By Gilles Teyssière, Alan P. Kirman
While utilising the statistical idea of lengthy variety based (LRD) procedures to economics, the robust complexity of macroeconomic and fiscal variables, in comparison to typical LRD strategies, turns into obvious. with a view to get a greater realizing of the behaviour of a few financial variables, the booklet assembles 3 diverse strands of lengthy reminiscence research: statistical literature at the homes of, and checks for, LRD methods; mathematical literature at the stochastic approaches concerned; types from financial conception supplying believable micro foundations for the occurence of lengthy reminiscence in economics. every one bankruptcy of the publication will supply a accomplished survey of the cutting-edge and the instructions that destiny advancements tend to take. Taken as a complete the booklet presents an outline of LRD tactics that's obtainable to economists, econometricians and statisticians.
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Example text
114. Surgailis, D. -C. (2002). Long memory properties and covariance structure of the EGARCH model. ESAIM: Probability and Statistics, 6, 311– 329. 115. S. B. (1986). Using renewal processes to generate longrange dependence and high variability. In Dependence in Probability and Statistics (eds E. Eberlein and M. S. Taqqu), pp. 73–89. Birkh¨ auser, Boston. 116. Taylor, S. (1986). Modelling Financial Time Series. Wiley, New York. 117. Ter¨ asvirta, T. (1996). Two stylized facts and the GARCH(1,1) model.
And Subba Rao, S. (2003). Statistical inference for time-varying ARCH processes. Annals of Statistics, forthcoming. 30. Davidson, J. (2004). Moment and memory properties of linear conditional heteroscedasticity models, and a new model. Preprint. 31. Davidson, J. and Sibbertsen, Ph. (2002). Generating schemes for long memory processes: regimes, aggregation and linearity. Preprint. 32. X. and Inoue, A. (2001). Long memory and regime switching. Journal of Econometrics, 105, 131–159. 33. Ding, Z. and Granger, C.
B. (1986). Using renewal processes to generate longrange dependence and high variability. In Dependence in Probability and Statistics (eds E. Eberlein and M. S. Taqqu), pp. 73–89. Birkh¨ auser, Boston. 116. Taylor, S. (1986). Modelling Financial Time Series. Wiley, New York. 117. Ter¨ asvirta, T. (1996). Two stylized facts and the GARCH(1,1) model. Stockholm School of Economics. SSE/EFI Working Paper Series in Economics and Finance, No. 96. 38 Liudas Giraitis, Remigijus Leipus, and Donatas Surgailis 118.