Indian Institute of Management Calcutta

About: Indian Institute of Management Calcutta is a education organization based out in Kolkata, India. It is known for research contribution in the topics: Supply chain & Context (language use). The organization has 415 authors who have published 1354 publications receiving 21725 citations. The organization is also known as: IIMC & IIM Calcutta.

Holistic Personality Development through Education Ancient Indian Cultural Experiences

Abstract: Ancient India recognized the supreme value of education in human life. The ancient thinkers felt that a healthy society was not possible without educated individuals. They framed an educational scheme carefully and wisely aiming at the harmonious development of the mind and body of students. What they framed was a very liberal, all-round education of a very high standard, calculated to prepare the students for a useful life in enjoying all aspects of life. This is essentially a universally applicable educational framework highlighting the purpose of human life and interconnectedness at all levels of existence as a basis of human values. Insights from ancient Indian educational system are of great help in facilitating the production of a creative, ethical and a learning mind, which will concern itself not only with greater ‘progress’, but primarily or more importantly with the inner transformation of the human consciousness.

Performance of Indian Equity Mutual Funds vis-a vis Their Style Benchmarks: An Empirical Exploration

Abstract: In this paper we did a return based style analysis of equity mutual funds in India using quadratic optimization of an asset class factor model proposed by William Sharpe. We found the 'style benchmarks' of each of our sample of equity funds as optimum exposure to eleven passive asset class indexes. We also analyzed the relative performance of the funds with respect to their style benchmarks. Our results show that the funds have not been able to beat their style benchmarks on the average.

Sequential estimation of normal mean under asymmetric loss function with a shrinkage stopping rule

Abstract: The problem of estimating a normal mean with unknown variance is considered under an asymmetric loss function such that the associated risk is bounded from above by a known quantity. In the absence of a fixed sample size rule, a sequential stopping rule and two sequential estimators of the mean are proposed and second-order asymptotic expansions of their risk functions are derived. It is demonstrated that the sample mean becomes asymptotically inadmissible, being dominated by a shrinkage-type estimator. Also a shrinkage factor is incorporated in the stopping rule and similar inadmissibility results are established.