Stock trading, as a kind of high frequency generally seeks profits in extremely short market changes. And effective stock price forecasting can help investors obtain higher returns. Based on the data set provided by Jane Street, this paper makes use XGBoost model and LightGBM to realize prediction price. Since given training has large amount includes abnormal such missing value, we first carry ...

Abstract Cryptocurrencies are distributed digital currencies that have emerged as a consequence of financial technology advancement. In 2017, cryptocurrencies shown huge rise in their market capitalization and popularity. They now employed today’s systems individual investors, corporate firms, big institutions heavily investing them. However, this industry is less stable than traditional curren...

Currently, stock price forecasting is carried out using either time series prediction methods or trend classifiers. The trend classifiers are designed to predict the behaviour of stock price’s movement. Recently, soft computing methods, like support vector machines, have shown promising results in the realization of this particular problem. In this paper, we apply several prototype generation c...