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Behavioral Finance Approach to the Time-Varying Return-Volatility Relation: Global Evidence

Disha Mittal et al.

Journal of Prediction Markets2025https://doi.org/10.5750/jpm.v18i2.2125article
AJG 1
Weight
0.50

What the paper says

This study investigates the asymmetric return-volatility relation for 21 major global market indices for the period 1998–2018, employing quantile regression methodology. The results show that the transmission of good news shocks and bad news shocks has contrasting implications for the tails of the return-volatility relation. During the periods of falling prices, the sentiment-driven noise traders increase the volatility levels. In contrast, during the periods of rising prices, the contrarian actions by the more informed traders reduce the volatility levels. Overall, the results support the affect, representativeness, and extrapolation bias heuristic theories of investor behavior.

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https://doi.org/https://doi.org/10.5750/jpm.v18i2.2125

Or copy a formatted citation

@article{disha2025,
  title        = {{Behavioral Finance Approach to the Time-Varying Return-Volatility Relation: Global Evidence}},
  author       = {Disha Mittal et al.},
  journal      = {Journal of Prediction Markets},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.5750/jpm.v18i2.2125},
}

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Behavioral Finance Approach to the Time-Varying Return-Volatility Relation: Global Evidence

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.