Artikel
Maximum likelihood estimation of stock volatility using jump-diffusion models
We investigate whether there are systematic jumps in stock prices using the Brownian motion approach and Poisson processes to test diffusion and jump risk, respectively, on Johannesburg Stock Exchange and whether these jumps cause asset return volatility. Using stock market data from June 2002 to September 2016, we hypothesize that stocks with high positive (negative) slopes are more likely to have large positive (negative) jumps in the future. As such, we expect to observe salient properties of volatility on listed stocks. We also conjecture that it is valid to use maximum likelihood procedures in estimating jumps in stocks.
- Language
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Englisch
- Bibliographic citation
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Journal: Cogent Economics & Finance ; ISSN: 2332-2039 ; Volume: 7 ; Year: 2019 ; Issue: 1 ; Pages: 1-17 ; Abingdon: Taylor & Francis
- Classification
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Wirtschaft
Hypothesis Testing: General
Methodological Issues: General
- Subject
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Merton jump diffusion model
Black scholes volatility (IV) curves
Weiner process
maximum likelihood estimation
- Event
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Geistige Schöpfung
- (who)
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Chekenya, Nixon S.
- Event
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Veröffentlichung
- (who)
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Taylor & Francis
- (where)
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Abingdon
- (when)
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2019
- DOI
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doi:10.1080/23322039.2019.1582318
- Handle
- Last update
- 10.03.2025, 11:44 AM CET
Data provider
This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Artikel
Associated
- Chekenya, Nixon S.
- Taylor & Francis
Time of origin
- 2019
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