Reinforcement learning for optimal control of stochastic nonlinear systems
AIChE Journal, EarlyView.Abstract A reinforcement learning (RL) approach is developed in this work for nonlinear systems under stochastic uncertainty. A stochastic control Lyapunov function (SCLF) candidate is first constructed using neural networks (NNs) as an approximator to the value function, and then a control policy designed using this SCLF is developed to ensure the ...
Xinji Zhu, Yujia Wang, Zhe Wu
wiley +1 more source
Stochastic Spot/Volatility Correlation in Stochastic Volatility Models and Barrier Option Pricing [PDF]
arXiv, 2014 Most models for barrier pricing are designed to let a market maker tune the model-implied covariance between moves in the asset spot price and moves in the implied volatility skew. This is often implemented with a local volatility/stochastic volatility mixture model, where the mixture parameter tunes that covariance.
arxiv
Regime-switching stochastic volatility model: estimation and calibration to VIX options
, 2017 We develop and implement a method for maximum likelihood estimation of a regime-switching stochastic volatility model. Our model uses a continuous time stochastic process for the stock dynamics with the instantaneous variance driven by a Cox–Ingersoll ...
Stéphane Goutte, Amine Ismail, H. Pham
semanticscholar +1 more source
Forecasting volatility: does continuous time do better than discrete time? [PDF]
In this paper we compare the forecast performance of continuous and discrete-time volatility models. In discrete time, we consider more than ten GARCH-type models and an asymmetric autoregressive stochastic volatility model.
Carles Bretó, Helena Veiga
core
Joint Situational Assessment‐Hierarchical Decision‐Making Framework for Maneuver Intent Decisions
Advanced Intelligent Systems, EarlyView.This study introduces a new framework for decision‐making in unmanned combat aerial vehicles (UCAVs), integrating graph convolutional networks and hierarchical reinforcement learning (HRL). The method tackles adopts a curriculum‐based training approach guided by cross‐entropy rewards.
Ruihai Chen +4 more
wiley +1 more source
Real Option Valuation with Stochastic Interest Rate and Stochastic Volatility
Matematika, 2019 . Real options are one of the most interesting research topics in Finance since 1977 Stewart C. Myers from MIT Sloan School of Management published his pioneering article on this subject in the Journal of Financial Economics.
Ramdhan Fazrianto Suwarman
doaj +1 more source
Econometric analysis of realised volatility and its use in estimating stochastic volatility models [PDF]
The availability of intra-data on the prices of speculative assets means that we can use quadratic variation like measures of activity in financial markets, called realised volatility, to study the stochastic properties of returns.
Neil Shephard, Ole E. Barndorff-Nielsen
core
Deep Learning Methods in Soft Robotics: Architectures and Applications
Advanced Intelligent Systems, EarlyView.Soft robotics has seen intense research over the past two decades and offers a promising approach for future robotic applications. However, standard industrial methods may be challenging to apply to soft robots. Recent advances in deep learning provide powerful tools to analyze and design complex soft machines that can operate in unstructured ...
Tomáš Čakurda +3 more
wiley +1 more source
On Calibrating Stochastic Volatility Models with time-dependent Parameters [PDF]
arXiv, 2010 We consider stochastic volatility models using piecewise constant parameters. We suggest a hybrid optimization algorithm for fitting the models to a volatility surface and provide some numerical results. Finally, we provide an outlook on how to further improve the calibration procedure.
arxiv
Seasonal Stochastic Volatility: Implications for the Pricing of Commodity Options
, 2016 Many commodity markets contain a strong seasonal component not only at the price level, but also in volatility. In this paper, the importance of seasonal behavior in the volatility for the pricing of commodity options is analyzed. We propose a seasonally
J. Arismendi +4 more
semanticscholar +1 more source