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Relevant bibliographies by topics / Girsanov controls

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Journal articles
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Academic literature on the topic 'Girsanov controls'

Author: Grafiati

Published: 6 September 2023

Last updated: 19 July 2025

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Journal articles on the topic "Girsanov controls"

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Kanjilal, Oindrila, and C. S. Manohar. "Estimation of time-variant system reliability of nonlinear randomly excited systems based on the Girsanov transformation with state-dependent controls." Nonlinear Dynamics 95, no. 2 (2018): 1693–711. http://dx.doi.org/10.1007/s11071-018-4655-6.

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Delavarkhalafi, Ali, Fatemion Aghda, and Mahdieh Tahmasebi. "Maximum principle for forward-backward partially observed optimal control of stochastic systems with delay." Filomat 37, no. 3 (2023): 809–32. http://dx.doi.org/10.2298/fil2303809d.

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In this paper, we consider partially observed optimal control for forward-backward stochastic delay differential equations (FBSDDEs) where the control domain is non-convex and the control variable is allowed to enter into both diffusion and observation terms. We obtain a general stochastic maximum principle of these optimal control problems by using Girsanov?s theorem, the spike variational method and the filtering technique. We also derive the adjoint equations to the problem. Finally, we apply our results to study a linear-quadratic (LQ) optimal control with delay.

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De Lara, M. Cohen, and J. Lévine. "Deterministic feedback linearization, Girsanov transformations and finite-dimensional filters." Systems & Control Letters 13, no. 1 (1989): 81–92. http://dx.doi.org/10.1016/0167-6911(89)90024-8.

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Knopov, Pavel, Tatyana Pepelyaeva, and Sergey Shpiga. "ON OPTIMAL CONTROL OF A STOCHASTIC EQUATION WITH A FRACTIONAL WIENER PROCESS." Journal of Automation and Information sciences 6 (November 1, 2021): 5–12. http://dx.doi.org/10.34229/1028-0979-2021-6-1.

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In recent years, a new direction of research has emerged in the theory of stochastic differential equations, namely, stochastic differential equations with a fractional Wiener process. This class of processes makes it possible to describe adequately many real phenomena of a stochastic nature in financial mathematics, hydrology, biology, and many other areas. These phenomena are not always described by stochastic systems satisfying the conditions of strong mixing, or weak dependence, but are described by systems with a strong dependence, and this strong dependence is regulated by the so-called

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Beliavsky, Grigory I., Natalia V. Danilova, and Gennady A. Ougolnitsky. "Approximation of supremum and infimum processes as a stochastic approach to the providing of homeostasis." Vestnik of Saint Petersburg University. Applied Mathematics. Computer Science. Control Processes 18, no. 1 (2022): 5–17. http://dx.doi.org/10.21638/11701/spbu10.2022.101.

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We consider the calculation of bounded functional of the trajectories of a stationary diffusion process. Since an analytical solution to this problem does not exist, it is necessary to use numerical methods. One possible direction for obtaining the numerical method is applying the Monte Carlo (MC) method. This involves reproducing the trajectory of a random process with subsequent averaging over the trajectories. To simplify the reproduction of the trajectory, the Girsanov transform is used in this paper. The main goal is to approximate the supremum and infimum processes, which allows us to mo

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Kanjilal, Oindrila, and C. S. Manohar. "State dependent Girsanov’s controls in time variant reliability estimation in randomly excited dynamical systems." Structural Safety 72 (May 2018): 30–40. http://dx.doi.org/10.1016/j.strusafe.2017.12.004.

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Li, Ruijing, Heping Ma, and Chaozhu Hu. "Maximum principle for partially observed leader–follower stochastic differential game." IET Control Theory & Applications, August 27, 2023. http://dx.doi.org/10.1049/cth2.12536.

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AbstractThis paper deals with the optimal control problem for partially observed leader–follower stochastic differential game. By virtue of the classical variational method and Girsanov's theorem, the stochastic maximum principles for the follower under one type of partially observed case and for the leader under the complete information structure are derived. As applications, two partially observed cases are considered for the linear–quadratic models. Then by the stochastic filtering technique, the optimal feedback controls for the follower and the leader are represented by the new stochastic

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Moagi, Gaoganwe S., and Obonye Doctor. "Optimal investment–consumption–insurance strategy with inflation risk and stochastic income in an Itô–Lévy setting." International Journal of Financial Engineering, January 3, 2024. http://dx.doi.org/10.1142/s2424786323500548.

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This paper’s focus is on finding the optimal strategies for a trader who invests in stock, a money market account and an inflation-linked index bond. The stock follows a jump diffusion process and the bond is linked to inflation making the two risky. The optimal strategies are determined on two generations of the life of an investor, that is before the investor dies and after the investor dies. We applied the concept of change of probability measures considering Girsanov’s and the Radon–Nikodym theorems. We found the generator of the Backward Stochastic differential equations defined and emplo

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Dissertations / Theses on the topic "Girsanov controls"

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Pagliarani, Stefano. "Portfolio optimization and option pricing under defaultable Lévy driven models." Doctoral thesis, Università degli studi di Padova, 2014. http://hdl.handle.net/11577/3423519.

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In this thesis we study some portfolio optimization and option pricing problems in market models where the dynamics of one or more risky assets are driven by Lévy processes, and it is divided in four independent parts. In the first part we study the portfolio optimization problem, for the logarithmic terminal utility and the logarithmic consumption utility, in a multi-defaultable Lévy driven model. In the second part we introduce a novel technique to price European defaultable claims when the pre-defaultable dynamics of the underlying asset follows an exponential Lévy process. In the third

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Kanjilal, Oindrila. "Structural Reliability Estimation Using Markov Chain Splitting and Girsanov’s Transformation Based Methods." Thesis, 2018. https://etd.iisc.ac.in/handle/2005/5405.

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The work reported in this thesis is in the area of Monte Carlo simulation based methods for structural reliability estimation with special focus on strategies to reduce sampling variance of the estimator for the probability of failure. The thesis aims to improve upon two existing methods of reliability assessment, namely, the Markov chain Monte Carlo based subset simulation, and the Girsanov transformation based importance sampling methods for dynamical systems. Specifically, three issues have been addressed in this thesis: (a) strategies to quantify and reduce sampling variance in the subset

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Book chapters on the topic "Girsanov controls"

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Björk, Tomas. "Good Deal Bounds." In Arbitrage Theory in Continuous Time. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198851615.003.0034.

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In this chapter we study an incomplete market, but we do not look for a unique martingale measure. Instead we try to find “reasonable” bounds on arbitrage free prices. The terms “reasonable” is formalized in terms of a price rule with bounded Sharpe ratio–so-called good deal bounds. We study a factor model and show that the good deal bounds can be obtained by solving a control problem where the likelihood process acts as a state variable, and the Girsanov kernel is the control variable. The theory is then applied to concrete examples.

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Björk, Tomas. "The Mathematics of the Martingale Approach." In Arbitrage Theory in Continuous Time. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198851615.003.0012.

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In this chapter we present the two main mathematical results which are needed for the application of the martingale approach to pricing and hedging. We first discuss and prove the martingale representation theorem which says that in a Wiener framework, every martingale can be represented as a stochastic integral. We then discuss and prove the Girsanov Theorem which gives us control over the class of absolutely continuous measure transformations. The abstract theory is then applied to stochastic differential equations, and to maximum likelihood estimation.

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Conference papers on the topic "Girsanov controls"

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Vladimirov, Igor G., Ian R. Petersen, and Matthew R. James. "A Girsanov Type Representation of Quadratic-Exponential Cost Functionals for Linear Quantum Stochastic Systems∗." In 2020 European Control Conference (ECC). IEEE, 2020. http://dx.doi.org/10.23919/ecc51009.2020.9143665.

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Charalambous, Charalambos D., and N. U. Ahmed. "Equivalence of decentralized stochastic dynamic decision systems via Girsanov's measure transformation." In 2014 IEEE 53rd Annual Conference on Decision and Control (CDC). IEEE, 2014. http://dx.doi.org/10.1109/cdc.2014.7039420.

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