<p>Let (<i>Z</i><Stack> <sub><i>t</i></sub> <sup><i>H</i></sup> </Stack>, <i>t</i> ⩾ 0) be the Rosenblatt process with Hurst index <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(H\in({{1}\over{2}},1)\)</EquationSource> <EquationSource Format="MATHML"><math display="block"> <mi>H</mi> <mo>∈</mo> <mo stretchy="false">(</mo> <mrow> <mfrac> <mrow> <mn>1</mn> </mrow> <mrow> <mn>2</mn> </mrow> </mfrac> </mrow> <mo>,</mo> <mn>1</mn> <mo stretchy="false">)</mo> </math></EquationSource> </InlineEquation>. We analyze the limit behavior of the oscillation of the Rosenblatt process given by <i>X</i><Stack> <sub><i>t</i></sub> <sup><i>H,ε</i></sup> </Stack> = <i>ε</i><sup>−<i>H</i></sup> (<i>Z</i><Stack> <sub><i>t</i>+<i>ε</i></sub> <sup><i>H</i></sup> </Stack> − <i>Z</i><Stack> <sub><i>t</i></sub> <sup><i>H</i></sup> </Stack>) with <i>ε</i> &gt; 0 and <i>t</i> ⩾ 0. Based on the Wiener chaos expansion, we prove that the quantity <InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(M_{Q} (X^{\varepsilon})= \int_{0}^{1} Q (X ^{\varepsilon}_{t}) \,{\rm d}t\)</EquationSource> <EquationSource Format="MATHML"><math display="block"> <msub> <mi>M</mi> <mrow> <mi>Q</mi> </mrow> </msub> <mo stretchy="false">(</mo> <msup> <mi>X</mi> <mrow> <mi>ε</mi> </mrow> </msup> <mo stretchy="false">)</mo> <mo>=</mo> <msubsup> <mo>∫</mo> <mrow> <mn>0</mn> </mrow> <mrow> <mn>1</mn> </mrow> </msubsup> <mi>Q</mi> <mo stretchy="false">(</mo> <msubsup> <mi>X</mi> <mrow> <mi>t</mi> </mrow> <mrow> <mi>ε</mi> </mrow> </msubsup> <mo stretchy="false">)</mo> <mspace width="thinmathspace" /> <mrow> <mrow> <mi mathvariant="normal">d</mi> </mrow> </mrow> <mi>t</mi> </math></EquationSource> </InlineEquation> converges as <i>ε</i> → 0, almost surely and in <i>L</i><sup>q</sup>(Ω) for any <i>q</i> ⩾ 1, to <b>E</b><i>Q</i>(<i>Z</i><Stack> <sub>1</sub> <sup><i>H</i></sup> </Stack>) for any polynomial function <i>Q</i> with <b>E</b><i>Q</i>(<i>Z</i><Stack> <sub>1</sub> <sup><i>H</i></sup> </Stack>) &lt; ∞. We also obtain a second order result, i.e., after a proper renormalization, the quantity <i>M</i><sub><i>Q</i></sub>(<i>X</i><sup><i>ε</i></sup>) − <b>E</b><i>Q</i>(<i>Z</i><Stack> <sub>1</sub> <sup><i>H</i></sup> </Stack>) converges as <i>ε</i> → 0, almost surely and in <i>L</i><sup><i>q</i></sup>(Ω) for any <i>q</i> ⩾ 1, to a Rosenblatt-distributed random variable.</p>

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Non-central limit theorem for the oscillation of the Rosenblatt process

  • Héctor Araya,
  • Ciprian A. Tudor

摘要

Let (Z t H , t ⩾ 0) be the Rosenblatt process with Hurst index \(H\in({{1}\over{2}},1)\) H ( 1 2 , 1 ) . We analyze the limit behavior of the oscillation of the Rosenblatt process given by X t H,ε = εH (Z t+ε H Z t H ) with ε > 0 and t ⩾ 0. Based on the Wiener chaos expansion, we prove that the quantity \(M_{Q} (X^{\varepsilon})= \int_{0}^{1} Q (X ^{\varepsilon}_{t}) \,{\rm d}t\) M Q ( X ε ) = 0 1 Q ( X t ε ) d t converges as ε → 0, almost surely and in Lq(Ω) for any q ⩾ 1, to EQ(Z 1 H ) for any polynomial function Q with EQ(Z 1 H ) < ∞. We also obtain a second order result, i.e., after a proper renormalization, the quantity MQ(Xε) − EQ(Z 1 H ) converges as ε → 0, almost surely and in Lq(Ω) for any q ⩾ 1, to a Rosenblatt-distributed random variable.