Ajim Uddin, PhD
I am an Assistant Professor of Financial Technology at Martin Tuchman School of Management (MTSM), New Jersey Institute of Technology (NJIT). In the broadest sense, my research interest is Machine Learning and Data Mining with Application to Finance. I am currently working on nonlinear tensor factorization and network representation for financial markets. Primarily my focus is on modeling dynamic changes in network structures and incorporating network information into traditional asset pricing models using spectrum analysis and graph neural networks.
On a personal level, I like to play Cricket and Soccer. I truly enjoy hiking and reading books. Two of my recent favorite books are "Becoming" - by Michelle Obama and "Born a Crime" - by Trevor Noah. Speaking of Trevor Noah, sometimes I do stand-up comedy, and trust me, I am really good at this.
I will attend the 2022 INFORMS Annual Meeting to present my paper "The Network Factor of Equity Pricing: A Signed Graph Laplacian Approach" on October 16-19, 2022. See you in Indianapolis, Indiana.
I will attend the 2022 FMA Annual Meeting to present my paper "Network Centrality, Leadership, and Institutional Investors Portfolio Performance." on October 19-22, 2022. See you in Atlanta, Georgia.
I will attend the DECISION SCIENCES INSTITUTE 53rd ANNUAL CONFERENCE to present my paper "Network Centrality, Leadership, and Institutional Investors Portfolio Performance." On November 19-21, 2022. See you in Houston, Texas.
Machine Learning and Data Mining with Application to Finance;
Empirical Asset Pricing;
Graph Neural Network for Representation Learning in Finance
Fang, M., Taylor, S., and Uddin, A. (2022). The Network Structure of Overnight Index Swap Rates. Finance Research Letters, 46(B), 102425. [ Link ]
Chowdhury, M., Meo, M., Uddin, A., and Haque, M., (2021). Asymmetric Effect of Energy Price on Commodity Price: New Evidence from NARDL and Time Frequency Wavelet Approaches. Energy , 231, 120934. [ Link ]
Uddin, A., Yu, D. (2020). Latent factor model for asset pricing, Journal of Behavioral and Experimental Finance , 27. [ Link ]
Uddin, A., Chowdhury, M., and Islam, M. (2020). Revisiting the impact of institutional quality on post-GFC bank risk-taking: Evidence from emerging countries. Emerging Markets Review , 42. [ Link ]
Uddin, A., Chowdhury, M., and Islam, M. (2017). Resiliency between Islamic and conventional banks in Bangladesh: Dynamic GMM and quantile regression approaches. International Journal of Islamic and Middle Eastern Finance and Management , 10(3), pp.400-418. [Link]
Uddin, A., Chowdhury, M., and Islam, M. (2017). Determinants of Financial Inclusion in Bangladesh: Dynamic GMM & Quantile Regression Approach. The Journal of Developing Areas, 51(2), pp.221-237. [Link]
Uddin, A., Chowdhury, M., and Islam, M. (2017). Do Socio-Economic Factors Matter for the Financial Development of a Muslim Country? A Study in Bangladesh Banking Sector. International Journal of Business and Society , 18(S1), pp.59-78. [Link]
Uddin, A., Tao, X., and Yu, D. (2021). Attention Based Dynamic Graph Learning Framework for Asset Pricing. in: 30th ACM International Conference on Information and Knowledge Management. CIKM-2021. ACM. [ Link ]
Uddin, A., Tao, X., Chou, C., and Yu, D. (2020). Nonlinear Tensor Completion Using Domain Knowledge: An Application in Analysts’ Earnings Forecast, In: 20th IEEE International Conference on Data Mining Workshop. ICDMW-2020. IEEE. [ Link ]
Rasid, M., Uddin, A. and Chowdhury, M. (2019). Islamic corporate finance: capital structure. In: H. Kabir, M. Rashid and S. Aliyu, ed., Islamic Corporate Finance, 1st ed. Abingdon, Oxfordshire: Routledge. [Book Link]
"Attention Based Dynamic Graph Neural Network for Asset Pricing." With X. Tao and D. Yu. [ Link ]
Revision requested (2nd round) at Journal of Banking & Finance.
Presented at 37th International Conference of the French Finance Association (AFFI) 2021. 26 - 28 May, 2021.
"Machine Learning for Earnings Prediction: A Nonlinear Tensor Approach for Data Integration and Completion." With X. Tao, C. Chou, and D. Yu.
Under review at ACM Transactions on Knowledge Discovery from Data (TKDD)
"MLCTR: A Fast Scalable Coupled Tensor Completion Based on Multi-Layer Non-Linear Matrix Factorization." With D. Zhou, X. Tao, C. Chou, and D. Yu. [Link]
"A Fast Non-Linear Coupled Tensor Completion Algorithm for Data Integration, Imputation and Link Prediction." With D. Zhou, Z. Shang, and D. Yu.
"Network Centrality, Leadership, and Institutional Investors Portfolio Performance."
Presented at Northeast Decision Sciences Institute 2022, Annual Conference. 7 - 09 October, 2022. Best Overall Conference Paper Award
Presented at Financial Management Association Annual Meeting, FMA (2021) 20 - 23 October, 2021.
[ GITHUB LINK ]
Are Missing Values Important for Earnings Forecast? A Machine Learning Perspective.
[ Python Code ]
Attention Based Dynamic Graph Learning Framework for Asset Pricing.
[ Python Code ]
|FIN 218||Financial Markets and Institutions||Fall 2021|
|MIS 245||Management Information System||Spring 2020, Fall 2019, Spring 2019|
|MIS 645||Information System Principles||Spring 2021|
|MGMT 316||Business Research Methods||Spring 2021|
|FIN 410||Data Mining and Machine Learning||Fall 2020|
|MGMT 630||Decision Analysis||Summer 2020, Fall 2020|
|MGMT 635||Data Mining and Analytics for Managers||Summer 2020|
|BUS 474||Financial Institutions and Capital Market||Spring 2016|
|BUS 370||Introduction to Corporate Finance||Spring 2016|
VP Finance PhD Club NJIT (2018-2019, 2019-2020)
MTSM Department Resprasentative Graduate Student Association (GSA) (2019-2020)
ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD)
ACM International Conference on Information and Knowledge Management (CIKM).
IEEE International Conference on Data Mining (ICDM)
AAAI Conference on Artificial Intelligence (AAAI)
Finance Research Letters
Journal of Behavioral and Experimental Finance
Emerging Markets Review
Emerging Markets Finance and Trade