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عنوان انگلیسی مقاله:
A simple model for now-casting volatility series
سال انتشار : 2016
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5. Finite sample properties
In this section, we compare the finite sample properties of alternative estimators for volatilities. The data are generated as yt = e ht /2 ξt t = 1, . . . , T , where ht may be ARMA : ht = α + βht−1 + κεt, (30) SV : ht = α + βht−1 + ηt, (31) or EGARCH : ht = α + βht−1 + ψ|ξt−1|. (32) The error process εt = log(ξ 2 t ) + 1.27 with ξt i.i.d. ∼ N(0, 1) is independent of ηt i.i.d. ∼ N(0, σ 2 η ). Accordingly, in the stochastic volatility model (SV), xt = log y 2 t is composed of two independent processes, whereas in the ARMA model, xt is driven by a single stochastic process εt . First, consider the case where the generated volatility is a classical stochastic volatility process. We follow Sandmann and Koopman (1998) in specifying the parameters of the SV model. Defining the coefficient of variation as CV = Var[exp(ht)]/E[exp(ht)] 2 , one obtains the expression CV = exp(σ 2 η /(1 − β 2 )) − 1. The coefficient of variation for this model is related directly to the kurtosis of yt , which is given by κ = 3(CV + 1). Here, α is an irrelevant scaling parameter, but Sandmann and Koopman (1998) determine α such that E[exp(ht)] = 0.0009, which gives a realistic annualized standard deviation of 22% for generated weekly data. To distinguish between highly and moderately persistent volatility processes, we fix β alternatively at 0.98 and 0.90. Similarly, we evaluate the effects of high versus low coefficients of variation (or, equivalently, high versus low kurtosis) by fixing CV alternatively at 10 and 1, with corresponding kurtosis coefficients of 33 and 6, respectively. This gives four different parameterizations. The sample sizes are T = 500 and 2000. Each process is simulated k = 1000 times.
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کلمات کلیدی:
A Simple Model for Now-Casting Volatility Series - EconPapers - RePEc econpapers.repec.org/RePEc:cor:louvco:2016004 by J Breitung - 2015 - Related articles Sep 14, 2016 - By Jörg Breitung and Christian M. Hafner; Abstract: Popular volatility models focus on the conditional variance given past observations, ... A simple model for now-casting volatility series www.wisostat.uni-koeln.de/fileadmin/sites/statistik/armavol15.pdf by J Breitung - 2014 - Related articles Dec 18, 2014 - cess that these models encounter in modelling financial time series, but also by the ... In other words, nowcasting volatility in the GARCH model. [PDF]A simple model for now-casting volatility series - ResearchGate https://www.researchgate.net/...model_for_now-casting_volatility_series/.../A-simple-... cess that these models encounter in modelling financial time series, but also by the non- exhausted ... In other words, nowcasting volatility in the GARCH model. A simple model for now-casting volatility series - EconBiz https://www.econbiz.de/.../a...model-for-now-casting-volatility-series.../10010484185 A simple model for now-casting volatility series ... graph. Darst. Series: CORE discussion papers : DP. - Louvain-la-Neuve, ZDB-ID 2220482-9. - Vol. 2014,60. A simple model for now-casting volatility series | DIAL.pr - BOREAL dial.uclouvain.be/handle/boreal:167774 Document type, : Document de travail (Working Paper). Abstract, : Popular volatility models focus on the conditional variance given past observations, whereas ... International Journal of Forecasting - Statistics Portal // Luxembourg ... www.statistiques.public.lu › Home › Publications Oct 4, 2016 - 1234-1246; BREITUNG Jörg, HAFNER Christian M. - A simple model for now-casting volatility series, pp. 1247-1255; WILMS Ines, CROUX ... [PDF]Now-casting and the real-time data flow - European Central Bank https://www.ecb.europa.eu/pub/pdf/scpwps/ecbwp1564.pdf?... Information on all of the papers published in the ECB Working Paper Series can ... developments in economic now-casting with special focus on those models that ...... especially for daily data, consists in modeling stochastic volatility and rare ...
