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Limit Theorems for Quadratic Variations of the Lei–Nualart Process

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Stochastic Processes and Applications (SPAS 2017)

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 271))

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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

$$V_{n}=\sum _{k=0}^{n-1}\left[ n^{2H}(\varDelta _k X)^{2}-n^{2H}\mathrm {I\! E}(\varDelta _k X)^{2}\right] .$$

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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Correspondence to Khalifa Es-Sebaiy .

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Appendix

Appendix

Proof

 (Proof of Lemma 5.2) (i) We have

$$ \alpha (x,x) = (2x+2)^{2H} - 2(2x+1)^{2H} + (2x)^{2H}. $$

Hence by applying Taylor’s theorem we observe

$$ \alpha (x,x) = 2H(2H-1)(2x)^{2H-2} + O(x^{2H-3}) $$

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

$$\begin{aligned} \begin{aligned} \partial _x \alpha (x,y) = 2H\left[ (x+y+2)^{2H-1}-(x+y+1)^{2H-1} \right. \\ \left. -(x+y+1)^{2H-1}+(x+y)^{2H-1}\right] \\ = 2H\left[ z_y(x+1) - z_y(x)\right] , \end{aligned} \end{aligned}$$

where \( z_y(x) = (x+y+1)^{2H-1} - (x+y)^{2H-1}. \) Here

$$ z'_y(x) = (2H-1)\left[ (x+y+1)^{2H-2} - (x+y)^{2H-2}\right] \le 0, $$

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 \(H\in (0,1)\setminus \{\frac{1}{2}\}\),

$$\mathrm {I\! E}[V_{n}^{2}] =\frac{1}{2}\sum _{r,k=0}^{n-1}\alpha (k,r)^{2}=\sum _{r<k}^{n-1}\alpha (k,r)^{2}+\frac{1}{2}\sum _{k=0}^{n-1}\alpha (k,k)^{2} = I(n)+J(n).$$

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

$$ J(n) \le C \sum _{k=1}^{n-1} k^{-1} \le C\log n, $$

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

$$ \frac{1}{n}\sum _{r<k}^{n-1} (k+r)^{-2} \le \frac{C}{n} \sum _{k=1}^{n-1} k^{-1} \le \frac{C \log n}{n} \rightarrow 0 $$

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

$$ \sum _{r<k}^{n-1} (k+r)^{-1} = \sum _{k=0}^{n-1} \sum _{s=k+1}^{2k-1} s^{-1}. $$

Changing the order of summation we get

$$ \sum _{k=0}^{n-1} \sum _{s=k+1}^{2k-1} s^{-1} = \sum _{s=1}^{2n-3} \sum _{\frac{s+1}{2}\le k \le s-1} s^{-1}. $$

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

$$ \sum _{r<k}^{n-1}\alpha (k,k)^2 \le \sum _{r<k}^{n-1} \alpha (k,r)^2 \le \sum _{r<k}^{n-1}\alpha (r,r)^2. $$

Here

$$ \sum _{r<k}^{n-1}\alpha (k,k)^2 \ge C\sum _{k=1}^{n-1} \left[ k k^{4H-4} + O(k^{4H-4})\right] . $$

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

$$ \sum _{r<k}^{n-1}\alpha (r,r)^2 \le C\sum _{r=1}^{n-1}(n-r)r^{4H-4} \le Cn^{4H-2} $$

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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