Abstract
Let X be a Lei–Nualart process with Hurst index \(H\in (0, 1)\), \(Z_{1}\) be an Hermite random variable. For any \(n \ge 1\), set
The aim of the current paper is to derive, in the case when the Hurst index verifies \(H > 3/4\), an upper bound for the total variation distance between the laws \(\mathcal {L}(Z_n)\) and \(\mathcal {L}(Z_{1})\), where \(Z_{n}\) stands for the correct renormalization of \(V_{n}\) which converges in distribution towards \(Z_{1}\). We derive also the asymptotic behavior of quadratic variations of process X in the critical case \(H=3/4\), i.e. an upper bound for the total variation distance between the \(\mathcal {L}(Z_n)\) and the Normal law.
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Appendix
Appendix
Proof
(Proof of Lemma 5.2) (i) We have
Hence by applying Taylor’s theorem we observe
from which the claim follows.
(ii) We show that for any fixed x (resp. y), the function \(x \mapsto \alpha (x,y)\) (resp. \(y\mapsto \alpha (x,y)\)) is decreasing provided that \(H\in \left[ \frac{3}{4},1\right) \). For this, let y be fixed. Then
where \( z_y(x) = (x+y+1)^{2H-1} - (x+y)^{2H-1}. \) Here
and thus \(z_y(x)\) is decreasing. This implies that \(\alpha (x,y)\) is also decreasing as a function of x. Furthermore, by changing the roles of x and y we observe that for each fixed x, the function \(y \mapsto \alpha (x,y)\) is also decreasing. Consequently, for every \(0\le x \le y\) we have \( \alpha (y,y) \le \alpha (x,y) \le \alpha (x,x). \) \(\square \)
Proof
(Proof of Lemma 5.3) Using (5.3) and (5.4) we have, for any \(H\in (0,1)\setminus \{\frac{1}{2}\}\),
The idea is to show that, depending on the value of H, the term I(n) behaves asymptotically correctly while the term J(n) is negligible.
(i) Case \(H=\frac{3}{4}\): By Lemma 5.2 item (i) we have
and hence, as \(n\rightarrow \infty \), \( \frac{J(n)}{n}\rightarrow 0. \) For the term I(n) we have \( \alpha (r,k)^2 = (k+r)^{-1} + O\left( (k+r)^{-2}\right) . \) Here
and consequently the term \(O\left( (k+r)^{-2}\right) \) does not affect the asymptotic variance. For the term \((k+r)^{-1}\) we substitute \(s = k+r\) to get
Changing the order of summation we get
Here \( \sum _{\frac{s+1}{2}\le k \le s-1} 1 = \frac{s}{2} - \frac{1}{2} \) if s is odd and \( \sum _{\frac{s+1}{2}\le k \le s-1} 1 = \frac{s}{2} \) if s is even. This implies \( c n \le \sum _{r<k}^{n-1} (k+r)^{-1} \le Cn. \)
(ii) Case \(\frac{3}{4}< H<1\): By Lemma 5.2 item (i) we have \( J(n) \le C \sum _{k=1}^{n-1} k^{4H-4} \le Cn^{4H-3} \) since \(4H-4>-1\). Hence, as \(n\rightarrow \infty \), \( \frac{J(n)}{n^{4H-2}}\rightarrow 0. \) For the term I(n) we use Lemma 5.2 item (ii) to observe that
Here
Here \( \frac{1}{n^{4H-2}} \sum _{k=1}^{n-1}k^{4H-4} \le Cn^{-1} \rightarrow 0 \) from which it follows that \( \sum _{r<k}^{n-1}\alpha (k,k)^2 \ge c n^{4H-2}. \) On the other hand, we have
from which the claim follows. \(\square \)
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Bajja, S., Es-Sebaiy, K., Viitasaari, L. (2018). Limit Theorems for Quadratic Variations of the Lei–Nualart Process. In: Silvestrov, S., Malyarenko, A., Rančić, M. (eds) Stochastic Processes and Applications. SPAS 2017. Springer Proceedings in Mathematics & Statistics, vol 271. Springer, Cham. https://doi.org/10.1007/978-3-030-02825-1_5
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