9. Heteroskedasticity

  1. Ngai Hang Chan

Published Online: 28 JAN 2011

DOI: 10.1002/9781118032466.ch9

Time Series: Applications to Finance with R and S-Plus, Second Edition

Time Series: Applications to Finance with R and S-Plus, Second Edition

How to Cite

Chan, N. H. (2010) Heteroskedasticity, in Time Series: Applications to Finance with R and S-Plus, Second Edition, John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9781118032466.ch9

Author Information

  1. The Chinese University of Hong Kong, Department of Statistics, Shatin, Hong Kong

Publication History

  1. Published Online: 28 JAN 2011
  2. Published Print: 13 SEP 2010

ISBN Information

Print ISBN: 9780470583623

Online ISBN: 9781118032466

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Keywords:

  • ARCH model;
  • foreign exchange rates;
  • GARCH model;
  • heteroskedasticity;
  • stochastic volatility model

Summary

Similar to linear regression analysis, many time series exhibit a heteroskedastic (nonconstant variance) structure. This chapter discusses the popular time series models for heteroskedasticity: ARCH and GARCH models. There are other alternatives that can be used to capture the heteroskedastic effects: for example, the stochastic volatility model. The chapter also talks about three simple approaches such as time series test, Portmanteau tests for residuals and Lagrange multiplier test. It presents an example of foreign exchange rates in which the weekly exchange rates of the U.S. dollar and British pound sterling between the years 1980 and 1988 are studied.

Controlled Vocabulary Terms

ARCH model; foreign exchange rates; GARCH Model; stochastic volatility model