Multifractality of US Dollar/Deutsche Mark Exchange Rates - Studies2
Multifractality of US Dollar/Deutsche Mark Exchange Rates - Studies2
Multifractality of US Dollar/Deutsche Mark Exchange Rates - Studies2
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their distribution is usually specified Student t rather than Gaussian. In simulation, we assume<br />
independence for lack <strong>of</strong> an explicit alternative, and use the Gaussian for ut. These assumptions<br />
should not qualitatively affect our conclusions.<br />
rewrite<br />
where<br />
For FIGARCH(1,d,0), (12) can be written more intuitively. Starting with<br />
(1 − L) d ε 2 t = ω +[1− β1L] vt,<br />
σ 2 t =<br />
<br />
ω − β1vt−1 + 1 − (1 − L) d<br />
ε 2 t<br />
=<br />
∞<br />
ω − β1vt−1 − ψkε 2 t−k .<br />
ψk =<br />
k=1<br />
Γ(k − d)<br />
Γ(k +1)Γ(−d)<br />
The ARMA representation in volatility clarifies how simulation proceeds, and how long memory<br />
arises. (Plotting ψk will help readers gain further intuition for the process.) Because the Gamma<br />
function is smooth, the path <strong>of</strong> volatility is also smooth. This is the property that leads to clumping<br />
<strong>of</strong> like-sized returns.<br />
Like ARFIMA, FIGARCH is a hybrid from the scaling point <strong>of</strong> view. For ARFIMA, intuition<br />
is clear since it is asymptotically equivalent in increments to Fractional Gaussian Noise. Short<br />
memory components are non-scaling, but become negligible over long sampling increments. This<br />
intuition disappears for FIGARCH since squared increments are asymptotically scaling, not incre-<br />
ments themselves.<br />
An alternative intuition is the literature on diffusion limits <strong>of</strong> ARCH sequences. The continuous<br />
time limit <strong>of</strong> discrete GARCH sequences is an Itô diffusion or jump-diffusion in certain cases.<br />
(Nelson, 1990; Drost and Nijman, 1996). Intuitively, GARCH is not scaling since Itô diffusions are<br />
not scaling. 37 Continuous time limits <strong>of</strong> FIGARCH, on the other hand, are not known. 38<br />
Twenty simulated partition functions, appearing in Figure 19, are used to investigate the scaling<br />
properties <strong>of</strong> FIGARCH. Each simulations consists <strong>of</strong> 100,000 observations, allowing like comparison<br />
37<br />
A reference is not available, but intuitively, it results from smoothness <strong>of</strong> volatility.<br />
38<br />
Nelson (1990) notes that his method <strong>of</strong> demonstrating convergence to a continuous time diffusion does not apply<br />
to long memory processes.<br />
27