Estimating Historical Volatility
The research considers the properties of a number of statistical measures of volatility, extending from the common standard deviation metric to less widely used range-based measures. Prior research in this field, which has typically featured the use of data series generated by Monte Carlo simulation within the theoretical framework of Geometric Brownian Motion, has tended towards the conclusion that alternate volatility estimators offer substantial efficiency improvements relative to the standard deviation estimator. This research indicates, however, that such findings are critically dependent on the assumptions made with regard to the nature of the underlying process of interest. The research considers the effect that departures from the behavior of the idealized Geometric Brownian Motion process may have on the performance of a variety of volatility estimators
Year of publication: |
2023
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Authors: | Brandt, Michael W. ; Kinlay, J |
Publisher: |
[S.l.] : SSRN |
Saved in:
freely available
Extent: | 1 Online-Ressource (44 p) |
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Type of publication: | Book / Working Paper |
Language: | English |
Notes: | Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments March 10, 2005 erstellt |
Other identifiers: | 10.2139/ssrn.4384038 [DOI] |
Classification: | C13 - Estimation ; c58 |
Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10014254197
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