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Evolutionary programming as a solution technique for the Bellman equation [PDF]
Evolutionary programming is a stochastic optimization procedure that has proved useful in optimizing difficult functions. This paper shows that evolutionary programming can be used to solve the Bellman equation problem with a high degree of accuracy and ...
Paul Gomme
core
The Uncertainty Bellman Equation and Exploration [PDF]
, 2017 Brendan O’Donoghue +3 more
openalex +1 more source
From gateway to value ladder—The curious case of online mutual aid in China
Journal of Risk and Insurance, EarlyView.Abstract This study examines how InsurTech‐enabled information provision, specifically the disclosure of claimant information previously unavailable in conventional insurance, influences individuals' insurance uptake. We leverage Mutual Aid (MA) platforms as a natural context to examine how socially framed loss information, peer influence, and salience
Ze Chen +3 more
wiley +1 more source
Utility indifference pricing of ESO with reload terms
上海师范大学学报. 自然科学版, 2018 “Nontradable” is one of the important characters of the Executive Stock Option(ESO).Therefore,the ESO cannot be priced by hedging the corresponding underlying asset.In this paper,we study ESO with reload terms by utility indifference method,based on ...
Fu Yi, Zhang Jizhou, Ji Sulei
doaj +1 more source
Weak Solution for a Class of Fully Nonlinear Stochastic Hamilton-Jacobi-Bellman Equations [PDF]
, 2015 This paper is concerned with the stochastic Hamilton-Jacobi-Bellman equation with controlled leading coefficients, which is a type of fully nonlinear backward stochastic partial differential equation (BSPDE for short).
Qiu, Jinniao
core
Tackling nonlinear price impact with linear strategies
Mathematical Finance, Volume 35, Issue 2, Page 422-440, April 2025.Abstract Empirical studies in various contexts find that the price impact of large trades approximately follows a power law with exponent between 0.4 and 0.7. Yet, tractable formulas for the portfolios that trade off predictive trading signals, risk, and trading costs in an optimal manner are only available for quadratic costs corresponding to linear ...
Xavier Brokmann +3 more
wiley +1 more source
Reinforcement Learning for Jump‐Diffusions, With Financial Applications
Mathematical Finance, EarlyView.ABSTRACT We study continuous‐time reinforcement learning (RL) for stochastic control in which system dynamics are governed by jump‐diffusion processes. We formulate an entropy‐regularized exploratory control problem with stochastic policies to capture the exploration–exploitation balance essential for RL.
Xuefeng Gao, Lingfei Li, Xun Yu Zhou
wiley +1 more source
Quantitative Effects of Employment Protection in OECD Labor Markets
The Manchester School, EarlyView.ABSTRACT This paper explores the quantitative role played by Employment Protection Legislation over employment and on‐the‐job training in the presence of dual labor markets across OECD economies. We extend the search and matching model by introducing formal education and investment decisions in training by firms, and a gap in firing costs between fixed‐
Joaquín Naval, José I. Silva
wiley +1 more source
MathematicsThis paper is devoted to the study of stochastic optimal control of averaged stochastic differential delay equations (SDDEs) with semi-Markov switchings and their applications in economics.
Mariya Svishchuk, Anatoliy V. Swishchuk
doaj +1 more source
Journal of Applied Mathematics, 2013 This paper studies a continuous-time dynamic mean-variance portfolio selection problem with the constraint of a higher borrowing rate, in which stock price is governed by a constant elasticity of variance (CEV) process. Firstly, we apply Lagrange duality
Hao Chang, Xi-min Rong
doaj +1 more source