Title

ExploRing Persistence in Financial Time Series

Publication Type

Book Chapter

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

Additional URL

http://dx.doi.org/10.1007/978-3-642-57292-0_15

Comments

Edited by W. Härdle, Z. Hlávka, and S. Klinke