Financial market efficiency has been constantly challenged with new evidence of calendar anomalies in the stock market. This paper examines the existence and predictability of the turn-of-the-month effect at Kuala Lumpur Composite Index (KLCI), Seoul Composite Stock Price Index (KOSPI) and Tokyo...

During times when the Chinese government wished to prop up the market, sell-side analysts from brokerages with significant government ownership issued relatively less pessimistic (or more optimistic) earnings forecasts, earnings-forecast revisions, and stock recommendations; they were also...

The asymmetric moving average model (asMA) is extended to allow forasymmetric quadratic conditional heteroskedasticity (asQGARCH). Theasymmetric parametrization of the conditional variance encompassesthe quadratic GARCH model of Sentana (1995). We introduce a framework fortesting asymmetries in...

In this paper, I show that the variance of Fama-French factors, the variance of the momentum factor, as well as the correlation between these factors, predict an important fraction of the time-series variation in post-1990 aggregate stock market returns. This predictability is particularly...

Recent empirical literature shows that Internet search activity is closely associated with volatility prediction in financial and commodity markets. In this study, we search for a benchmark model with available market-based predictors to evaluate the net contribution of the Internet search...

Asset prices are a valuable source of information about financial market participants.expectations about key macroeconomic variables. However, the presence of time-varying risk premia requires an adjustment of market prices to obtain the market’s rational assessment of future price and policy...

The emergence of algorithmic high-frequency trading in the market for credit risk affords accurate inference of new risk measures. When combined with machine learning predictive methods, these measures forecast substantial future changes in firms' credit and equity risk premiums in...

We study the performance of many traditional and novel, text-based variables for in-sample and out-of-sample forecasting of oil spot, futures, and energy company stock returns, and changes in oil volatility, production, and inventories. After controlling for small-sample biases, we find evidence...

Using density forecast evaluation techniques we compare the predictive performance of econometric specifications that have been developed for modeling duration processes in intra-day financial markets. The model portfolio encompasses various variants of the Autoregressive Conditional Duration...

This study sheds new light on the question of whether or not sentiment surveys, and the expectations derived from them, are relevant to forecasting economic growth and stock returns, and whether they contain information that is orthogonal to macroeconomic and financial data. I examine 16...