Estimation in Financial Models - RiskLab
Estimation in Financial Models - RiskLab
Estimation in Financial Models - RiskLab
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conditions for the cont<strong>in</strong>uity of the sample paths of X t and the denitions<br />
for a h and b h . Later we will refer to these conditions as Nelson-conditions.<br />
Now as an application of Theorem 1 Nelson [54] nds and analyzes the diffusion<br />
limit of GARCH(1,1)-type processes.<br />
The GARCH(1,1)-M process of Engle and Bollerslev (see [13]) is dened as<br />
where f" t gN(0; 1) iid.<br />
Y t = Y t,1 + c 2 t + t " t ; (2.1)<br />
2 t+1<br />
= + 2 t<br />
h<br />
+ "<br />
2<br />
t<br />
i<br />
; (2.2)<br />
Now our purpose is to reduce the length of the time <strong>in</strong>tervals more and more.<br />
The parameters , and of the system may depend on h. The drift term<br />
<strong>in</strong> (2.1) and the variance of " t are made proportional to h:<br />
Y kh = Y (k,1)h + h ckh 2 + kh " kh ; (2.3)<br />
<br />
(k+1)h 2 = h + kh<br />
2 h + <br />
h<br />
h "2 kh ; (2.4)<br />
where f" kh gN(0;h) iid and as for the <strong>in</strong>itial distribution (k =0)wehave<br />
P h (Y 0 ; 2 0) 2 A i = h (A)<br />
and (h) 2<br />
t are con-<br />
for all A 2 B(IR 2 ). The cont<strong>in</strong>uous time processes Y (h)<br />
t<br />
structed by<br />
Y (h)<br />
t Y kh and (h) 2<br />
t <br />
2<br />
kh<br />
for kh t 0:<br />
h#0<br />
11