We propose several nonparametric predictors of the mid-price in a limit order book, based on different features constructed from the order book data observed contemporaneously and in the recent past. We evaluate our predictors in the context of an order execution task by constructing order...

This paper proposes a new method for predicting jump arrivals in stock markets with high-frequency limit order book data. We introduce a new model architecture, based on Convolutional Long Short-Term Memory with attention, to apply time series representation learning with memory and to focus the...

Financial distress and bankruptcy of companies may cause the resources to be wasted and the investment opportunities to be faded. Bankruptcy prediction by providing necessary warnings can make the companies aware of this problem. The aim of this study is to compare the ability of Bayesian...

Financial distress and bankruptcy of companies may cause the resources to be wasted and the investment opportunities to be faded. Bankruptcy prediction by providing necessary warnings can make the companies aware of this problem. The aim of this study is to compare the ability of Bayesian...

In the context of a continually changing and reforming financial market, stock market volatility plays a vital role in indicating macroeconomic environment changes, market participants' expectation and interaction mechanism. Market volatility research has been conducted by worldwide academics...