Asymmetric dependence between the prospect theory value and stock returns in India: a quantile regression approach

被引:0
|
作者
Yadav, Manisha [1 ]
Dixit, Gaurav [2 ]
机构
[1] Indian Inst Technol Roorkee, Dept Management Studies, Roorkee, India
[2] Indian Inst Technol Roorkee, Roorkee, India
关键词
Asset pricing model; Behavioral biases; Prospect theory; Quantile regression; Risk preferences; G11; G12; G41; C31; ASSET PRICES; PROBABILITY; LOTTERIES; GAMBLES;
D O I
10.1108/MF-10-2023-0628
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
PurposeMotivated by the evidence highlighting the role of sentiments and cognitive biases in investors' decision-making, this study examines a novel behavioral finance-based asset pricing model incorporating the prospect theory framework in the Indian equity market. Specifically, the study's primary objective is to investigate the importance of Prospect Theory Value (PTV) in the cross-sectional pricing of stocks.Design/methodology/approachThe empirical findings rely on data taken from NIFTY 500 and BSE S&P 500 stocks, encompassing daily, weekly and monthly observations. The analysis employs diverse statistical techniques, including Ordinary Least Squares (OLS), Fama-Macbeth Cross-section Regressions, Panel Fixed Effect and Quantile Regression.FindingsThe study demonstrates an asymmetric association between PTV and subsequent stock returns. The findings maintain their robustness even when factoring in stock-specific attributes such as market capitalization and book-to-market ratio, market beta and indicators related to lottery-like behavior such as skewness and MAX. This observed pattern persists when analyzing data at various frequencies, including daily, weekly and monthly intervals. Loss aversion behavior dominates among Indian equity investors, contrary to lottery preferences in the US equity market.Originality/valueAs far as the authors are aware, the study is the first to introduce a new behavioral finance-motivated stock return predictor (PTV) in the Indian stock market. The study also marks the pioneering use of a novel method that evaluates the predictability of PTV across various sections of the conditional return distribution using quantile regression.
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页数:26
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