Sankarshan Basu

Market-wide Herding and the Impact of Institutional Investors in the Indian Capital Market

The article tries to identify the presence of ‘market-wide herding’ in the Indian capital market and whether institutional investors impact such herding. In particular, the article looks at the impact of Foreign Institutional Investors flows as well as mutual funds on herding. The work also looks at the the impact of index return and volatility on herding. JEL Classification: G140, G180, C580, G120

Term Structure Estimation in Illiquid Government Bond Markets An Empirical Analysis for India

With increasing liquidity of the Indian sovereign debt market since 1997, it has become possible to estimate the term structure in India. However, the market is characterised by several frictions that cause individual securities to be priced differently from the ‘average’ pricing in the market. In such a scenario, traditional estimation procedures like ordinary least squares using various functional forms do not perform well. In this paper, we find that mean absolute deviation is a better estimation procedure in illiquid markets than the ordinary least square. We further discover a novel liquidity weighted objective function for parameter estimation. We model the liquidity function using the exponential and hyperbolic tangent functions and suggest the most robust model for estimating term structures in India.

Development of Utility Function for Life Insurance Buyers in the Indian Market

Insurance as a financial instrument has been used for a long time. The dramatic increase in competition within the insurance sector (in terms of providers coupled with awareness for the need for insurance) has concomitantly resulted in more policy options being available in the market. The insurance seller needs to know the buyers preference for an insurance product accurately. Based on such multi-criterion decision-making, we use a logarithmic goal programming method to develop a linear utility model. The model is then used to develop a ready reckoner for policies that will aid investors in comparing them across various attributes.

Derivatives in Asia-Pacific Markets

Asian derivative markets today account for one-third of the worldwide foreign exchange and over 40 per cent of equity derivative trading. Korea hosts the world’s largest derivative exchanges, while India has the world’s fastest growing exchange. Derivatives have made Asian capital markets more competitive. They also have significant developmental benefits, for example, as hedging tools for commodity producers and as cheaper financing tools for corporations. Policymakers all around the world have learned to emphasise good regulation, governance and risk management through central counterparties in order to minimise potential threats to financial stability. BIS reports that the over-the-counter (OTC) derivative markets have grown ten-fold over

Country Risk Analysis in Emerging Markets: The Indian Example

The Beta Country Risk Model, as described by Erb, Harvey and Viskanta (1996) and used by Andrade and Teles (2004) for Brazil, is used to estimate the country risk of India based on several macroeconomic indicators. Ordinary least squares regression is run on the white noise (unexpected component) of these variables to explain the variation in country risk to identify the most relevant of these variables. The study shows that the variation in country risk of India is highly correlated with changes in FDI flows, interest rates (monetary policy), exchange rates and the unemployment rate. The effect of political risk on overall country risk is also studied.

Asset liability management model with decision support system for life insurance companies: Computational results

Abstract Big Data Analytics is an important and flexible tool available for data analysis and informed decision making. In this paper, we look at the use of Big Data Analytics in asset liability management and asset allocation in uncertain economic situations using stochastic linear programming (SLP). In particular, this paper is an extension of our earlier work and we contribute to the existing literature by conducting experiments on the stochastic model through DSS. In particular, for this SLP based DSS, we address issues like the optimal number of scenarios required for good results, and the impact of the change in the number of scenarios on the stability of the model. The paper also addresses the impact of the change in the number of scenarios on the policy holders’ as well as shareholders’ reserves. In particular, we show the relevance of employing a larger number of scenarios and also present the experimental design developed to test the relevance of this model. We also show that a stochastic model employing fewer scenarios produced marked improvements in both return side measures as well as risk side measures compared to a mean value model or a partial mean value model.

Database Structure for a Multi Stage Stochastic Optimization Based Decision Support System for Asset – Liability Management of a Life Insurance Company

We introduce a stochastic optimization based decision support system (DSS) for asset-liability management of a life insurance firm using a multi-stage, stochastic optimization model. The DSS is based on a multi-stage stochastic linear program (SLP) with recourse for strategic planning. The model can be used with little or no knowledge of management sciences. The model maximizes the expected value of total reserve (policy holders’ reserve and shareholders’ reserve) at the end of the time period of planning. We discuss the issues related to database design structure, DSS interface design, database updating procedure, and solution reporting.