Evolving an explanatory model for Indian Stock Market (Bombay Stock Exchange) using Agent based Artificial Stock Markets

Abstract

Volatility is an established phenomenon in emerging markets, and India is no exception. The volatility prevailing in the Indian stock market of Bombay Stock Exchange (BSE) is relatively high when compared to NASDAQ or NYSE in the US. The BSE trading system, which was initially both Order and Quote driven, transformed to only Order driven, wherein the buyers and sellers transact directly with each other. In the NASDAQ and NYSE, market-makers/ specialists newlinerespectively, play a vital role in their structure in trading, and bring in stability to the market. newlineHowever, market-makers are absent in the Indian markets, which is perhaps one of the key reasons for the prevailing high volatility. Stock markets are complex systems; hence models are needed to study their dynamics. newlineArtificial Stock Markets (ASM) are models for studying the link between individual investor newlinebehavior and financial market dynamics, enabling the study of agents behavior, price discovery mechanisms, the influence of market microstructure, and the reproduction of the stylized facts of real-world financial time-series. Market participants are modeled as evolving systems of autonomous interacting agents that correspond to the trading parties. In ASM models, prices can newlinebe endogenously formed by the system itself as the result of interaction of market participants. newlineThis dissertation focuses on evolving an explanatory model to study the behavior patterns of market participants of BSE employing agent based ASM models, and suggests a suitable market making model to regulate the volatility. A large number of agent based ASM models have been proposed by researchers primarily dealing with US markets, whereas, no such work has been seen published for the BSE. In this study, few well known representative ASM have been analysed to assess their suitability to model the BSE.