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This paper presents an axiomatic scheme for interest rate models in discrete time. We take a pricing kernel approach, which builds in the arbitrage-free property and provides a link to equilibrium economics. We require that the pricing…

Pricing of Securities · Quantitative Finance 2009-11-05 Lane P. Hughston , Andrea Macrina

Restricting the variance of a policy's return is a popular choice in risk-averse Reinforcement Learning (RL) due to its clear mathematical definition and easy interpretability. Traditional methods directly restrict the total return…

Machine Learning · Computer Science 2023-11-06 Yudong Luo , Guiliang Liu , Pascal Poupart , Yangchen Pan

The classic integrated conditional moment test is a promising method for testing regression model misspecification. However, it severely suffers from the curse of dimensionality. To extend it to handle the testing problem for parametric…

Statistics Theory · Mathematics 2020-05-26 Falong Tan , Lixing Zhu

This paper studies continuous-time Markov decision processes under the risk-sensitive average cost criterion. The state space is a finite set, the action space is a Borel space, the cost and transition rates are bounded, and the…

Optimization and Control · Mathematics 2015-12-22 Qingda Wei , Xian Chen

This paper investigates a novel behavioral feature of recursive preferences: aversion to risks that persist over time, or simply \textit{correlation aversion}. Greater persistence provides information about future consumption but reduces…

Theoretical Economics · Economics 2026-03-24 Lorenzo Maria Stanca

Our paper contributes to the theory of conditional risk measures and conditional certainty equivalents. We adopt a random modular approach which proved to be effective in the study of modular convex analysis and conditional risk measures.…

Mathematical Finance · Quantitative Finance 2022-11-10 Giulio Principi , Fabio Maccheroni

The integration and innovation of finance and technology have gradually transformed the financial system into a complex one. Analyses of the causesd of abnormal fluctuations in the financial market to extract early warning indicators…

Risk Management · Quantitative Finance 2024-03-20 Shige Peng , Shuzhen Yang , Wenqing Zhang

Constructing confidence intervals that are simultaneously valid across a class of estimates is central to tasks such as multiple mean estimation, generalization guarantees, and adaptive experimental design. We frame this as an ``error…

Machine Learning · Computer Science 2026-02-05 Sanath Kumar Krishnamurthy , Anna Lyubarskaja , Emma Brunskill , Susan Athey

The relationship between set-valued risk measures for processes and vectors on the optional filtration is investigated. The equivalence of risk measures for processes and vectors and the equivalence of their penalty function formulations…

Risk Management · Quantitative Finance 2021-11-30 Yanhong Chen , Zachary Feinstein

We study the risk assessment of uncertain cash flows in terms of dynamic convex risk measures for processes as introduced in Cheridito, Delbaen, and Kupper (2006). These risk measures take into account not only the amounts but also the…

Risk Management · Quantitative Finance 2010-02-22 Beatrice Acciaio , Hans Foellmer , Irina Penner

We study a static portfolio optimization problem with two risk measures: a principle risk measure in the objective function and a secondary risk measure whose value is controlled in the constraints. This problem is of interest when it is…

Portfolio Management · Quantitative Finance 2020-12-14 Çağın Ararat

Descriptive statistics for parametric models are currently highly sensative to departures, gross errors, and/or random errors. Here, leveraging the structures of parametric distributions and their central moment kernel distributions, a…

Statistics Theory · Mathematics 2024-09-11 Li Tuobang

In certain applications involving the solution of a Bayesian inverse problem, it may not be possible or desirable to evaluate the full posterior, e.g. due to the high computational cost of doing so. This problem motivates the use of…

Statistics Theory · Mathematics 2024-02-27 Han Cheng Lie , T. J. Sullivan , Aretha Teckentrup

We consider a long-term optimal investment problem where an investor tries to minimize the probability of falling below a target growth rate. From a mathematical viewpoint, this is a large deviation control problem. This problem will be…

Probability · Mathematics 2010-01-14 Hiroaki Hata , Hideo Nagai , Shuenn-Jyi Sheu

In this paper,we consider a macro approximation of the flow of a risk reserve, The process is observed at discrete time points. Because we cannot directly observe each jump time and size then we will make use of a technique for identifying…

Statistics Theory · Mathematics 2016-06-22 Chunhao Cai , Junyi Guo , Honglong You

In this paper we consider the problem of detecting a change in the parameters of an autoregressive process, where the moments of the innovation process do not necessarily exist. An empirical likelihood ratio test for the existence of a…

Statistics Theory · Mathematics 2016-12-07 Fumiya Akashi , Holger Dette , Yan Liu

Mutual information is fundamentally important for measuring statistical dependence between variables and for quantifying information transfer by signaling and communication mechanisms. It can, however, be challenging to evaluate for…

Information Theory · Computer Science 2014-07-29 Clive G. Bowsher , Margaritis Voliotis

This article proposes a new index for quantifying the degree of dependence between random vectors. The index takes values in [0,1] and equals zero if and only if the random vectors are sub-independent. Unlike mere uncorrelatedness,…

Statistics Theory · Mathematics 2026-05-19 Chuancun yin

Portfolio diversification is a cornerstone of modern finance, while risk aversion is central to decision theory; both concepts are long-standing and foundational. We investigate their connections by studying how different forms of…

Theoretical Economics · Economics 2026-03-26 Xiangxin He , Fangda Liu , Ruodu Wang

In real-world decision-making problems, for instance in the fields of finance, robotics or autonomous driving, keeping uncertainty under control is as important as maximizing expected returns. Risk aversion has been addressed in the…

Machine Learning · Computer Science 2019-12-09 Lorenzo Bisi , Luca Sabbioni , Edoardo Vittori , Matteo Papini , Marcello Restelli
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