically demonstrated that the residual theory, partial adjustment and adaptive expectations models are all special cases of the integrated model specified in this paper. Marquardts non-linear regression method is adopted to estimate the parameters of the integrated model, using both quarterly and annual data of earnings and dividends from a randomly selected sample. Empirical results show that the integrated model better explains the firms dividend decision process.

The elasticity of substitution in urban housing production: A VES approach

Abstract Many of the models which have been developed to explain urban spatial structure and land-use patterns rest on the properties of production functions. Differing factor price ratios within urban areas, particularly land prices, result in capital-land ratios exemplified by high-rise apartments and single-family dwellings. The purpose of this paper is to explore a new functional form for the housing production function. Specifically, a variable elasticity of substitution production function is proposed and some preliminary empirical evidence is provided using data for single-family housing.

Functional Form, Skewness Effect, and the Risk-Return Relationship

In this paper, possible factors affecting the second-pass regression results in capital asset pricing are investigated in detail. First, the true functional form used to test the risk-return relation is determined by using Box and Coxs [2] generalized functional form technique. Secondly, Box and Coxs residual analysis and transformation technique are used to show the importance of the skewness effect in capital asset pricing. Finally, some other factors affecting the results of second-pass regression coefficient in capital asset pricing also are explored. From these analyses, it is found that the functional form, the skewness effect, and the change of market condition are the most important factors in affecting the empirical conclusions in testing the bias of composite performance measures and the risk-return relation.

Beta stability and tendency: An application of a variable mean response regression model

Abstract A Variable Mean Response Regression (VMRR) model is used to reexamine the stability and tendency of beta estimates. The analysis presented indicates that the VMRR model is a better model than the traditional fixed-coefficient regression model in investigating the beta stability and tendency. The mean square error criteria is also used to show that the beta estimates obtained from the VMRR model are generally more appropriate for forecasting the future betas than those obtained from the fixed-coefficient regression model.

The Heterogeneous Investment Horizon and the Capital Asset Pricing Model: Theory and Implications

This paper generalizes the risk-return relationship implied by the traditional capital asset pricing model with finite investment horizons. It examines the effect of heterogeneous investment horizons on the functional form of capital asset pricing and proposes a translog model for estimating the risk-return relationship. In addition, this paper contends that some empirical findings that are inconsistent with the traditional CAPM have resulted from misspecification of the CAPM by ignoring the discrepancy between the observed data periods and the true investment horizons. Finally, the paper shows that under various conditions, the translog model is a suitable function for estimating the relationship between risk and expected returns.

Structural shifts in urban population density gradients: An empirical investigation

Abstract This study investigates the structural shifts in urban population density gradients by first using the shifting regression technique of Farley, Hinich, and McGuire to detect the possible change in the structure of an urban area. Secondly, a generalized random coefficient technique is used to simultaneously detect the possible structural change and stochastic behavior of density gradients. Data for 50 United States SMSAs are used to do the empirical analyses.

Forecasting bank failures and deposit insurance premium

Abstract Logistic regressions are performed to estimate the probability of bank failure. The in-sample logistic regression analysis indicates that the higher the equity capital, profitability, or liquidity, the lower the probability of bank failure. On the negative side, the ratio of past due loans to total asset is the most stable factor contributing to bank failures over the sample period. Other failure contributing factors change over time. In addition, a numerical illustration is provided to calculate the actuarial fair deposit insurance premiums.

A multivariate test of the covariance-co-skewness restriction for the three moment CAPM

Abstract This paper re-examines the importance of co-skewness in asset pricing using the multivariate testing procedure proposed by Gibbons (1982). This new approach allows for the testing of a share restriction derived from the Kraus and Litzenberger (1976) model which has been ignored in previous empirical studies. The results indicate that co-skewness is statistically significant in pricing risky assets and that the covariance risk is much more important in explaining the risk-return relationship than the co-skewness risk. However, the results also indicate that the Kraus and Litzenberger model does not adequately describe expected returns.

Time-Series Properties of Financial Series and Implications for Modeling

This paper investigates the time-series properties of a wide range of corporate financial and accounting series. Unit root tests developed by Dickey and Fuller (1979) are applied to these series. The results support the hypothesis that most of these series contain both permanent (random walk) and transitory components. The results show that most financial series are dominated by a random walk component. However, for some series, such as net sales, net income, earnings per share, and returns on investments, there is a relatively significant stationary component, which suggests the presence of successful smoothing for these series. We show that smoothing may reduce volatility of financial series but it cannot produce a deterministic growth trend. Implications of nonstationarity for financial modeling are explored.