In this paper we examine the interactions between the U.S. stock market and the Chinese stock market in the scope of market microstructure. In particular, first time in the literature, we examine the forecasting ability of the stock performance in one market to predict the direction of the stock...

This paper revisits two valuation models based on accounting figures: the Residual Income Valuation (RIV) and Abnormal Earnings Growth (AEG). Our research design has two approaches: i) we demonstrate theoretical integration of both models; and ii) we show in a practical manner that models...

This paper studies the intertemporal relation between U.S. volatility risk and international equity risk premia. We show that a common volatility risk factor constructed from the option-implied U.S. forward variances positively and significantly predicts future stock market returns of the...

Existing models of option returns neglect the distribution of expected underlying asset volatility. An ensemble of six common GARCH models affords estimates of the moments of the physical—rather than the risk-neutral—distribution of anticipated—instead of historical—volatility, as well...

This paper provides an empirical study on the predictability of implied volatility using dataset collected from the London over-the-counter currency option market. The present work is motivated by the lack of empirical studies that address implied volatility characteristics across various...

In 2008, the S&P500 aggregated a loss of 30.16% during three selected days. Unfortunately, benchmark risk measures didn't forecast these hazards. Consequently, we witness a growing interest in coherent risk measures, sensitive to high moments and heavy tail risk. Such measures were proposed by...

We use learning in an equilibrium model to explain the puzzling predictive power of the volatility risk premium (VRP) for option returns. In the model, a representative agent follows a rational Bayesian learning process in an economy under incomplete information with the objective of pricing...

We forecast monthly Value at Risk (VaR) and Conditional Value at Risk (CVaR) using option market data and four different econometric techniques. Independently from the econometric approach used, all models produce quick to estimate forward-looking risk measures that do not depend from the amount...