Neural Network Trained to Predict Crises in Russian Stock Market
Economists from HSE University have developed a neural network model that can predict the onset of a short-term stock market crisis with over 83% accuracy, one day in advance. The model performs well even on complex, imbalanced data and incorporates not only economic indicators but also investor sentiment. The paper by Tamara Teplova, Maksim Fayzulin, and Aleksei Kurkin from the Centre for Financial Research and Data Analytics at the HSE Faculty of Economic Sciences has been published in Socio-Economic Planning Sciences.
Neural Network for Assessing English Language Proficiency Developed at HSE University
The AI Lingua Neural Network has been collaboratively developed by the HSE University’s AI Research Centre, School of Foreign Languages, and online campus. The model has been trained on thousands of expert assessments of both oral and written texts. The system evaluates an individual's ability to communicate in English verbally and in writing.