Modelling and Forecasting High Frequency Financial Data by Stavros Degiannakis & Christos Floros

Author:Stavros Degiannakis & Christos Floros
Language: eng
Format: epub
ISBN: 9781137396501
Publisher: Palgrave Macmillan
Published: 2015-03-18T16:00:00+00:00

Table 4.1 (B). The probability (1−p) that the minimum X(1) of a trivariate gamma vector is less than or equal to ω1−p for 2 ≥ ω1−p ≥ 50, 5 ≥ a ≥ 50, and ρ1,2 = 95%, ρ1,3 = 95% and ρ2,3 = 95%, the non-diagonal elements of C123.

FX(1) (ω1−p;a,C123) = P(X(1) ≤ ω1−p) = 1−p

where for Pt denoting the price of the asset at time t, μt is the conditional mean estimation, and εt is the unpredictable component σt is the conditional standard deviation which isame a sure of volatility estimation of yt (expressed as a time-varying, positive and measurable function of the information set at time t−1), μ(.) and g(.) are linear or nonlinear functional forms of It−1, and N (.) is the normal density function of zt.

Consider the standardized one-step-ahead prediction errors zt+1|t ≡ (yt+1|t−yt) , where yt+1|t is the one-step-ahead forecast of yt , and σt+1|t is the

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