The article compares ARMA, boosting, neural network models, GARCH and HAR models, and proposes a new efficient method for forecasting one day ahead of the realized volatility of financial series. The GARCH and HAR models are taken as comparable models, which showed the best results in Manevich...

In the practical business of asset management by investment trusts and the like, the general practice is to manage over the medium to long term owing to the burden of operations and increase in transaction costs with the increase in turnover ratio. However, when machine learning is used to...

It is vitally crucial to establish a method that can accurately forecast prices on the stock exchange market because of the influence the stock market has on the country’s ability to raise capital and advance its economic growth. On the stock market, a great number of sensitivity factors are...

Financial contagion has been widely recognized as a fundamental risk to the financial system. Particularly potent is price-mediated contagion, wherein forced liquidations by firms depress asset prices and propagate financial stress, enabling crises to proliferate across a broad spectrum of...

We survey the nascent literature on machine learning in the study of financial markets. We highlight the best examples of what this line of research has to offer and recommend promising directions for future research. This survey is designed for both financial economists interested in grasping...