Pub Date : 2023-07-03DOI: 10.1080/15326349.2022.2138440
Xiufang Li, Dongxu Zhao, Xiaowei Chen
Abstract This paper considers a state-dependent optimal asset-liability management problem in continuous-time settings. The investor maximizes the expected state-dependent utility of the terminal asset-liability ratio in a regime-switching market to better describe insurance companies’ needs for asset-liability matching and regulation with background risk. We apply the stochastic dynamic programming method to get closed-form results. We find that the optimal strategy in the state-dependent utility case is the same, and the optimal value function differs from the state-independent utility case. Finally, we study how the parameters impact the optimal investment strategy and corresponding value functions through numerical examples.
{"title":"Asset-liability management with state-dependent utility in the regime-switching market","authors":"Xiufang Li, Dongxu Zhao, Xiaowei Chen","doi":"10.1080/15326349.2022.2138440","DOIUrl":"https://doi.org/10.1080/15326349.2022.2138440","url":null,"abstract":"Abstract This paper considers a state-dependent optimal asset-liability management problem in continuous-time settings. The investor maximizes the expected state-dependent utility of the terminal asset-liability ratio in a regime-switching market to better describe insurance companies’ needs for asset-liability matching and regulation with background risk. We apply the stochastic dynamic programming method to get closed-form results. We find that the optimal strategy in the state-dependent utility case is the same, and the optimal value function differs from the state-independent utility case. Finally, we study how the parameters impact the optimal investment strategy and corresponding value functions through numerical examples.","PeriodicalId":21970,"journal":{"name":"Stochastic Models","volume":"39 1","pages":"566 - 591"},"PeriodicalIF":0.7,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46191560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-10DOI: 10.1080/15326349.2023.2210206
S. Zheng, Fei Zhang, Chunhua Wang, Xuejun Wang
{"title":"A general result on complete f-moment convergence with its application to nonparametric regression models","authors":"S. Zheng, Fei Zhang, Chunhua Wang, Xuejun Wang","doi":"10.1080/15326349.2023.2210206","DOIUrl":"https://doi.org/10.1080/15326349.2023.2210206","url":null,"abstract":"","PeriodicalId":21970,"journal":{"name":"Stochastic Models","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42507010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-19DOI: 10.1080/15326349.2023.2212763
Mohamed El Omari
{"title":"On the Gaussian Volterra processes with power-type kernels","authors":"Mohamed El Omari","doi":"10.1080/15326349.2023.2212763","DOIUrl":"https://doi.org/10.1080/15326349.2023.2212763","url":null,"abstract":"","PeriodicalId":21970,"journal":{"name":"Stochastic Models","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46083317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-12DOI: 10.1080/15326349.2023.2201329
Jhonatan Tavori, H. Levy
{"title":"Stochastic epidemic spreading: not all super-spreading processes are born equal, neither all lockdown strategies","authors":"Jhonatan Tavori, H. Levy","doi":"10.1080/15326349.2023.2201329","DOIUrl":"https://doi.org/10.1080/15326349.2023.2201329","url":null,"abstract":"","PeriodicalId":21970,"journal":{"name":"Stochastic Models","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48737328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-09DOI: 10.1080/15326349.2023.2209146
Xijun Liu, Qingwu Gao, Zimai Dong
{"title":"Asymptotics for a diffusion-perturbed risk model with dependence structures, constant interest force, and a random number of delayed claims","authors":"Xijun Liu, Qingwu Gao, Zimai Dong","doi":"10.1080/15326349.2023.2209146","DOIUrl":"https://doi.org/10.1080/15326349.2023.2209146","url":null,"abstract":"","PeriodicalId":21970,"journal":{"name":"Stochastic Models","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43633798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-06DOI: 10.1080/15326349.2023.2184832
C. Hirsch, B. Jahnel, E. Cali
Abstract We consider a hybrid spatial communication system in which mobile nodes can connect to static sinks in a bounded number of intermediate relaying hops. We describe the distribution of the connection intervals of a typical mobile node, i.e., the intervals of uninterrupted connection to the family of sinks. This is achieved in the limit of many hops, sparse sinks and growing time horizons. We identify three regimes reflecting various degrees of sink densities. Namely, (1) a regime of dense sinks, in which the limit is deterministic and given as an expectation with respect to percolation clusters, (2) a regime of sparse sinks, in which the limit depends on a random number of reachable sinks, and (3) an intermediate critical regime.
{"title":"Connection intervals in multi-scale infrastructure-augmented dynamic networks","authors":"C. Hirsch, B. Jahnel, E. Cali","doi":"10.1080/15326349.2023.2184832","DOIUrl":"https://doi.org/10.1080/15326349.2023.2184832","url":null,"abstract":"Abstract We consider a hybrid spatial communication system in which mobile nodes can connect to static sinks in a bounded number of intermediate relaying hops. We describe the distribution of the connection intervals of a typical mobile node, i.e., the intervals of uninterrupted connection to the family of sinks. This is achieved in the limit of many hops, sparse sinks and growing time horizons. We identify three regimes reflecting various degrees of sink densities. Namely, (1) a regime of dense sinks, in which the limit is deterministic and given as an expectation with respect to percolation clusters, (2) a regime of sparse sinks, in which the limit depends on a random number of reachable sinks, and (3) an intermediate critical regime.","PeriodicalId":21970,"journal":{"name":"Stochastic Models","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48851821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-28DOI: 10.1080/15326349.2023.2173233
Markus Hess
In this paper, we derive stochastic Leibniz formulas for Volterra integrals under enlarged filtrations. We investigate both pure-jump and Brownian Volterra processes under diverse initially enlarged filtration approaches. In these setups, we compare the ordinary with the stochastic (Doléans-Dade) exponential of a Volterra process and provide the corresponding martingale conditions. We also consider backward stochastic Volterra integral equations (BSVIEs) under enlarged filtrations and obtain the related solution formulas. We finally propose an anticipative Heath Jarrow Morton (HJM) forward rate model of Volterra-type and infer the associated bond price representation. In an introductory section, we compile various facts on deterministic and stochastic Leibniz formulas for parameter integrals.
{"title":"The stochastic Leibniz formula for Volterra integrals under enlarged filtrations","authors":"Markus Hess","doi":"10.1080/15326349.2023.2173233","DOIUrl":"https://doi.org/10.1080/15326349.2023.2173233","url":null,"abstract":"In this paper, we derive stochastic Leibniz formulas for Volterra integrals under enlarged filtrations. We investigate both pure-jump and Brownian Volterra processes under diverse initially enlarged filtration approaches. In these setups, we compare the ordinary with the stochastic (Doléans-Dade) exponential of a Volterra process and provide the corresponding martingale conditions. We also consider backward stochastic Volterra integral equations (BSVIEs) under enlarged filtrations and obtain the related solution formulas. We finally propose an anticipative Heath Jarrow Morton (HJM) forward rate model of Volterra-type and infer the associated bond price representation. In an introductory section, we compile various facts on deterministic and stochastic Leibniz formulas for parameter integrals.","PeriodicalId":21970,"journal":{"name":"Stochastic Models","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135678117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-15DOI: 10.1080/15326349.2023.2175869
G. Yin, Huy Nguyen
Abstract In this work, we consider a number of matrix-valued random sequences that are modulated by a discrete-time Markov chain having a finite space. Assuming that the state space of the Markov chain is large, our main effort in this paper is devoted to reducing the computation complexity. To achieve this goal, our formulation uses time-scale separation of the Markov chain. The state-space of the Markov chain is split into subspaces. Next, the states of the Markov chain in each subspace are aggregated into a “super” state. Then we normalize the matrix-valued sequences that are modulated by the two-time-scale Markov chain. Under simple conditions, we derive a scaling limit of the centered and scaled sequence by using a martingale averaging approach. The study is carried out through a functional. It is shown that the scaled and interpolated sequence converges weakly to a switching diffusion.
{"title":"Sequences of random matrices modulated by a discrete-time Markov chain*","authors":"G. Yin, Huy Nguyen","doi":"10.1080/15326349.2023.2175869","DOIUrl":"https://doi.org/10.1080/15326349.2023.2175869","url":null,"abstract":"Abstract In this work, we consider a number of matrix-valued random sequences that are modulated by a discrete-time Markov chain having a finite space. Assuming that the state space of the Markov chain is large, our main effort in this paper is devoted to reducing the computation complexity. To achieve this goal, our formulation uses time-scale separation of the Markov chain. The state-space of the Markov chain is split into subspaces. Next, the states of the Markov chain in each subspace are aggregated into a “super” state. Then we normalize the matrix-valued sequences that are modulated by the two-time-scale Markov chain. Under simple conditions, we derive a scaling limit of the centered and scaled sequence by using a martingale averaging approach. The study is carried out through a functional. It is shown that the scaled and interpolated sequence converges weakly to a switching diffusion.","PeriodicalId":21970,"journal":{"name":"Stochastic Models","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49160200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-23DOI: 10.1080/15326349.2023.2166534
Caibin Zhang, Zhibin Liang
Abstract This article studies a mean-variance portfolio selection problem for a jump-diffusion model, where the drift process is modulated by a continuous unobservable Markov chain. Since there is a constraint on wealth, we tackle this problem via the technique of martingale. We first investigate the full information case that the Markov chain can be observable, closed-form expressions not only for the optimal wealth process and optimal portfolio strategy but for the efficient frontier are derived. Then, by the filtering theory, we reduce the original partial information problem to a full information one, and the corresponding optimal results are obtained as well. Furthermore, if short selling is not allowed, we find that the solution in the full information case can be derived by transforming the problem into an equivalent one with constraint only on wealth, but this technique is not applicable anymore for the partial information case.
{"title":"Constrained mean-variance portfolio optimization for jump-diffusion process under partial information","authors":"Caibin Zhang, Zhibin Liang","doi":"10.1080/15326349.2023.2166534","DOIUrl":"https://doi.org/10.1080/15326349.2023.2166534","url":null,"abstract":"Abstract This article studies a mean-variance portfolio selection problem for a jump-diffusion model, where the drift process is modulated by a continuous unobservable Markov chain. Since there is a constraint on wealth, we tackle this problem via the technique of martingale. We first investigate the full information case that the Markov chain can be observable, closed-form expressions not only for the optimal wealth process and optimal portfolio strategy but for the efficient frontier are derived. Then, by the filtering theory, we reduce the original partial information problem to a full information one, and the corresponding optimal results are obtained as well. Furthermore, if short selling is not allowed, we find that the solution in the full information case can be derived by transforming the problem into an equivalent one with constraint only on wealth, but this technique is not applicable anymore for the partial information case.","PeriodicalId":21970,"journal":{"name":"Stochastic Models","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42145285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：