We use realized volatilities based on after hours high frequency returns to predict next day volatility. We extend GARCH and long-memory forecasting models to include additional information: the whole night, the preopen, the postclose realized variance, and the overnight squared return. For four...

The validity of the Efficient Market Hypothesis has been under severe scrutiny since several decades. However, the evidence against it is not conclusive. Artificial Neural Networks provide a model-free means to analize the prediction power of past returns on current returns. This chapter...

The purpose of this research is to examine the impact of sentiment derived from news headlines on the direction of stock price changes. The study examines stocks listed on the WIG-banking sub-sector index on the Warsaw Stock Exchange. Two types of data were used: textual and market data. The...

The Efficient Market Hypothesis is one of the most popular subjects in the empirical finance literature. Previous studies in the stock markets, which are mostly based on fixed time price variations, do not provide conclusive findings, in which evidence of short-term predictability varies...

This paper examines the proxy variables of investor sentiment in Chinese stock market carefully, and tries to construct an investor sentiment index indirectly. We use cross correlation analysis to examine lead-lag relationship between the proxy variables and HS300 index. The results show that...

Our research on data for the S&P 500 ETF from 1993-2013 documents an intraday momentum pattern: the first half-hour return on the market (from the previous day's close) predicts the last half-hour return. The predictability, both statistically and economically significant, is stronger on more...

Price movements in industrial metals such as copper and aluminum predict stock returns. Increasing industrial metal prices are good news for equity markets in recessions and bad news in expansions. A one standard deviation increase in industrial metal returns predicts a price drop of one and a...

This study discusses the trading behavior of foreign investors with respect to economic uncertainty in the South Korean stock market from a time-varying perspective. We employ a news-based measure of economic uncertainty along with the model of time-varying parameter vector autoregression with...

Noisy markets need extensive descriptions that are noisy themselves, such as deep regression trees that capture many data-local nonlinear anomalies and that do not require arbitrary weighting schemes like traditional linear multifactor models often do. Simple tools allow extraction of general...

This paper examines return predictability of the U.S. stock market using portfolios sorted by size, book-to-market ratio, and industry. A novel panel variance ratio test is proposed and employed to evaluate time-varying return predictability from 1964 to 2011. It is found that the stock returns...