Pub Date : 2026-01-14DOI: 10.1016/j.spa.2026.104887
A. Pedicone, E. Orsingher
In this paper we study the telegraph meander, a random function obtained by conditioning the telegraph process to stay above the zero level. The finite dimensional distribution of the telegraph meander is derived by applying the reflection principle for the telegraph process and the Markovianity of the telegraph process with the velocity process. We show that the law of the telegraph meander at the end time is a solution to a hyperbolic equation, and we find the characteristic function and moments of any order. Finally, we prove that Brownian meander is the weak limit of the telegraph meander.
{"title":"On the distribution of the telegraph meander and its properties","authors":"A. Pedicone, E. Orsingher","doi":"10.1016/j.spa.2026.104887","DOIUrl":"10.1016/j.spa.2026.104887","url":null,"abstract":"<div><div>In this paper we study the telegraph meander, a random function obtained by conditioning the telegraph process to stay above the zero level. The finite dimensional distribution of the telegraph meander is derived by applying the reflection principle for the telegraph process and the Markovianity of the telegraph process with the velocity process. We show that the law of the telegraph meander at the end time is a solution to a hyperbolic equation, and we find the characteristic function and moments of any order. Finally, we prove that Brownian meander is the weak limit of the telegraph meander.</div></div>","PeriodicalId":51160,"journal":{"name":"Stochastic Processes and their Applications","volume":"195 ","pages":"Article 104887"},"PeriodicalIF":1.2,"publicationDate":"2026-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145978768","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 : 2026-01-12DOI: 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":"2026-01-12","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 : 2026-01-09DOI: 10.1016/j.spa.2026.104873
Rajat Subhra Hazra, Frank den Hollander, Azadeh Parvaneh
In [1] we analysed the friendship paradox for sparse random graphs. For four classes of random graphs we characterised the empirical distribution of the friendship biases between vertices and their neighbours at distance 1, proving convergence as n → ∞ to a limiting distribution, with n the number of vertices, and identifying moments and tail exponents of the limiting distribution. In the present paper we look at the multi-level friendship bias between vertices and their neighbours at distance obtained via a k-step exploration according to a backtracking or a non-backtracking random walk. We identify the limit of the empirical distribution of the multi-level friendship biases as n → ∞ and/or k → ∞. We show that for non-backtracking exploration the two limits commute for a large class of sparse random graphs, including those that locally converge to a rooted Galton-Watson tree. In particular, we show that the same limit arises when k depends on n, i.e., , provided under some mild conditions. We exhibit cases where the two limits do not commute and show the relevance of the mixing time of the exploration.
{"title":"The multi-level friendship paradox for sparse random graphs","authors":"Rajat Subhra Hazra, Frank den Hollander, Azadeh Parvaneh","doi":"10.1016/j.spa.2026.104873","DOIUrl":"10.1016/j.spa.2026.104873","url":null,"abstract":"<div><div>In [1] we analysed the friendship paradox for sparse random graphs. For four classes of random graphs we characterised the empirical distribution of the friendship biases between vertices and their neighbours at distance 1, proving convergence as <em>n</em> → ∞ to a limiting distribution, with <em>n</em> the number of vertices, and identifying moments and tail exponents of the limiting distribution. In the present paper we look at the multi-level friendship bias between vertices and their neighbours at distance <span><math><mrow><mi>k</mi><mo>∈</mo><mi>N</mi></mrow></math></span> obtained via a <em>k</em>-step exploration according to a backtracking or a non-backtracking random walk. We identify the limit of the empirical distribution of the multi-level friendship biases as <em>n</em> → ∞ and/or <em>k</em> → ∞. We show that for non-backtracking exploration the two limits commute for a large class of sparse random graphs, including those that locally converge to a rooted Galton-Watson tree. In particular, we show that the same limit arises when <em>k</em> depends on <em>n</em>, i.e., <span><math><mrow><mi>k</mi><mo>=</mo><msub><mi>k</mi><mi>n</mi></msub></mrow></math></span>, provided <span><math><mrow><msub><mi>lim</mi><mrow><mi>n</mi><mo>→</mo><mi>∞</mi></mrow></msub><msub><mi>k</mi><mi>n</mi></msub><mo>=</mo><mi>∞</mi></mrow></math></span> under some mild conditions. We exhibit cases where the two limits do not commute and show the relevance of the mixing time of the exploration.</div></div>","PeriodicalId":51160,"journal":{"name":"Stochastic Processes and their Applications","volume":"195 ","pages":"Article 104873"},"PeriodicalIF":1.2,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145978769","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 : 2026-01-07DOI: 10.1016/j.spa.2026.104871
Emmanuel Gobet , Adrien Richou , Lukasz Szpruch
In this work we study the numerical approximation of a class of ergodic Backward Stochastic Differential Equations. These equations are formulated in an infinite horizon framework and provide a probabilistic representation for elliptic Partial Differential Equations of ergodic type. In order to build our numerical scheme, we put forward a new representation of the PDE solution by using a classical probabilistic representation of the gradient. Then, based on this representation, we propose a fully implementable numerical scheme using a Picard iteration procedure, a grid space discretization and a Monte-Carlo approximation. Up to a limiting technical condition that guarantees the contraction of the Picard procedure, we obtain an upper bound for the numerical error. We also provide some numerical experiments that show the efficiency of this approach for small dimensions.
{"title":"Numerical approximation of ergodic BSDEs using non linear Feynman-Kac formulas","authors":"Emmanuel Gobet , Adrien Richou , Lukasz Szpruch","doi":"10.1016/j.spa.2026.104871","DOIUrl":"10.1016/j.spa.2026.104871","url":null,"abstract":"<div><div>In this work we study the numerical approximation of a class of ergodic Backward Stochastic Differential Equations. These equations are formulated in an infinite horizon framework and provide a probabilistic representation for elliptic Partial Differential Equations of ergodic type. In order to build our numerical scheme, we put forward a new representation of the PDE solution by using a classical probabilistic representation of the gradient. Then, based on this representation, we propose a fully implementable numerical scheme using a Picard iteration procedure, a grid space discretization and a Monte-Carlo approximation. Up to a limiting technical condition that guarantees the contraction of the Picard procedure, we obtain an upper bound for the numerical error. We also provide some numerical experiments that show the efficiency of this approach for small dimensions.</div></div>","PeriodicalId":51160,"journal":{"name":"Stochastic Processes and their Applications","volume":"195 ","pages":"Article 104871"},"PeriodicalIF":1.2,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145978772","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 : 2026-01-07DOI: 10.1016/j.spa.2026.104870
Jingtao Lin, Jingtao Shi
This paper is concerned with one kind of partially observed progressive optimal control problems of coupled forward-backward stochastic systems driven by both Brownian motion and Poisson random measure with risk-sensitive criteria. The control domain is not necessarily convex, and the control variable can enters into all the coefficients. The observation equation also has correlated noises with the state equation. Under the Poisson jump setting, the original problem is equivalent to a stochastic recursive optimal control problem of a forward-backward system with quadratic-exponential generator. In order to establish the first- and second-order variations, some new techniques are introduced to overcome difficulties caused by the quadratic-exponential feature. A new global stochastic maximum principle is deduced. As an application, a risk-sensitive optimal investment problem with factor model is studied. Moreover, the risk-sensitive stochastic filtering problem is studied, which involves both Brownian and Poissonian correlated noises. A modified Zakai equation is obtained.
{"title":"Global maximum principle for partially observed risk-sensitive progressive optimal control of FBSDE with Poisson jumps","authors":"Jingtao Lin, Jingtao Shi","doi":"10.1016/j.spa.2026.104870","DOIUrl":"10.1016/j.spa.2026.104870","url":null,"abstract":"<div><div>This paper is concerned with one kind of partially observed progressive optimal control problems of coupled forward-backward stochastic systems driven by both Brownian motion and Poisson random measure with risk-sensitive criteria. The control domain is not necessarily convex, and the control variable can enters into all the coefficients. The observation equation also has correlated noises with the state equation. Under the Poisson jump setting, the original problem is equivalent to a stochastic recursive optimal control problem of a forward-backward system with quadratic-exponential generator. In order to establish the first- and second-order variations, some new techniques are introduced to overcome difficulties caused by the quadratic-exponential feature. A new global stochastic maximum principle is deduced. As an application, a risk-sensitive optimal investment problem with factor model is studied. Moreover, the risk-sensitive stochastic filtering problem is studied, which involves both Brownian and Poissonian correlated noises. A modified Zakai equation is obtained.</div></div>","PeriodicalId":51160,"journal":{"name":"Stochastic Processes and their Applications","volume":"195 ","pages":"Article 104870"},"PeriodicalIF":1.2,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145978771","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 : 2026-01-06DOI: 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":"2026-01-06","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 : 2026-01-05DOI: 10.1016/j.spa.2026.104869
Feng-Yu Wang , Bingyao Wu , Jie-Xiang Zhu
In this paper we study the long time behavior in Wasserstein distance for empirical measures of (non-symmetric) diffusion processes on a length space satisfying the Nash inequality, which in particular include the (reflecting) diffusion processes on a connected compact Riemannian manifold. As a general result, the sharp convergence rate in for the p-Wasserstein distance is derived uniformly in p ∈ [1, ∞) and q ∈ (0, ∞). A key novelty of our approach, compared to existing works, is the use of a Bernstein-type inequality for diffusion processes.
{"title":"Sharp Lq-convergence rate in p-Wasserstein distance for empirical measures of diffusion processes","authors":"Feng-Yu Wang , Bingyao Wu , Jie-Xiang Zhu","doi":"10.1016/j.spa.2026.104869","DOIUrl":"10.1016/j.spa.2026.104869","url":null,"abstract":"<div><div>In this paper we study the long time behavior in Wasserstein distance for empirical measures of (non-symmetric) diffusion processes on a length space satisfying the Nash inequality, which in particular include the (reflecting) diffusion processes on a connected compact Riemannian manifold. As a general result, the sharp convergence rate in <span><math><mrow><msup><mi>L</mi><mi>q</mi></msup><mrow><mo>(</mo><mi>P</mi><mo>)</mo></mrow></mrow></math></span> for the <em>p</em>-Wasserstein distance is derived uniformly in <em>p</em> ∈ [1, ∞) and <em>q</em> ∈ (0, ∞). A key novelty of our approach, compared to existing works, is the use of a Bernstein-type inequality for diffusion processes.</div></div>","PeriodicalId":51160,"journal":{"name":"Stochastic Processes and their Applications","volume":"195 ","pages":"Article 104869"},"PeriodicalIF":1.2,"publicationDate":"2026-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145927997","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 : 2026-01-04DOI: 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":"2026-01-04","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}
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":"2026-01-03","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 : 2025-12-27DOI: 10.1016/j.spa.2025.104855
Lucie Laurence , Philippe Robert
The asymptotic properties of some Markov processes associated to stochastic chemical reaction networks (CRNs) driven by the kinetics of the law of mass action are analyzed. The scaling regime introduced in the paper assumes that the norm of the initial state is converging to infinity. The reaction rate constants are kept fixed. The purpose of the paper is of showing, with simple examples, a scaling analysis in this context. The main difference with the scalings of the literature is that it does not change the graph structure of the CRN or its reaction rates. Several CRNs are investigated to illustrate the insight that can be gained on the qualitative properties of these networks. A detailed scaling analysis of a CRN with several interesting asymptotic properties, with a bi-modal behavior in particular, is worked out in the last section. Additionally, with several examples, we also show that a stability criterion due to Filonov for positive recurrence of Markov processes may simplify significantly the stability analysis of these networks.
{"title":"Scaling methods for stochastic chemical reaction networks","authors":"Lucie Laurence , Philippe Robert","doi":"10.1016/j.spa.2025.104855","DOIUrl":"10.1016/j.spa.2025.104855","url":null,"abstract":"<div><div>The asymptotic properties of some Markov processes associated to stochastic chemical reaction networks (CRNs) driven by the kinetics of the law of mass action are analyzed. The scaling regime introduced in the paper assumes that the norm of the initial state is converging to infinity. The reaction rate constants are kept fixed. The purpose of the paper is of showing, with simple examples, a scaling analysis in this context. The main difference with the scalings of the literature is that it does not change the graph structure of the CRN or its reaction rates. Several CRNs are investigated to illustrate the insight that can be gained on the qualitative properties of these networks. A detailed scaling analysis of a CRN with several interesting asymptotic properties, with a bi-modal behavior in particular, is worked out in the last section. Additionally, with several examples, we also show that a stability criterion due to Filonov for positive recurrence of Markov processes may simplify significantly the stability analysis of these networks.</div></div>","PeriodicalId":51160,"journal":{"name":"Stochastic Processes and their Applications","volume":"194 ","pages":"Article 104855"},"PeriodicalIF":1.2,"publicationDate":"2025-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145842463","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}