With approximately 900 million observations we conduct, to our knowledge, the largest study ever of intraday stock return predictability using machine learning techniques finding consistent out-of-sample predictability across market, sector, and individual stock returns at various time horizons....

For stock market predictions, the essence of the problem is usually predicting the magnitude and direction of the stock price movement as accurately as possible. There are different approaches (e.g., econometrics and machine learning) for predicting stock returns. However, it is non-trivial to...

This study employs a variety of machine learning models and a wide range of economic and financial variables to enhance the forecasting accuracy of the Korean won-U.S. dollar (KRW/USD) exchange rate and the U.S. and Korean stock market returns. We construct international asset allocation...

A speculative bubble is usually defined as the difference between the market value of a security and its fundamental value. Although there are several important theoretical issues surrounding the topic of asset bubbles, the existence of bubbles is inherently an empirical issue that has not been...

This paper examines the evidence regarding predictability in the market risk premium using artificial neural networks (ANNs), namely the Elman Network (EN) and the Higher Order Neural network (HONN), univariate ARMA and exponential smoothing techniques, such as Single Exponential Smoothing (SES)...

Pastor and Stambaugh (2012) demonstrate that from a forward-looking perspective, stocks are more volatile in the long run than they are in the short run. We investigate how the economic constraint of non-negative equity premia aspects predictive variance. When investors expect non-negative...

This paper proposes a new information share for price discovery based on Russell's (1999) autoregressive conditional intensity model. While previous studies rely on equally spaced high frequency data, we use the information conveyed by trade intensities to determine a market's contribution to...

The stock market behaviour and trend can be move according to the different internal, external, micro economic and macro economic factors. The impact of some events that definitely occurs can't be envisaged by the stock market with confidence due to their nature. A budget is an influential...

Fractal analysis is carried out on the stock market indices of seven European countries and the US. We find evidence of long-range dependence in the log return series of the Mibtel (Italy) and the PX-Glob (Czech Republic). Long-range dependence implies that predictable patterns in the log...

Since portfolio management relies on the association of portfolio diversification, analyzing the spillover between the United States (US) and Asian-Pacific financial markets has become more critical. If Asian stock markets have low or negative correlations with each other and/or the US market,...