Research output per year
Research output per year
Personal profile
Overview
Eghbal obtained his undergraduate degree in Economics from the University of Tehran (first-class honours), his master's degree in Industrial Engineering from the Iran University of Science and Technology (distinction) and his PhD degree in Finance from the Alliance Manchester Business School (AMBS), the University of Manchester. He is currently a Lecturer in Finance at the Alliance Manchester Business School, working on the theory and application of machine learning (ML) and natural language processing (NLP) in Finance. His current project focuses on developing the first comprehensive financial NLP repository, FinText, in collaboration with researchers and industry partners. This repository covers a variety of NLP models (from Word2Vec to GPT) and benchmarks, incorporating different big financial textual datasets. He recently secured a £12,000 grant from Alan Turing Institute (AI-Assisted Real-Time Decision-Making – Turing/Manchester) to accelerate this project.
Teaching
Lecturer
2022-2023 - Semester 1 Financial Derivatives.
University of Manchester - Alliance Manchester Business School (AMBS).
2021-2023 - Semester 2 Financial Engineering.
University of Manchester - Alliance Manchester Business School (AMBS).
2021-2022 - Semester 2 Fundamentals of Finance.
University of Manchester - Alliance Manchester Business School (AMBS).
Teacher assistant
2020-2021 - Semester 1 Statistics and Machine Learning(M.Sc.).
University of Manchester - Data Science .
2019-2021 - Semester 1 Financial Derivatives.
University of Manchester - Alliance Manchester Business School (AMBS).
2019-2020 - Semester 2 Advanced Statistics.
University of Manchester - Economics Department.
Further information
Workshops
02/21 Natural Language Processing (NLP), a theoretical and practical review.
University of Manchester (2 hours).
09/19 Programming skills for machine learning - an overview of the current practical and theoretical trend.
University of Manchester (2 hours).
06/17 - 11/17 Advanced MATLAB programming course with a focus on financial modeling and machine learning.
Khatam university / Securities and Exchange Organization of Iran (60 hours).
10/15 - 01/16 Intermediate MATLAB programming course for the banking sector.
Parsian bank - Investment department (40 hours).
Prizes and awards
2022 Best paper award (semifinalist).
FMA Annual Meeting.
2018 Alliance Manchester Business School PhD Scholarship.
University of Manchester.
2012 Top 5% GPA in undergraduate school among 100 students.
Faculty of Economics - University of Tehran.
2012 Was accepted at the graduate school without entrance exam.
Was accepted at Iran University of Science and Technology, Department of Industrial Engineering based on outstanding academic background (Exceptional Talents program).
Other research
Nonlinearity Test for Principal Component Analysis: A MATLAB code.
Habibnia, Ali, Eghbal Rahimikia, and Hossein Mahdikhah.
(2018). ResearchGate, 2018
MATLAB Cheat Sheet for Data Science - London School of Economics.
Habibnia, Ali and Eghbal Rahimikia.
ResearchGate (2017). London School of Economics, 2017
Detecting corporate tax evasion using a hybrid intelligent system: A case study of Iran.
Rahimikia, Eghbal, Shapour Mohammadi, Teymur Rahmani, and Mehdi Ghazanfari.
International Journal of Accounting Information Systems 25 (2017) pp. 1–17. Elsevier, 2017
Education/Academic qualification
Doctor of Philosophy, Finance, Alliance Manchester Business School
2018 → 2023
Award Date: 31 Mar 2023
Master of Engineering, Industerial Engineering, Iran University of Science & Technology
2012 → 2014
Award Date: 31 Dec 2014
Bachelor of Economics, University of Tehran
2009 → 2012
Award Date: 31 Dec 2012
External positions
Research assistant Intern - Developing FinText, a purpose-built financial word embedding for financial textual analysis, proposing an ML model via FinText for realised volatility forecasting, and making the designed model more transparent and understandable by Explainable AI methods under the supervision of Stefan Zohren at Oxford-Man Institute of Quantitative Finance., Oxford University
Jan 2021 → Apr 2021
CEO consultant - Working as CEO consultant in design and implementation of an integrated financial, accounting, and auditing software connecting and supervising 33 subsidiary companies., Omid Investment Management Group Co
2017
Project manager/Software developer - Designing and developing a system to detect corporate tax evasion based on machine learning and statistical models with more than 10,000 lines of written code. Also, developing models to determine the current status of tax offices across the country and promote selected offices using Factor Analysis. , Iranian National Tax Administration
2014 → 2017
Areas of expertise
- HG Finance
- Financial Markets
- Quantitative Modelling
- Financial Econometrics
- QA75 Electronic computers. Computer science
- Machine Learning
- Deep Learning
- text mining
- Big Data
- Data Science
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Network
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Machine Learning for Realised Volatility Forecasting
Rahimikia, E. & Poon, S-H., 12 Oct 2020, Social Science Research Network, 51 p.Research output: Working paper
Open Access -
Alternative Data for Realised Volatility Forecasting: Limit Order Book and News Stories
Rahimikia, E. & Poon, S-H., 12 Sep 2020, Social Science Research Network, 36 p. (SSRN Electronic Journal).Research output: Working paper
Open Access -
Realised Volatility Forecasting: Machine Learning via Financial Word Embedding
Rahimikia, E., Zohren, S. & Poon, S-H., 29 Jul 2021.Research output: Working paper
Open Access -
Detecting corporate tax evasion using a hybrid intelligent system: A case study of Iran
Rahimikia, E., Mohammadi, S., Rahmani, T. & Ghazanfari, M., 1 May 2017, In: International Journal of Accounting Information Systems. 25, p. 1-17 17 p.Research output: Contribution to journal › Article › peer-review