Statistical Analysis of Daily Exchange Rate Data

Christian Ullrich ()
Additional contact information
Christian Ullrich: BMW AG

Chapter 8 in Forecasting and Hedging in the Foreign Exchange Markets, 2009, pp 47-63 from Springer

Abstract: A A time series {y t } is a discrete time continuous state process where the variable y is identified by the value that it takes at time t denoted y t . Time is taken at equally spaced intervals from –∞ to +∞ and the finite sample size T of data on y is for t = 1,2, . . . ,T. Time series {y t } may emerge from deterministic and/or stochastic influences. For example, a time trend y t = t is a very simple deterministic time series. If {y t } is generated by a deterministic linear process, it has high predictability, and its future values can be forecasted very well from the past values. A basic stochastic time series is “white noise,” yt = εt , where εt is an independent and identically distributed (i.i.d.) variable with mean 0 and variance σ2 for all t, written εt ~ i.i.d.(0, σ2). A special case is “Gaussian white noise,” where the εt are independent and normally distributed variables with mean 0 and variance σ2 for all t, written εt ~ NID(0, σ2). A time series generated by a stochastic process has low predictability, and its past values provide only a statistical characterization of the future values. Predictability of a time series can therefore be considered as the signal strength of the deterministic component of the time series to the whole time series. Usually, a given time series is not simply deterministic or stochastic, but rather some combination of both: (8.1) $$y_t = \alpha + \beta _t + \varepsilon _t$$

Keywords: Exchange Rate; Unit Root Test; GARCH Model; Conditional Variance Equation; GARCH Volatility (search for similar items in EconPapers)
Date: 2009
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:lnechp:978-3-642-00495-7_8

Ordering information: This item can be ordered from
http://www.springer.com/9783642004957

DOI: 10.1007/978-3-642-00495-7_8

Access Statistics for this chapter

More chapters in Lecture Notes in Economics and Mathematical Systems from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().