Publication Type
Book Chapter
Version
publishedVersion
Publication Date
2000
Abstract
If financial time series exhibits persistence or long-memory, then their unconditional probability distribution may not be normal. This has important implications for many areas in finance, especially asset pricing, option pricing, portfolio allocation and risk management. Furthermore, if the random walk does not apply, a wide range of results obtained by quantitative analysis may be inappropriate. The capital asset pricing model, the Black-Scholes option pricing formula, the concept of risk as standard deviation or volatility, and the use of Sharpe, Treynor, and other performance measures are not consistent with nonnormal distributions. Unfortunately, nonnormality is common among distributions of financial time series according to observations from empirical studies of financial series.
Keywords
Financial time series, Finance, Statistical Computing, Statistical Programs, Statistics, XploRe
Discipline
Finance and Financial Management
Research Areas
Quantitative Finance
Publication
XploRe: Applications Guide
Editor
Hardle, Wolfgang; Hlávka, Zděnk; Klinke, Sigbert
First Page
377
Last Page
396
ISBN
9783540675457
Identifier
10.1007/978-3-642-57292-0_15
Publisher
Springer
City or Country
Berlin
Citation
Lee, David Kuo Chuen. 2000. "ExploRing Persistence in Financial Time Series." In XploRe : application guide, edited by W. Härdle, Z. Hlávka, and S. Klinke. Berlin: Springer.
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1007/978-3-642-57292-0_15
Comments
Edited by W. Härdle, Z. Hlávka, and S. Klinke