Pub Date : 2026-05-01Epub Date: 2026-01-17DOI: 10.1016/j.spa.2026.104888
Zhishui Hu , Hanying Liang , Qiying Wang
On the convergence to stochastic integrals, semi-martingale structure is imposed in most of previous literature. This semi-martingale structure is restrictive in many statistical and econometric applications, particularly in the field of cointegration. In this paper, we investigate the convergence to stochastic integrals beyond the semi-martingale structure. In particular, we consider the convergence of stochastic integrals with general linear process innovations, allowing for long memory, short memory and antipersistence processes in a unified framework.
{"title":"Limit theorems for stochastic integrals with long memory processes","authors":"Zhishui Hu , Hanying Liang , Qiying Wang","doi":"10.1016/j.spa.2026.104888","DOIUrl":"10.1016/j.spa.2026.104888","url":null,"abstract":"<div><div>On the convergence to stochastic integrals, semi-martingale structure is imposed in most of previous literature. This semi-martingale structure is restrictive in many statistical and econometric applications, particularly in the field of cointegration. In this paper, we investigate the convergence to stochastic integrals beyond the semi-martingale structure. In particular, we consider the convergence of stochastic integrals with general linear process innovations, allowing for long memory, short memory and antipersistence processes in a unified framework.</div></div>","PeriodicalId":51160,"journal":{"name":"Stochastic Processes and their Applications","volume":"195 ","pages":"Article 104888"},"PeriodicalIF":1.2,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146023275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We examine the sensitivity at the origin of the distributional robust optimization problem in the context of a model generated by a mean field stochastic differential equation. We adapt the finite dimensional argument developed by Bartl, Drapeau, Obloj, & Wiesel to our framework involving the infinite dimensional gradient of the solution of the mean field SDE with respect to its initial data. We revisit the derivation of this gradient process as previously introduced by Buckdahn, Li, Peng, & Rainer and we complement the existing properties so as to satisfy the requirement of our main result. We use the theory developed in the context of a mean-field systemic risk model by evaluating the sensitivity with respect to the initial distribution for the variance of the log-monetary reserve of a representative bank.
{"title":"Sensitivity of functionals of McKean-Vlasov SDEs with respect to the initial distribution","authors":"Filippo de Feo , Salvatore Federico , Fausto Gozzi , Nizar Touzi","doi":"10.1016/j.spa.2025.104868","DOIUrl":"10.1016/j.spa.2025.104868","url":null,"abstract":"<div><div>We examine the sensitivity at the origin of the distributional robust optimization problem in the context of a model generated by a mean field stochastic differential equation. We adapt the finite dimensional argument developed by Bartl, Drapeau, Obloj, & Wiesel to our framework involving the infinite dimensional gradient of the solution of the mean field SDE with respect to its initial data. We revisit the derivation of this gradient process as previously introduced by Buckdahn, Li, Peng, & Rainer and we complement the existing properties so as to satisfy the requirement of our main result. We use the theory developed in the context of a mean-field systemic risk model by evaluating the sensitivity with respect to the initial distribution for the variance of the log-monetary reserve of a representative bank.</div></div>","PeriodicalId":51160,"journal":{"name":"Stochastic Processes and their Applications","volume":"195 ","pages":"Article 104868"},"PeriodicalIF":1.2,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145927916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-05-01Epub Date: 2026-01-06DOI: 10.1016/j.spa.2026.104872
Yinshan Chang
We consider the one-dimensional Littlewood-Offord problem for general Ising models. More precisely, we consider the concentration functionwhere , are real numbers such that , and are random spins of some Ising model. Let . Under natural assumptions, we show that there exists a universal constant C such that for all n ≥ 1,As an application of the method, under the same assumption, we give a lower bound on the smallest eigenvalue of the truncated correlation matrix of the Ising model.
{"title":"Littlewood-Offord problems for Ising models","authors":"Yinshan Chang","doi":"10.1016/j.spa.2026.104872","DOIUrl":"10.1016/j.spa.2026.104872","url":null,"abstract":"<div><div>We consider the one-dimensional Littlewood-Offord problem for general Ising models. More precisely, we consider the concentration function<span><span><span><math><mtable><mtr><mtd><mrow><msub><mi>Q</mi><mi>n</mi></msub><mrow><mo>(</mo><mi>x</mi><mo>,</mo><mi>v</mi><mo>)</mo></mrow><mo>=</mo><mi>P</mi><mrow><mo>(</mo><munderover><mo>∑</mo><mrow><mi>i</mi><mo>=</mo><mn>1</mn></mrow><mi>n</mi></munderover><msub><mrow><mi>ε</mi></mrow><mi>i</mi></msub><msub><mi>v</mi><mi>i</mi></msub><mo>∈</mo><mrow><mo>(</mo><mi>x</mi><mo>−</mo><mn>1</mn><mo>,</mo><mi>x</mi><mo>+</mo><mn>1</mn><mo>)</mo></mrow><mo>)</mo></mrow><mo>,</mo></mrow></mtd></mtr></mtable></math></span></span></span>where <span><math><mrow><mi>x</mi><mo>∈</mo><mi>R</mi></mrow></math></span>, <span><math><mrow><msub><mi>v</mi><mn>1</mn></msub><mo>,</mo><msub><mi>v</mi><mn>2</mn></msub><mo>,</mo><mo>…</mo><mo>,</mo><msub><mi>v</mi><mi>n</mi></msub></mrow></math></span> are real numbers such that <span><math><mrow><mrow><mo>|</mo></mrow><msub><mi>v</mi><mn>1</mn></msub><mrow><mo>|</mo><mo>≥</mo><mn>1</mn><mo>,</mo><mo>|</mo></mrow><msub><mi>v</mi><mn>2</mn></msub><mrow><mo>|</mo><mo>≥</mo><mn>1</mn><mo>,</mo><mo>…</mo><mo>,</mo><mo>|</mo></mrow><msub><mi>v</mi><mi>n</mi></msub><mrow><mo>|</mo><mo>≥</mo><mn>1</mn></mrow></mrow></math></span>, and <span><math><mrow><msub><mrow><mo>(</mo><msub><mrow><mi>ε</mi></mrow><mi>i</mi></msub><mo>)</mo></mrow><mrow><mi>i</mi><mo>=</mo><mn>1</mn><mo>,</mo><mn>2</mn><mo>,</mo><mo>…</mo><mo>,</mo><mi>n</mi></mrow></msub><mo>∈</mo><msup><mrow><mo>{</mo><mo>−</mo><mn>1</mn><mo>,</mo><mn>1</mn><mo>}</mo></mrow><mi>n</mi></msup></mrow></math></span> are random spins of some Ising model. Let <span><math><mrow><msub><mi>Q</mi><mi>n</mi></msub><mo>=</mo><msub><mi>sup</mi><mrow><mi>x</mi><mo>,</mo><mi>v</mi></mrow></msub><msub><mi>Q</mi><mi>n</mi></msub><mrow><mo>(</mo><mi>x</mi><mo>,</mo><mi>v</mi><mo>)</mo></mrow></mrow></math></span>. Under natural assumptions, we show that there exists a universal constant <em>C</em> such that for all <em>n</em> ≥ 1,<span><span><span><math><mtable><mtr><mtd><mrow><mrow><mo>(</mo><mfrac><mi>n</mi><mrow><mo>[</mo><mi>n</mi><mo>/</mo><mn>2</mn><mo>]</mo></mrow></mfrac><mo>)</mo></mrow><msup><mn>2</mn><mrow><mo>−</mo><mi>n</mi></mrow></msup><mo>≤</mo><msub><mi>Q</mi><mi>n</mi></msub><mo>≤</mo><mi>C</mi><msup><mi>n</mi><mrow><mo>−</mo><mfrac><mn>1</mn><mn>2</mn></mfrac></mrow></msup><mo>.</mo></mrow></mtd></mtr></mtable></math></span></span></span>As an application of the method, under the same assumption, we give a lower bound on the smallest eigenvalue of the truncated correlation matrix of the Ising model.</div></div>","PeriodicalId":51160,"journal":{"name":"Stochastic Processes and their Applications","volume":"195 ","pages":"Article 104872"},"PeriodicalIF":1.2,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145927915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-05-01Epub Date: 2026-01-04DOI: 10.1016/j.spa.2025.104867
Yan-Xia Ren , Renming Song , Yaping Zhu
In this paper, we investigate the asymptotic behaviors of the survival probability and maximal displacement of a subcritical branching killed Lévy process X in . Let ζ denote the extinction time, Mt be the maximal position of all the particles alive at time t, and be the all-time maximum. Under the assumption that the offspring distribution satisfies the Llog L condition and some conditions on the spatial motion, we find the decay rate of the survival probability and the tail behavior of Mt as t → ∞. As a consequence, we establish a Yaglom-type theorem. We also find the asymptotic behavior of as y → ∞.
{"title":"Asymptotic behaviors of subcritical branching killed Lévy processes","authors":"Yan-Xia Ren , Renming Song , Yaping Zhu","doi":"10.1016/j.spa.2025.104867","DOIUrl":"10.1016/j.spa.2025.104867","url":null,"abstract":"<div><div>In this paper, we investigate the asymptotic behaviors of the survival probability and maximal displacement of a subcritical branching killed Lévy process <em>X</em> in <span><math><mi>R</mi></math></span>. Let <em>ζ</em> denote the extinction time, <em>M<sub>t</sub></em> be the maximal position of all the particles alive at time <em>t</em>, and <span><math><mrow><mi>M</mi><mo>:</mo><mo>=</mo><msub><mi>sup</mi><mrow><mi>t</mi><mo>≥</mo><mn>0</mn></mrow></msub><msub><mi>M</mi><mi>t</mi></msub></mrow></math></span> be the all-time maximum. Under the assumption that the offspring distribution satisfies the <em>L</em>log <em>L</em> condition and some conditions on the spatial motion, we find the decay rate of the survival probability <span><math><mrow><msub><mi>P</mi><mi>x</mi></msub><mrow><mo>(</mo><mi>ζ</mi><mo>></mo><mi>t</mi><mo>)</mo></mrow></mrow></math></span> and the tail behavior of <em>M<sub>t</sub></em> as <em>t</em> → ∞. As a consequence, we establish a Yaglom-type theorem. We also find the asymptotic behavior of <span><math><mrow><msub><mi>P</mi><mi>x</mi></msub><mrow><mo>(</mo><mi>M</mi><mo>></mo><mi>y</mi><mo>)</mo></mrow></mrow></math></span> as <em>y</em> → ∞.</div></div>","PeriodicalId":51160,"journal":{"name":"Stochastic Processes and their Applications","volume":"195 ","pages":"Article 104867"},"PeriodicalIF":1.2,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145927998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-05-01Epub Date: 2026-01-28DOI: 10.1016/j.spa.2026.104895
Marco Romito , Leonardo Tolomeo
We introduce a new notion of irregularity of paths, in terms of control of growth of the size of small balls by means of the occupation measure of the path. This notion ensures Besov regularity of the occupation measure and thus extends the analysis of Catellier and Gubinelli [1] to general Besov spaces. On stochastic processes this notion is granted by suitable properties of local non-determinism.
{"title":"Yet another notion of irregularity through small ball estimates","authors":"Marco Romito , Leonardo Tolomeo","doi":"10.1016/j.spa.2026.104895","DOIUrl":"10.1016/j.spa.2026.104895","url":null,"abstract":"<div><div>We introduce a new notion of irregularity of paths, in terms of control of growth of the size of small balls by means of the occupation measure of the path. This notion ensures Besov regularity of the occupation measure and thus extends the analysis of Catellier and Gubinelli [1] to general Besov spaces. On stochastic processes this notion is granted by suitable properties of local non-determinism.</div></div>","PeriodicalId":51160,"journal":{"name":"Stochastic Processes and their Applications","volume":"195 ","pages":"Article 104895"},"PeriodicalIF":1.2,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146173746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-05-01Epub Date: 2026-01-22DOI: 10.1016/j.spa.2026.104892
Martin Friesen , Stefan Gerhold , Kristof Wiedermann
We study small-time central limit theorems for stochastic Volterra integral equations with Hölder continuous coefficients and general locally square integrable Volterra kernels. We prove the convergence of the finite-dimensional distributions, a functional CLT, and limit theorems for smooth transformations of the process, covering a large class of Volterra kernels including rough models based on Riemann-Liouville kernels with short- or long-range dependencies. To illustrate our results, we derive asymptotic pricing formulae for digital calls on the realized variance in three different regimes. The latter provides a robust and largely model-independent pricing method for small maturities in rough volatility models. Finally, for the case of completely monotone kernels, we introduce a flexible framework of Hilbert space-valued Markovian lifts and derive analogous limit theorems for such lifts. The latter provides new small-time limit theorems for stochastic Volterra processes obtained by transformation of the underlying Volterra kernels.
{"title":"Small-time central limit theorems for stochastic Volterra integral equations and their Markovian lifts","authors":"Martin Friesen , Stefan Gerhold , Kristof Wiedermann","doi":"10.1016/j.spa.2026.104892","DOIUrl":"10.1016/j.spa.2026.104892","url":null,"abstract":"<div><div>We study small-time central limit theorems for stochastic Volterra integral equations with Hölder continuous coefficients and general locally square integrable Volterra kernels. We prove the convergence of the finite-dimensional distributions, a functional CLT, and limit theorems for smooth transformations of the process, covering a large class of Volterra kernels including rough models based on Riemann-Liouville kernels with short- or long-range dependencies. To illustrate our results, we derive asymptotic pricing formulae for digital calls on the realized variance in three different regimes. The latter provides a robust and largely model-independent pricing method for small maturities in rough volatility models. Finally, for the case of completely monotone kernels, we introduce a flexible framework of Hilbert space-valued Markovian lifts and derive analogous limit theorems for such lifts. The latter provides new small-time limit theorems for stochastic Volterra processes obtained by transformation of the underlying Volterra kernels.</div></div>","PeriodicalId":51160,"journal":{"name":"Stochastic Processes and their Applications","volume":"195 ","pages":"Article 104892"},"PeriodicalIF":1.2,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146078391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-05-01Epub Date: 2026-01-11DOI: 10.1016/j.spa.2026.104882
Mathew D. Penrose , Xiaochuan Yang
Let k, d be positive integers. We determine a sequence of constants that are asymptotic to the probability that the cluster at the origin in a d-dimensional Poisson Boolean model with balls of fixed radius is of order k, as the intensity becomes large. Using this, we determine the asymptotics of the mean of the number of components of order k, denoted Sn,k in a random geometric graph on n uniformly distributed vertices in a smoothly bounded compact region of d-dimensional Euclidean space, with distance parameter r(n) chosen so that the expected degree grows slowly as n becomes large (the so-called mildly dense limiting regime). We also show that the variance of Sn,k is asymptotic to its mean, and prove Poisson and normal approximation results for Sn,k in this limiting regime. We provide analogous results for the corresponding Poisson process (i.e. with a Poisson number of points).
We also give similar results in the so-called mildly sparse limiting regime where r(n) is chosen so the expected degree decays slowly to zero as n becomes large.
{"title":"On k-clusters of high-intensity random geometric graphs","authors":"Mathew D. Penrose , Xiaochuan Yang","doi":"10.1016/j.spa.2026.104882","DOIUrl":"10.1016/j.spa.2026.104882","url":null,"abstract":"<div><div>Let <em>k, d</em> be positive integers. We determine a sequence of constants that are asymptotic to the probability that the cluster at the origin in a <em>d</em>-dimensional Poisson Boolean model with balls of fixed radius is of order <em>k</em>, as the intensity becomes large. Using this, we determine the asymptotics of the mean of the number of components of order <em>k</em>, denoted <em>S</em><sub><em>n,k</em></sub> in a random geometric graph on <em>n</em> uniformly distributed vertices in a smoothly bounded compact region of <em>d</em>-dimensional Euclidean space, with distance parameter <em>r</em>(<em>n</em>) chosen so that the expected degree grows slowly as <em>n</em> becomes large (the so-called mildly dense limiting regime). We also show that the variance of <em>S</em><sub><em>n,k</em></sub> is asymptotic to its mean, and prove Poisson and normal approximation results for <em>S</em><sub><em>n,k</em></sub> in this limiting regime. We provide analogous results for the corresponding Poisson process (i.e. with a Poisson number of points).</div><div>We also give similar results in the so-called mildly sparse limiting regime where <em>r</em>(<em>n</em>) is chosen so the expected degree decays slowly to zero as <em>n</em> becomes large.</div></div>","PeriodicalId":51160,"journal":{"name":"Stochastic Processes and their Applications","volume":"195 ","pages":"Article 104882"},"PeriodicalIF":1.2,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146023261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-05-01Epub Date: 2026-01-12DOI: 10.1016/j.spa.2026.104883
David Hobson , Dominykas Norgilas
<div><div>We give an injective martingale coupling; in particular, given measures <em>μ</em> and <em>ν</em> in convex order on <span><math><mi>R</mi></math></span> such that <em>ν</em> is continuous, we construct a martingale transport such that for each <em>y</em> in the support of the target law <em>ν</em> there is a <em>unique x</em> in a support of the initial law <em>μ</em> such that (some of) the mass at <em>x</em> is transported to <em>y</em>. Then <em>π</em> has disintegration <span><math><mrow><mi>π</mi><mrow><mo>(</mo><mi>d</mi><mi>x</mi><mo>,</mo><mi>d</mi><mi>y</mi><mo>)</mo></mrow><mo>=</mo><mi>ν</mi><mrow><mo>(</mo><mi>d</mi><mi>y</mi><mo>)</mo></mrow><msub><mi>δ</mi><mrow><mi>θ</mi><mo>(</mo><mi>y</mi><mo>)</mo></mrow></msub><mrow><mo>(</mo><mi>d</mi><mi>x</mi><mo>)</mo></mrow></mrow></math></span> for some function <em>θ</em>.</div><div>More precisely we construct a martingale coupling <em>π</em> of the measures <em>μ</em> and <em>ν</em> such that there is a set Γ<sub><em>μ</em></sub> such that <span><math><mrow><mi>μ</mi><mo>(</mo><msub><mstyle><mi>Γ</mi></mstyle><mi>μ</mi></msub><mo>)</mo><mo>=</mo><mn>1</mn></mrow></math></span> and a disintegration <span><math><msub><mrow><mo>(</mo><msub><mi>π</mi><mi>x</mi></msub><mo>)</mo></mrow><mrow><mi>x</mi><mo>∈</mo><msub><mstyle><mi>Γ</mi></mstyle><mi>μ</mi></msub></mrow></msub></math></span> of <em>π</em> of the form <span><math><mrow><mi>π</mi><mrow><mo>(</mo><mi>d</mi><mi>x</mi><mo>,</mo><mi>d</mi><mi>y</mi><mo>)</mo></mrow><mo>=</mo><msub><mi>π</mi><mi>x</mi></msub><mrow><mo>(</mo><mi>d</mi><mi>y</mi><mo>)</mo></mrow><mi>μ</mi><mrow><mo>(</mo><mi>d</mi><mi>x</mi><mo>)</mo></mrow></mrow></math></span> such that, with <span><math><msub><mstyle><mi>Γ</mi></mstyle><msub><mi>π</mi><mi>x</mi></msub></msub></math></span> a support of <em>π<sub>x</sub></em>, we have <span><math><mrow><mo>#</mo><mrow><mo>{</mo><mi>x</mi><mo>∈</mo><msub><mstyle><mi>Γ</mi></mstyle><mi>μ</mi></msub><mo>:</mo><mi>y</mi><mo>∈</mo><msub><mstyle><mi>Γ</mi></mstyle><msub><mi>π</mi><mi>x</mi></msub></msub><mo>}</mo></mrow><mo>∈</mo><mrow><mo>{</mo><mn>0</mn><mo>,</mo><mn>1</mn><mo>}</mo></mrow></mrow></math></span> for all <em>y</em> and <span><math><mrow><mrow><mo>{</mo><mi>y</mi><mo>:</mo><mo>#</mo><mrow><mo>{</mo><mi>x</mi><mo>∈</mo><msub><mstyle><mi>Γ</mi></mstyle><mi>μ</mi></msub><mo>:</mo><mi>y</mi><mo>∈</mo><msub><mstyle><mi>Γ</mi></mstyle><msub><mi>π</mi><mi>x</mi></msub></msub><mo>}</mo></mrow><mo>=</mo><mn>1</mn><mo>}</mo></mrow><mo>=</mo><mtext>supp</mtext><mrow><mo>(</mo><mi>ν</mi><mo>)</mo></mrow></mrow></math></span>. Moreover, if <em>μ</em> is continuous we may take <span><math><mrow><msub><mstyle><mi>Γ</mi></mstyle><msub><mi>π</mi><mi>x</mi></msub></msub><mo>=</mo><mtext>supp</mtext><mrow><mo>(</mo><msub><mi>π</mi><mi>x</mi></msub><mo>)</mo></mrow></mrow></math></span> for each <em>x</em>. However, we cannot also insist that <span><math><mrow><msub><mstyle><mi>Γ</mi></mstyle><mi>μ</mi></msub><mo>=</m
{"title":"An injective martingale coupling","authors":"David Hobson , Dominykas Norgilas","doi":"10.1016/j.spa.2026.104883","DOIUrl":"10.1016/j.spa.2026.104883","url":null,"abstract":"<div><div>We give an injective martingale coupling; in particular, given measures <em>μ</em> and <em>ν</em> in convex order on <span><math><mi>R</mi></math></span> such that <em>ν</em> is continuous, we construct a martingale transport such that for each <em>y</em> in the support of the target law <em>ν</em> there is a <em>unique x</em> in a support of the initial law <em>μ</em> such that (some of) the mass at <em>x</em> is transported to <em>y</em>. Then <em>π</em> has disintegration <span><math><mrow><mi>π</mi><mrow><mo>(</mo><mi>d</mi><mi>x</mi><mo>,</mo><mi>d</mi><mi>y</mi><mo>)</mo></mrow><mo>=</mo><mi>ν</mi><mrow><mo>(</mo><mi>d</mi><mi>y</mi><mo>)</mo></mrow><msub><mi>δ</mi><mrow><mi>θ</mi><mo>(</mo><mi>y</mi><mo>)</mo></mrow></msub><mrow><mo>(</mo><mi>d</mi><mi>x</mi><mo>)</mo></mrow></mrow></math></span> for some function <em>θ</em>.</div><div>More precisely we construct a martingale coupling <em>π</em> of the measures <em>μ</em> and <em>ν</em> such that there is a set Γ<sub><em>μ</em></sub> such that <span><math><mrow><mi>μ</mi><mo>(</mo><msub><mstyle><mi>Γ</mi></mstyle><mi>μ</mi></msub><mo>)</mo><mo>=</mo><mn>1</mn></mrow></math></span> and a disintegration <span><math><msub><mrow><mo>(</mo><msub><mi>π</mi><mi>x</mi></msub><mo>)</mo></mrow><mrow><mi>x</mi><mo>∈</mo><msub><mstyle><mi>Γ</mi></mstyle><mi>μ</mi></msub></mrow></msub></math></span> of <em>π</em> of the form <span><math><mrow><mi>π</mi><mrow><mo>(</mo><mi>d</mi><mi>x</mi><mo>,</mo><mi>d</mi><mi>y</mi><mo>)</mo></mrow><mo>=</mo><msub><mi>π</mi><mi>x</mi></msub><mrow><mo>(</mo><mi>d</mi><mi>y</mi><mo>)</mo></mrow><mi>μ</mi><mrow><mo>(</mo><mi>d</mi><mi>x</mi><mo>)</mo></mrow></mrow></math></span> such that, with <span><math><msub><mstyle><mi>Γ</mi></mstyle><msub><mi>π</mi><mi>x</mi></msub></msub></math></span> a support of <em>π<sub>x</sub></em>, we have <span><math><mrow><mo>#</mo><mrow><mo>{</mo><mi>x</mi><mo>∈</mo><msub><mstyle><mi>Γ</mi></mstyle><mi>μ</mi></msub><mo>:</mo><mi>y</mi><mo>∈</mo><msub><mstyle><mi>Γ</mi></mstyle><msub><mi>π</mi><mi>x</mi></msub></msub><mo>}</mo></mrow><mo>∈</mo><mrow><mo>{</mo><mn>0</mn><mo>,</mo><mn>1</mn><mo>}</mo></mrow></mrow></math></span> for all <em>y</em> and <span><math><mrow><mrow><mo>{</mo><mi>y</mi><mo>:</mo><mo>#</mo><mrow><mo>{</mo><mi>x</mi><mo>∈</mo><msub><mstyle><mi>Γ</mi></mstyle><mi>μ</mi></msub><mo>:</mo><mi>y</mi><mo>∈</mo><msub><mstyle><mi>Γ</mi></mstyle><msub><mi>π</mi><mi>x</mi></msub></msub><mo>}</mo></mrow><mo>=</mo><mn>1</mn><mo>}</mo></mrow><mo>=</mo><mtext>supp</mtext><mrow><mo>(</mo><mi>ν</mi><mo>)</mo></mrow></mrow></math></span>. Moreover, if <em>μ</em> is continuous we may take <span><math><mrow><msub><mstyle><mi>Γ</mi></mstyle><msub><mi>π</mi><mi>x</mi></msub></msub><mo>=</mo><mtext>supp</mtext><mrow><mo>(</mo><msub><mi>π</mi><mi>x</mi></msub><mo>)</mo></mrow></mrow></math></span> for each <em>x</em>. However, we cannot also insist that <span><math><mrow><msub><mstyle><mi>Γ</mi></mstyle><mi>μ</mi></msub><mo>=</m","PeriodicalId":51160,"journal":{"name":"Stochastic Processes and their Applications","volume":"195 ","pages":"Article 104883"},"PeriodicalIF":1.2,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145978770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-05-01Epub Date: 2025-12-24DOI: 10.1016/j.spa.2025.104857
Chiara Amorino , Ivan Nourdin , Radomyra Shevchenko
We address the problem of estimating the drift parameter in a system of N interacting particles driven by additive fractional Brownian motion of Hurst index H ≥ 1/2. Considering continuous observation of the interacting particles over a fixed interval [0, T], we examine the asymptotic regime as N → ∞. Our main tool is a random variable reminiscent of the least squares estimator but unobservable due to its reliance on the Skorohod integral. We demonstrate that this object is consistent and asymptotically normal by establishing a quantitative propagation of chaos for Malliavin derivatives, which holds for any H ∈ (0, 1). Leveraging a connection between the divergence integral and the Young integral, we construct computable estimators of the drift parameter. These estimators are shown to be consistent and asymptotically Gaussian. Finally, a numerical study highlights the strong performance of the proposed estimators.
{"title":"Fractional interacting particle system: Drift parameter estimation via Malliavin calculus","authors":"Chiara Amorino , Ivan Nourdin , Radomyra Shevchenko","doi":"10.1016/j.spa.2025.104857","DOIUrl":"10.1016/j.spa.2025.104857","url":null,"abstract":"<div><div>We address the problem of estimating the drift parameter in a system of <em>N</em> interacting particles driven by additive fractional Brownian motion of Hurst index <em>H</em> ≥ 1/2. Considering continuous observation of the interacting particles over a fixed interval [0, <em>T</em>], we examine the asymptotic regime as <em>N</em> → ∞. Our main tool is a random variable reminiscent of the least squares estimator but unobservable due to its reliance on the Skorohod integral. We demonstrate that this object is consistent and asymptotically normal by establishing a quantitative propagation of chaos for Malliavin derivatives, which holds for any <em>H</em> ∈ (0, 1). Leveraging a connection between the divergence integral and the Young integral, we construct computable estimators of the drift parameter. These estimators are shown to be consistent and asymptotically Gaussian. Finally, a numerical study highlights the strong performance of the proposed estimators.</div></div>","PeriodicalId":51160,"journal":{"name":"Stochastic Processes and their Applications","volume":"195 ","pages":"Article 104857"},"PeriodicalIF":1.2,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145886101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-05-01Epub Date: 2026-01-29DOI: 10.1016/j.spa.2026.104890
Valentin Tissot-Daguette
A stochastic process X becomes occupied when it is enlarged with its occupation flow that tracks the time spent by the path at each level. When X is Markov, the occupied process enjoys a Markov structure as well. We develop an Itô calculus for occupied processes that lies midway between Dupire’s functional Itô calculus and the classical version. We derive Itô formulae and, through Feynman-Kac, unveil a broad class of path-dependent PDEs where plays the role of time. The space variable, given by the current value of X, remains finite-dimensional, thereby paving the way for standard elliptic PDE techniques and numerical methods.
The framework’s benefits are illustrated via an optimal stopping problem involving local times, followed by financial applications. For the latter, we show how occupation flows provide unified Markovian lifts for exotic options and variance instruments, allowing financial institutions to price derivatives books with a single numerical solver. We finally explore an extension of forward variance models so as to leverage the entire forward occupation surface.
{"title":"Occupied processes: Going with the flow","authors":"Valentin Tissot-Daguette","doi":"10.1016/j.spa.2026.104890","DOIUrl":"10.1016/j.spa.2026.104890","url":null,"abstract":"<div><div>A stochastic process <em>X</em> becomes <em>occupied</em> when it is enlarged with its occupation flow <span><math><mi>O</mi></math></span> that tracks the time spent by the path at each level. When <em>X</em> is Markov, the occupied process <span><math><mrow><mo>(</mo><mi>O</mi><mo>,</mo><mi>X</mi><mo>)</mo></mrow></math></span> enjoys a Markov structure as well. We develop an Itô calculus for occupied processes that lies midway between Dupire’s functional Itô calculus and the classical version. We derive Itô formulae and, through Feynman-Kac, unveil a broad class of path-dependent PDEs where <span><math><mi>O</mi></math></span> plays the role of time. The space variable, given by the current value of <em>X</em>, remains finite-dimensional, thereby paving the way for standard elliptic PDE techniques and numerical methods.</div><div>The framework’s benefits are illustrated via an optimal stopping problem involving local times, followed by financial applications. For the latter, we show how occupation flows provide unified Markovian lifts for exotic options and variance instruments, allowing financial institutions to price derivatives books with a single numerical solver. We finally explore an extension of forward variance models so as to leverage the entire forward occupation surface.</div></div>","PeriodicalId":51160,"journal":{"name":"Stochastic Processes and their Applications","volume":"195 ","pages":"Article 104890"},"PeriodicalIF":1.2,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146173742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}