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Eghbal Rahimikia_

Assistant Professor in Financial Technology, Alliance Manchester Business School (AMBS)

Email:
eghbal.rahimikia@manchester.ac.uk
Address:
3.054, Alliance Manchester Business School, Booth St W, Manchester M15 6PB United Kingdom

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I obtained my undergraduate degree in Economics from the University of Tehran (first-class honours), my master's degree in Industrial Engineering from the Iran University of Science and Technology (distinction) and my PhD degree in Finance from the Alliance Manchester Business School (AMBS), the University of Manchester. I am currently an Assistant Professor (Lecturer) in Financial Technology (FinTech) at the Alliance Manchester Business School, working on the theory and application of machine learning (ML) and natural language processing (NLP) in Finance.

NEWS:

  1. • (September 2024) - FinText is updated with the first suite of 68 historical pre-trained Large Language Models (LLMs) designed specifically for business studies. Explore it here!
  2. • (January 2023) - FinText Gold-Standard Financial Benchmark is available to download now!
  3. • (November 2022) - FinText has been visited and downloaded over 1500 times during the past 12 months. We are happy to announce that it is renaming as a brand new repository of NLP models in finance. Updates are on the way by introducing new models and benchmarks in this area.
  4. • (July 2021) - The first group of purpose-built financial word embedding for financial textual analysis is available now for download under the FinText repository.

Education_

University of Manchester, UK

Alliance Manchester Business School (AMBS)

2018 - 2023 (March)

Ph.D. in Finance.

Supervisor: Ser-Huang Poon.

Examination Committee: Stephen Roberts (University of Oxford), Stuart Hyde (University of Manchester).

GPA: Distinction.

Iran University of Science and Technology, Iran

2012 - 2014

M.Sc. in Industrial Engineering.

Major: Socio-Economical Systems Engineering.

Thesis: Bankruptcy prediction of Iranian companies based on hybrid intelligent systems.

GPA: 18.33/20, Thesis grade: 20/20 (distinction).

University of Tehran, Iran

2009 - 2012

B.A. in Economics.

GPA: 18.42/20 (first-class honours).

Experience_

Assistant Professor in Financial Technology (FinTech)

University of Manchester, UK

Agusut 2023 - Cur.

Consultant

Hull Tactical Asset Allocation, US

Agusut 2023 - Cur.

Lecturer in Finance

University of Manchester, UK

Sep 2021 - Agusut 2023

Research Assistant Intern

University of Oxford, UK

Jan 2021 - Apr 2021

Graduate Teaching Assistant

University of Manchester, UK

Sep 2019 - Sep 2021

CEO Consultant

Omid Investment Management Group Co, Iran

Jul 2017 - Dec 2017

Project manager/Software developer

Iranian National Tax Administration, Iran

Jul 2014 - Jul 2017

Publications_

Re(Visiting) Large Language Models in Finance

Rahimikia, Eghbal, and Felix Drinkall

Available at SSRN (2024). 20241

Realised Volatility Forecasting: Machine Learning via Financial Word Embedding

Rahimikia, Eghbal, Stefan Zohren, and Ser-Huang Poon

Available at SSRN 3895272 (2021). 2021

Machine Learning for Realised Volatility Forecasting

Rahimikia, Eghbal and Ser-Huang Poon

Available at SSRN 3707796 (2020). 2020

Alternative Data for Realised Volatility Forecasting: Limit Order Book and News Stories

Rahimikia, Eghbal and Ser-Huang Poon

Available at SSRN 3684040 (2020). 2020

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

Get in touch_

Email:
eghbal.rahimikia@manchester.ac.uk

© 2024 Eghbal Rahimikia.