Essays On The Relationship Between Overconfident Trading Behavior And Market Returns Evidence From India And China

Abstract

newline Essays On The Relationship Between Overconfident Trading Behavior And Market Returns: Evidence From India And China newline newlineThis thesis mainly focuses on the examination of the overconfident trading behavior of the Chinese and Indian investors. The testing has been performed by utilizing different context and dimensions. The testing variable comprises the trading volume, a proxy for trading activities, market returns, market liquidity, and market volatility for the time-series analysis. The body of this work comprised of mainly four chapters. newline First chapter is the Introduction. The second chapter is the systematic literature review based on 17 cognitive and behavioral heuristics and biases. The systematic approach adopts the segmentation design through the distribution of 200 research papers on the basis of the ageing analysis, research methods, themes, heuristics and biases, and statistical techniques. Then, we present the integrated model (holistic model) to understand how these biases are linked to each other based on the literature review. This will assist the investors to understand the behavioral heuristics and biases and further lead to develop future research works based on the step-size models or integrated model. newlineThe first essay (Chapter third) is based on the central theme of literature review i.e. overconfidence bias. We examine the overconfident trading behavior and its persistence in pre-, during-, and post global recession through the vector autoregression and impulse response function. This work performs the comparative study between the Chinese and Indian investors. We also explore the overconfident trading behavior in up and down market states. In spite of overconfident trading activities, we also check the liquidity and volatility effect through the four-variate vector autoregression. newlineThe second essay examines the overconfident trading behavior through the regime-dependent models. The methodology adopted for this section includes the threshold vector auto regression and Markov regime-s