Mamata Parhi

University of Roehampton

Roehampton Lane

London, SW15 5PU

United Kingdom

SCHOLARLY PAPERS

4

DOWNLOADS

435

SSRN CITATIONS

0

CROSSREF CITATIONS

0

Scholarly Papers (4)

1.

Luck or Skill: What Drives Hedge Fund Performance Persistence?

Number of pages: 25 Posted: 04 Aug 2022
Roehampton University, University of Roehampton, Southampton Business School, University of Southampton and Independent
Downloads 307 (186,086)

Abstract:

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Hedge fund; Persistence performance;

2.

Giver and the Receiver: Understanding Spillover Effects and Predictive Power in Cross-Market Bitcoin Prices

International Review of Financial Analysis, Vol. 63, No. 86-104, 2019
Number of pages: 43 Posted: 05 Mar 2020 Last Revised: 01 Sep 2022
Ahmad Al'Maaitah, Tapas Mishra and Mamata Parhi
University of Southampton - Centre for Digital Finance, Southampton Business School, University of Southampton and University of Roehampton
Downloads 81 (563,360)

Abstract:

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Cross-market Bitcoin prices; Return and volatility spillovers; Uncertainty; Inefficiency; Prediction

3.

COVID-19, ‘Meteor Showers’ and the Dependence Structure Among Major Developed and Emerging Stock Markets

Number of pages: 50 Posted: 05 Dec 2022
Wenshuo Guo, Ahmad Al'Maaitah and Mamata Parhi
University of Southampton, University of Southampton - Centre for Digital Finance and University of Roehampton
Downloads 47 (739,347)

Abstract:

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Risk contagion, Stock market, COVID-19, R-vine copula, Network

4.

How Effective are Policy Interventions in a Spatially-embedded International Real Estate Market?

Journal of Real Estate Finance and Economics, 2019
Posted: 02 Jul 2019
Kun Duan, Tapas Mishra, Mamata Parhi and Simon Wolfe
University of Southampton - Southampton Business School, Southampton Business School, University of Southampton, University of Roehampton and University of Southampton - Southampton Business School

Abstract:

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Housing price variations; Macroeconomic adjustments; Spatial frictions; Real estate market; Spatial dynamic panel regression; Estimation bias