Variance minimizing strategies for stochastic processes with applications to tracking stock indices

Colwell, DB; El-Hassan, N; Kwon, OK

Variance minimizing strategies for stochastic processes with applications to tracking stock indices

Colwell, DB El-Hassan, N Kwon, OK

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Publisher:: Wiley
Publication Type:: Journal Article
Citation:: International Review of Finance, 2021, 21, (2), pp. 430-446
Issue Date:: 2021-06-01

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Field	Value	Language
dc.contributor.author	Colwell, DB
dc.contributor.author	El-Hassan, N
dc.contributor.author	Kwon, OK
dc.date.accessioned	2022-07-05T05:36:38Z
dc.date.available	2022-07-05T05:36:38Z
dc.date.issued	2021-06-01
dc.identifier.citation	International Review of Finance, 2021, 21, (2), pp. 430-446
dc.identifier.issn	1369-412X
dc.identifier.issn	1468-2443
dc.identifier.uri	http://hdl.handle.net/10453/158661
dc.description.abstract	This paper extends the notion of variance optimal hedging of contingent claims under the incomplete market setting to the hedging of entire processes and applies the results to the problem of tracking stock indices. Sufficient conditions under which this is possible are given, along with the corresponding variance minimizing strategy. The performances of tracking error variance (TEV) minimizing, locally risk minimizing, and variance minimizing strategies in tracking stock indices are investigated using both simulated and historical market data. In particular, it is shown using S&P500 data over the period 2000 and 2015 that the TEV of the variance minimizing strategy is statistically lower than other strategies at the 95% confidence level for 6-month holding periods.
dc.language	en
dc.publisher	Wiley
dc.relation.ispartof	International Review of Finance
dc.relation.isbasedon	10.1111/irfi.12285
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	1501 Accounting, Auditing and Accountability, 1502 Banking, Finance and Investment
dc.title	Variance minimizing strategies for stochastic processes with applications to tracking stock indices
dc.type	Journal Article
utslib.citation.volume	21
utslib.for	1501 Accounting, Auditing and Accountability
utslib.for	1502 Banking, Finance and Investment
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Faculty of Business/Finance Discipline
utslib.copyright.status	closed_access	*
dc.date.updated	2022-07-05T05:36:36Z
pubs.issue	2
pubs.publication-status	Published
pubs.volume	21
utslib.citation.issue	2

Abstract:

This paper extends the notion of variance optimal hedging of contingent claims under the incomplete market setting to the hedging of entire processes and applies the results to the problem of tracking stock indices. Sufficient conditions under which this is possible are given, along with the corresponding variance minimizing strategy. The performances of tracking error variance (TEV) minimizing, locally risk minimizing, and variance minimizing strategies in tracking stock indices are investigated using both simulated and historical market data. In particular, it is shown using S&P500 data over the period 2000 and 2015 that the TEV of the variance minimizing strategy is statistically lower than other strategies at the 95% confidence level for 6-month holding periods.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/158661