Volatility Discovery

Gustavo Fruet Dias (), Cristina M. Scherrer () and Fotis Papailias ()
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Gustavo Fruet Dias: Aarhus University and CREATES, Postal: Department of Economics and Business Economics, Fuglesangs Allé 4, 8210 Aarhus V, Denmark
Cristina M. Scherrer: Aarhus University and CREATES, Postal: Department of Economics and Business Economics, Fuglesangs Allé 4, 8210 Aarhus V, Denmark
Fotis Papailias: Queen's University Management School, Postal: Queen's University Management School, Queen's University Belfast, Riddel Hall, 185 Stranmillis Road, BT9 5EE, Northern Ireland

CREATES Research Papers from Department of Economics and Business Economics, Aarhus University

Abstract: TWe propose a novel way to assess information processing in a complex environment of market fragmentation. We take a different angle from the price discovery literature, and investigate information processing in the stochastic process driving stock's volatility (volatility discovery). We show that our volatility discovery framework successfully identifies the leading market in the volatility process, whereas price discovery measures are unable to capture the dynamics of the market-specific volatilities. We compute volatility discovery for 30 stocks and find significant differences in how exchanges impound information into the effcient volatility, as ARCA and NYSE are more important than NASDAQ. Interestingly, price discovery measures suggest different results for nearly half the sample.

Keywords: fragmented markets; information processing; volatility persistency; market microstructure; price discovery; high-frequency data (search for similar items in EconPapers)
JEL-codes: C32 C51 C52 G12 (search for similar items in EconPapers)
Pages: 58
Date: 2016-02-24
New Economics Papers: this item is included in nep-ets and nep-mst
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Citations: View citations in EconPapers (3)

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