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In this paper, I aim to explore the effect of good governance on equity returns, and empirically investigate if governance at the country level has asset pricing implications and contributes to the idiosyncrasy of price jumps. Jumps are found to be far less systematic than the smooth (non-jump) component of country price indexes. Hence, if jumps are more idiosyncratic, governance should primarily affect the jump risk component. This is good news for international investors, because diversification provides insurance against jumps. Relying on an equilibrium asset-pricing model in an economy under jump diffusion, I decompose the moments of the returns of international stock markets into a diffusive (systematic) risk and a (idiosyncratic) jump risk part. For a balanced panel of 52 countries, my results suggest that governance is an important determinant of (idiosyncratic) jump risk. Stock markets in poorly governed countries are characterized by higher volatility and more negative return asymmetry, primarily driven by the higher jump risk. Regulatory quality, the government effectiveness and the control of corruption appear to be most important. Results are robust to the inclusion of various controls for other country- or market-specific characteristics. [ABSTRACT FROM AUTHOR]

In this paper, the problem of whether the left tail and the right tail of a distribution share the same extreme value index (EVI) is addressed and we propose two different test statistics. The first one is based on the result of the joint asymptotic normality of the two Hill estimators for the EVIs of both tails. And therefore, we can construct a quotient-type test statistic, which is asymptotic χ2(1) distributed after some standardization. The second test statistic proposed in this paper is inspired by the two-sample empirical likelihood methodology, and we prove its non parametric version of Wilk's theorem. At last, we compare the efficiencies of our two test statistics and the maximum likelihood (ML) ratio test statistic proposed by Jondeau and Rockinger (2003) in terms of empirical first type error and power through a number of simulation studies, which indicate that the performance of the ML ratio test statistic is worse than our two test statistics in most cases. [ABSTRACT FROM AUTHOR]

Using 5-minute high frequency data from the Chinese stock market, we employ a non-parametric method to estimate Fama-French portfolio realized jumps and investigate whether the estimated positive, negative and sign realized jumps could forecast or explain the cross-sectional stock returns. The Fama-MacBeth regression results show that not only have the realized jump components and the continuous volatility been compensated with risk premium, but also that the negative jump risk, the positive jump risk and the sign jump risk, to some extent, could explain the return of the stock portfolios. Therefore, we should pay high attention to the downside tail risk and the upside tail risk. [ABSTRACT FROM AUTHOR]

Using an agent-based model we examine the dynamics of stock price fluctuations and their rates of return in an artificial financial market composed of fundamentalist and chartist agents with and without confidence. We find that chartist agents who are confident generate higher price and rate of return volatilities than those who are not. We also find that kurtosis and skewness are lower in our simulation study of agents who are not confident. We show that the stock price and confidence index—both generated by our model—are cointegrated and that stock price affects confidence index but confidence index does not affect stock price. We next compare the results of our model with the S&P 500 index and its respective stock market confidence index using cointegration and Granger tests. As in our model, we find that stock prices drive their respective confidence indices, but that the opposite relationship, i.e., the assumption that confidence indices drive stock prices, is not significant. [ABSTRACT FROM AUTHOR]

There is not general support to explain the correlation among the macroeconomic variables and share returns in different countries and time. The unique characteristics of the Brazilian economy have changed deeply over the last years, thus the purpose of this study is to explore the correlation among the macroeconomic variables and share returns in Brazil from 2000 to 2010. The study investigates the causality relationships among real stock returns, basic interest rates, GDP, inflation and the market expectation of future behavior of these macroeconomic variables. The method used to find the correlation among the variables studied was the Stepwise Multiple Regression. The results show that basic interest rates and GDP affect the stock returns, however inflation and market expectation of future behavior of these macroeconomic variables affect stock returns insignificantly. [ABSTRACT FROM AUTHOR]

This paper examines how major earthquakes affected the returns and volatility of aggregate stock market indices in thirty-five financial markets over the last twenty years. Results show that global financial markets are resilient to shocks caused by earthquakes even if these are domestic. Our analysis reveals that, in a few instances, some macroeconomic variables and earthquake characteristics (gross domestic product per capita, trade openness, bilateral trade flows, earthquake magnitude, a tsunami indicator, distance to the epicenter, and number of fatalities) mediate the impact of earthquakes on stock market returns, resulting in a zero net effect. However, the influence of these variables is market-specific, indicating no systematic pattern across global capital markets. Results also demonstrate that stock market volatility is unaffected by earthquakes, except for Japan. [ABSTRACT FROM AUTHOR]