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Asymmetric herding as a source of asymmetric return volatility

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  • Park, Beum-Jo

Abstract

As a considerable source of asymmetry in return volatility, this paper introduces asymmetric herding and extends the continuous beliefs system to account for its asymmetry and derive the asymmetric herding parameters that are easily estimated by using a maximum likelihood method based on the GARCH-type econometric model. This paper presents new empirical evidence for asymmetry in the exchange rates volatility of major currencies against the US dollar, which have bilateral nature. Interestingly, the asymmetry of Japanese yen is the opposite of that of others and the global financial crisis highlights the opposite asymmetry. Some of traditional hypotheses, such as the leverage effect and the volatility feedback effect, do not adequately explain these findings; however, a significant asymmetric herding effect is observed and appears to be time-varying. Further, the clear link between asymmetric herding and volatility strongly supports the hypothesis of the asymmetric herding effect.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Banking & Finance.

Volume (Year): 35 (2011)
Issue (Month): 10 (October)
Pages: 2657-2665

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Handle: RePEc:eee:jbfina:v:35:y:2011:i:10:p:2657-2665

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Web page: http://www.elsevier.com/locate/jbf

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Keywords: Asymmetry in return volatility Continuous beliefs system Asymmetric herding parameters Foreign exchange markets;

References

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Citations

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Cited by:
  1. Akdoğu, Evrim & MacKay, Peter, 2012. "Product markets and corporate investment: Theory and evidence," Journal of Banking & Finance, Elsevier, vol. 36(2), pages 439-453.
  2. Park, Beum-Jo, 2014. "Time-varying, heterogeneous risk aversion and dynamics of asset prices among boundedly rational agents," Journal of Banking & Finance, Elsevier, vol. 43(C), pages 150-159.
  3. Haas, Markus & Krause, Jochen & Paolella, Marc S. & Steude, Sven C., 2013. "Time-varying mixture GARCH models and asymmetric volatility," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 602-623.
  4. Cordis, Adriana S. & Kirby, Chris, 2014. "Discrete stochastic autoregressive volatility," Journal of Banking & Finance, Elsevier, vol. 43(C), pages 160-178.
  5. Toshio Utsunomiya, 2013. "A new approach to the effect of intervention frequency on the foreign exchange market: evidence from Japan," Applied Economics, Taylor & Francis Journals, vol. 45(26), pages 3742-3759, September.
  6. Beum-Jo Park, 2011. "Forecasting Volatility in Financial Markets Using a Bivariate Stochastic Volatility Model with Surprising Information," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 37-58, September.
  7. Olivier Damette & Stéphane Goutte, 2014. "Tobin tax and trading volume tightening: a reassessment," Working Papers halshs-00926805, HAL.

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