Mr Eghbal Rahimikia

Overview

Eghbal obtained his undergraduate degree in Economics from the University of Tehran (first-class honours) and his master degree in Industrial Engineering from the Iran University of Science and Technology (distinction). In the master's degree, he focused on the theory and application of machine learning in bankruptcy prediction of companies. During that time, the Iranian National Tax Administration offered him a project related to tax evasion detection. He worked for more than two years in this project as a project manager and developer, and he developed a comprehensive software with more than 10,000 lines of written code incorporating different machine learning techniques such as Artificial Neural Network and Support Vector Machine. After this, he did different projects using Factor Analysis and Data Envelopment Analysis related to the calculation of efficiency of tax sectors and banking industry. Furthermore, he published the results of his research and projects in different journals. He is currently a PhD student at Alliance Manchester Business School (AMBS) under the supervision of Prof. Ser-Huang Poon working on the theory and application of machine learning and deep learning in finance. He finished working on two papers entitled Big Data Approach to Realised Volatility Forecasting Using HAR Model Augmented With Limit Order Book and News and Machine learning for Realised Volatility Forecasting. Currently, he's working on text mining and machine learning with a focus on financial news for volatility and return forecasting. Also, he is research assistant intern at the Oxford-Man Institute of Quantitative Finance, the University of Oxford under the supervision of Stefan Zohren. For more information, please visit his Personal Page.