Machine learning (ML) is a novel method that has applications in asset pricing and that fits well within the problem of measurement in economics. Unlike econometrics, ML models are not designed for parameter estimation and inference, but similar to econometrics, they address, and may be better...

Stock market prediction has always caught the attention of many analysts and researchers. Popular theories suggest that stock markets are essentially a random walk and it is a fool’s game to try and predict them. Predicting stock prices is a challenging problem in itself because of the number...

The sentiment of news predicts the short-term stock market performance of individual companies. We find that this association is solely due to the idiosyncratic informational content of an article. We transparently quantify the association between news sentiment and stock market performance of...

We investigate whether machine learning techniques and a large set of financial and macroeconomic variables can be used to predict future S&P realized volatility. We evaluate the aggregate volatility predictions of regularization methods (Ridge, Lasso, and Elastic Net), tree-based methods...

We examine the predictability of expected stock returns across horizons using machine learning. We use neural networks, and gradient boosted regression trees on the U.S. and international equity datasets. We find that predictability of returns using neural networks models decreases with longer...

With its America First strategy, the former US administration turned away from an internationally oriented trade policy. It attempted to assert its interests, especially vis-à-vis China, with bilateral and mostly restrictive measures such as import tariffs. This Weekly Report shows that the...

Although the effects of economic news announcements on asset prices are well established, theserelationships are unlikely to be stable. This paper documents the time variation in the responses of yield curves and exchange rates using high-frequency data from January 2000 through August 2011....

Although the effects of economic news announcements on asset prices are well established, theserelationships are unlikely to be stable. This paper documents the time variation in the responses of yield curves and exchange rates using high-frequency data from January 2000 through August 2011....

The paper aims to investigate the possible dual causality between exchange rates and stock indices of China and ASEAN using Structural Vector Auto-Regressive Model (SVAR). The paper has analysed the dynamic relationships between the Yuan and the Shanghai Composite Index and Shenzhen Stock Index...