The subject of unobservable variables encompasses this thesis. These latent (i.e., unobservable) variables must be inferred using statistical models or observable proxies. The objectives of my doctoral thesis are to develop and test new statistical models to infer these variables and link them...

The paper focuses on the relationship between firms' characteristics and cross-section returns. The author reviews and critically assesses the most recent contributions in the literature. After comparing the abnormal returns (Alpha) and t statistics of the original works with those of...

We use intraday data to compute weekly realized variance, skewness, and kurtosis for equity returns and study the realized moments' time-series and cross-sectional properties. We investigate if this week's realized moments are informative for the cross-section of next week's stock returns. We...

We investigate the cross-sectional pattern of stock returns for eight emerging markets using Vector Autoregressive Approach (VAR) to test whether dividend yields can predict stock returns through impulse response characteristics. Our results confirm that dividend yield shocks play an important...

According to the Granger-causality test, this study investigates the causation of business sector return in the Thailand stock market. Moreover, the result reveals that sectors' return connectedness contributes to the predictive model for forecasting price. First, we construct vector...

This paper investigates the role of volatility risk on stock return predictability specified on two global financial crises: the dot-com bubble and recent financial crisis. Using a broad sample of stock options traded at the American Stock Exchange and the Chicago Board Options Exchange (CBOE)...

This paper reports that the variance-of-variance premium (VVP), the difference between the risk-neutral and physical measures of variance-of-variance, has strong predictability for stock returns, especially at very short horizons. Furthermore, pooling both information on the VVP and the variance...