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In this paper, we study the portfolio optimization problem with general utility functions and when the return and volatility of underlying asset are slowly varying. An asymptotic optimal strategy is provided within a specific class of…

Mathematical Finance · Quantitative Finance 2016-11-08 Jean-Pierre Fouque , Ruimeng Hu

We propose a general approximation method for determining optimal trading strategies in markets with proportional transaction costs, with a polynomial approximation of the residual value function. The method is exemplified by several…

Portfolio Management · Quantitative Finance 2024-07-11 Eberhard Mayerhofer

We study the minimization of the expected costs under stochastic constraint at the terminal time. The first and the main result says that for a power type of costs, the value function is the minimal positive solution of a second order…

Probability · Mathematics 2020-01-28 Yan Dolinsky , Benjamin Gottesman , Ori Gurel-Gurevich

We consider an agent who invests in a stock and a money market account with the goal of maximizing the utility of his investment at the final time T in the presence of a proportional transaction cost. The utility function considered is…

Portfolio Management · Quantitative Finance 2011-12-14 Maxim Bichuch

We consider the problem of computing the value and an optimal strategy for minimizing the expected termination time in one-counter Markov decision processes. Since the value may be irrational and an optimal strategy may be rather…

Formal Languages and Automata Theory · Computer Science 2012-05-08 Tomáš Brázdil , Antonín Kučera , Petr Novotný , Dominik Wojtczak

We investigate the problem of jointly testing multiple hypotheses and estimating a random parameter of the underlying distribution in a sequential setup. The aim is to jointly infer the true hypothesis and the true parameter while using on…

Signal Processing · Electrical Eng. & Systems 2024-02-02 Dominik Reinhard , Michael Fauß , Abdelhak M. Zoubir

Time Optimal Path Parametrization is the problem of minimizing the time interval during which an actuation constrained agent can traverse a given path. Recently, an efficient linear-time algorithm for solving this problem was proposed.…

Robotics · Computer Science 2019-06-24 Igor Spasojevic , Varun Murali , Sertac Karaman

Considering the problem of risk-sensitive parameter estimation, we propose a fairly wide family of lower bounds on the exponential moments of the quadratic error, both in the Bayesian and the non--Bayesian regime. This family of bounds,…

Information Theory · Computer Science 2017-03-02 Neri Merhav

This paper investigates the optimal investment problem in a market with two types of illiquidity: transaction costs and search frictions. Extending the framework established by arXiv:2101.09936, we analyze a power-utility maximization…

Mathematical Finance · Quantitative Finance 2025-07-22 Tae Ung Gang , Jin Hyuk Choi

The problem of estimating a linear functional based on observational data is canonical in both the causal inference and bandit literatures. We analyze a broad class of two-stage procedures that first estimate the treatment effect function,…

Statistics Theory · Mathematics 2022-09-28 Wenlong Mou , Martin J. Wainwright , Peter L. Bartlett

In this paper, we consider asymptotics of the optimal value and the optimal solutions of parametric minimax estimation problems. Specifically, we consider estimators of the optimal value and the optimal solutions in a sample minimax problem…

Statistics Theory · Mathematics 2025-04-16 Mika Meitz , Alexander Shapiro

In this paper we investigate a new class of growth rate maximization problems based on impulse control strategies such that the average number of trades per time unit does not exceed a fixed level. Moreover, we include proportional…

Portfolio Management · Quantitative Finance 2013-06-10 Sören Christensen , Marc Wittlinger

Asymptotic statistical theory for estimating functions is reviewed in a generality suitable for stochastic processes. Conditions concerning existence of a consistent estimator, uniqueness, rate of convergence, and the asymptotic…

Statistics Theory · Mathematics 2018-09-06 Jean Jacod , Michael Sørensen

We derive asymptotically optimal statistical decision rules for discrete choice problems when payoffs depend on a partially-identified parameter $\theta$ and the decision maker can use a point-identified parameter $\mu$ to deduce…

Econometrics · Economics 2025-12-19 Timothy Christensen , Hyungsik Roger Moon , Frank Schorfheide

Consider a decision maker who is responsible to dynamically collect observations so as to enhance his information about an underlying phenomena of interest in a speedy manner while accounting for the penalty of wrong declaration. Due to the…

Information Theory · Computer Science 2013-12-19 Mohammad Naghshvar , Tara Javidi

In a classical optimal stopping problem the aim is to maximize the expected value of a functional of a diffusion evaluated at a stopping time. This note considers optimal stopping problems beyond this paradigm. We study problems in which…

Probability · Mathematics 2017-08-04 Vicky Henderson , David Hobson , Matthew Zeng

This paper studies the portfolio optimization problem when the investor's utility is general and the return and volatility of the risky asset are fast mean-reverting, which are important to capture the fast-time scale in the modeling of…

Mathematical Finance · Quantitative Finance 2019-01-31 Ruimeng Hu

We present stability conditions for deterministic time-varying nonlinear discrete-time systems whose inputs aim to minimize an infinite-horizon time-dependent cost. Global asymptotic and exponential stability properties for general…

Systems and Control · Electrical Eng. & Systems 2023-08-28 Sifeddine Benahmed , Romain Postoyan , Mathieu Granzotto , Lucian Buşoniu , Jamal Daafouz , Dragan Nešić

This paper investigates asymptotic behaviors of gradient descent algorithms (particularly accelerated gradient descent and stochastic gradient descent) in the context of stochastic optimization arising in statistics and machine learning…

Machine Learning · Statistics 2019-11-13 Yazhen Wang

We present a technique to study normalizing strategies when termination is asymptotic, that is, it appears as a limit, as opposite to reaching a normal form in a finite number of steps. Asymptotic termination occurs in several settings,…

Logic in Computer Science · Computer Science 2022-05-24 Claudia Faggian , Giulio Guerrieri
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