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Stock Market Data (stock + market_data)
Selected AbstractsExcess Risk Premia of Asian BanksINTERNATIONAL REVIEW OF FINANCE, Issue 2 2000Jianping (J.P.) Mei This paper develops a framework for gauging the risks of emerging market banks by using stock market data. Employing a multifactor asset pricing model that allows for time-varying risk premia, we find the presence of large excess risk premia on Asian bank stocks, especially in those markets affected by the Asian financial crisis. We find that the excess risk premia appear to be negatively related to the degree of economic freedom of a country but positively related to its corruption level. Thus, our findings are consistent with the view that crony capitalism in Asia may have distorted the market mechanism or the systematic risk exposure of banks. This suggests that the excess risk premium provides useful information on risk exposure for opaque banking systems where quality accounting information is not available. [source] Measures of Fit for Rational Expectations ModelsJOURNAL OF ECONOMIC SURVEYS, Issue 3 2002Tom Engsted This survey provides a detailed description of some of the recent theoretical and empirical literature on rational expectations econometrics. The survey pays special attention to non,stationarity of the data, and to the various methods for evaluating rational expectations models that have been developed as alternatives to the classical statistical approach of testing overidentifying restrictions. These methods have become very popular and widely used in empirical research. We provide an illustration using Danish stock market data, and we summarize the many results obtained recently using these measures in areas as diverse as stock prices, the term structure of interest rates, exchange rates, consumption and saving, the balance of payments, tax,smoothing, hyperinflation, and linear quadratic adjustment cost models for inventories, labour demand, and money demand. [source] Market Efficiency and Return Statistics: Evidence from Real Estate and Stock Markets Using a Present-Value ApproachREAL ESTATE ECONOMICS, Issue 2 2001Yuming Fu This paper develops a methodology to identify asset price response to news in the framework of the Campbell,Shiller log-linear present-value equation. We further show that a slow price adjustment in real estate markets not only induces a high serial autocorrelation in excess returns, but also dampens the return volatility and the correlation with excess returns in other asset markets. Using Hong Kong real estate and stock market data, we find that the quarterly real estate price assimilates only about half the effect of market news, whereas the quarterly stock price incorporates the news fully. Our analysis identifies a cumulative price adjustment that recovers lost information in real estate returns due to market inefficiency and thereby restores the real estate return volatility and the correlation between real estate and stock markets. [source] Idiosyncratic and Common Shocks to Investment Decisions*THE ECONOMIC JOURNAL, Issue 482 2002Mark Schankerman We show how microeconomic data on investment plans can be used to study the structure of risk firms face. Revisions of investment plans form a martingale and reveal the underlying shocks driving investment. We decompose revisions in investment plans into micro, sector and aggregate shocks, and exploit stock market data to distinguish between structural (value-related) shocks and measurement error in investment revisions. Using panel data for US firms, we find that micro shocks are not the dominant source of risk in investment decisions, and that much of the observed micro variation is actually due to heterogeneity in firm-level responses to aggregate shocks. [source] Consumption, Aggregate Wealth, and Expected Stock ReturnsTHE JOURNAL OF FINANCE, Issue 3 2001Martin Lettau This paper studies the role of fluctuations in the aggregate consumption,wealth ratio for predicting stock returns. Using U.S. quarterly stock market data, we find that these fluctuations in the consumption,wealth ratio are strong predictors of both real stock returns and excess returns over a Treasury bill rate. We also find that this variable is a better forecaster of future returns at short and intermediate horizons than is the dividend yield, the dividend payout ratio, and several other popular forecasting variables. Why should the consumption,wealth ratio forecast asset returns? We show that a wide class of optimal models of consumer behavior imply that the log consumption,aggregate wealth (human capital plus asset holdings) ratio summarizes expected returns on aggregate wealth, or the market portfolio. Although this ratio is not observable, we provide assumptions under which its important predictive components for future asset returns may be xpressed in terms of observable variables, namely in terms of consumption, asset holdings and labor income. The framework implies that these variables are cointegrated, and that deviations from this shared trend summarize agents' expectations of future returns on the market portfolio. [source] Do Stock Prices and Volatility Jump?THE JOURNAL OF FINANCE, Issue 3 2004Option Prices, Reconciling Evidence from Spot This paper examines the empirical performance of jump diffusion models of stock price dynamics from joint options and stock markets data. The paper introduces a model with discontinuous correlated jumps in stock prices and stock price volatility, and with state-dependent arrival intensity. We discuss how to perform likelihood-based inference based upon joint options/returns data and present estimates of risk premiums for jump and volatility risks. The paper finds that while complex jump specifications add little explanatory power in fitting options data, these models fare better in fitting options and returns data simultaneously. [source] | ||||||||||||||||||||||