DEPARTMENT SEMINAR ON
Speaker: Prof. Raghu Nandan Sengupta
DIME, IIT Kanpur
Date: 9 April 2025 [Wednesday]
Time: 12:00 PM
Venue: Annex Classroom No:1 [Management Studies]
Title: “Robust Portfolio Optimization considering HARA Utility Functions and Mean Lower Semi-Absolute Deviation (MLSAD)”
Abstract:
The study of portfolio management denotes the process of identification, selection, and managing a collection of investments, e.g., stocks, bonds, commodities, derivatives, cash, cash equivalents, etc. In this research we develop “Robust Optimization” models for the Markowitz Mean Variance case, HARA objective function with HARA return and HARA variance cases (considering both normal as well as EVD returns) and finally the Mean Lower Semi-Absolute Deviation (MLSAD) objective function considering HARA return and HARA variance cases. The data is taken are the index prices of CAC 40, DJIA, Nikkei 225, NIFTY 50, DAX, HANG SENG and KOSPI, for the time period 01-06-2020 to 31-05-2022. The results demonstrate the efficacy of our models and help us draw few interesting conclusions from the outputs.
Brief Bio:
Professor Raghu Nandan Sengupta is a distinguished academic in the Department of Industrial and Management Engineering at the Indian Institute of Technology Kanpur (IIT Kanpur). He earned his Bachelor’s degree in Mechanical Engineering from Birla Institute of Technology Mesra, Ranchi, India, in 1992, and completed his Fellow Programme in Management (Ph.D.) with a specialization in Operations Management from the Indian Institute of Management Calcutta in 2003. Prof. Sengupta’s research interests encompass Sequential Estimation, Statistical and Mathematical Reliability Theory, Risk Analysis, Optimization Techniques in Finance, Metaheuristic Techniques, Reliability-based Optimization, and Robust Optimization. He has contributed extensively to these fields through numerous publications and has been involved in various academic initiatives, including the Global Initiative of Academic Networks (GIAN) courses on Multiobjective Optimization Using Metaheuristics and Data Analytics for Operations Research.