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The relationship between the volatility of returns and the number of jumps in financial markets

Abstract:

We propose a methodology to employ high frequency financial data to obtain estimates of volatility of log-prices which are not affected by microstructure noise and Lévy jumps. We introduce the “number of jumps” as a variable to explain and predict volatility and show that the number of jumps in SPY prices is an important variable to explain the daily volatility of the SPY log-returns, has more explanatory power than other variables (e.g., high and low, open and close), and has a similar expla...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Accepted manuscript

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Publisher copy:
10.1080/07474938.2014.976529

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Institution:
University of Oxford
Department:
Oxford, MPLS, Mathematical Institute
Role:
Author
Publisher:
Taylor & Francis Group Publisher's website
Journal:
Econometric Reviews Journal website
Volume:
35
Issue:
6
Pages:
929-950
Publication date:
2014-10-20
DOI:
ISSN:
0747-4938 and 1532-4168
Pubs id:
pubs:624669
URN:
uri:881242b6-3609-4f4a-8c81-cc4e6fb7ddac
UUID:
uuid:881242b6-3609-4f4a-8c81-cc4e6fb7ddac
Local pid:
pubs:624669
Paper number:
6
Keywords:

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