Harvey, AndrewRuiz Ortega, EstherShephard, Neil2009-07-152009-07-151995ARCH: Selected readings, 1995, p. 256-2769780198774327019877432Xhttps://hdl.handle.net/10016/4783Publicado además en: The Review of Economic Studies, 1994, vol. 61, n. 2, p. 247-264Publicado además en: Recent developments in Time Series, 2003, vol. 2, pp. 134-152Publicado además en: Selected Readings for Stochastic Volatility, 2005, p. 156-176, ISBN10: 0199257191, ISBN13: 9780199257195Changes in variance, or volatility, over time can be modeled using the approach based on autoregressive conditional heteroscedasticity. Another approach is to model variance as an unobserved stochastic process. Although it is not easy to obtain the exact likelihood function for such stochastic variance models, they tie in closely with developments in finance theory and have certain statistical attractions. This article sets up a multivariate model, discusses its statistical treatment, and shows how it can be modified to capture common movements in volatility in a very natural way. The model is then fitted to daily observations on exchange rates.application/pdfengModel Construction and Estimation (C510)Multiple or Simultaneous Equation ModelsTime-Series ModelsDynamic Quantile Regressions (C320)Foreign Exchange (F310)book partEstadísticaopen access