Results 111 to 120 of about 1,307,477 (404)
Hedging with Stochastic and Local Volatility [PDF]
We derive the local volatility hedge ratios that are consistent with a stochastic instantaneous volatility and show that this ‘stochastic local volatility’ model is equivalent to the market model for implied volatilities.
Carol Alexander, Leonardo M. Nogueira
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AIChE Journal, EarlyView.Abstract Integrated dynamic scheduling (IDS) and economic nonlinear model predictive control (eNMPC) enable economic operation of chemical plants subject to volatile energy prices. Herein, we combine the two concepts into an integrated two‐layer scheme. Therein, IDS performs “long‐horizon” scheduling on a day‐ahead (DA) market and eNMPC “short‐horizon”
Jan C. Schulze +3 more
wiley +1 more source
Pricing Parisian Option under a Stochastic Volatility Model
Journal of Applied Mathematics, 2014 We study the pricing of a Parisian option under a stochastic volatility model. Based on the manipulation problem that barrier options might create near barriers, the Parisian option has been designed as an extended barrier option. A stochastic volatility
Min-Ku Lee, Kyu-Hwan Jang
doaj +1 more source
, 2018 We consider a class of stochastic path-dependent volatility models where the stochastic volatility, whose square follows the Cox-Ingersoll-Ross model, is multiplied by a (leverage) function of the spot price, its running maximum, and time.
Cozma, Andrei, Reisinger, Christoph
core +1 more source
Generalized optimization framework for synthesis of thermally coupled distillation columns
AIChE Journal, EarlyView.Abstract In this article, a generalized optimization framework is proposed for the synthesis of thermally coupled distillation systems within an equation‐oriented environment. The proposed framework consists of three components: an efficient superstructure representation, a novel mathematical formulation, and the associated solution algorithm ...
Chao Liu, Yingjie Ma, Jie Li
wiley +1 more source
Super-replication in stochastic volatility models under portfolio constraints [PDF]
, 1999 Jakša Cvitanić +2 more
openalex +2 more sources
Sequential Bayesian Learning for Merton's Jump Model with Stochastic Volatility [PDF]
arXiv, 2016 Jump stochastic volatility models are central to financial econometrics for volatility forecasting, portfolio risk management, and derivatives pricing. Markov Chain Monte Carlo (MCMC) algorithms are computationally unfeasible for the sequential learning of volatility state variables and parameters, whereby the investor must update all posterior and ...
arxiv
AIChE Journal, EarlyView.Abstract Supply and manufacturing networks in the chemical industry involve diverse processing steps across different locations, rendering their operation vulnerable to disruptions from unplanned events. Optimal responses should consider factors such as product allocation, delayed shipments, and price renegotiation, among other factors. In such context,
Daniel Ovalle +6 more
wiley +1 more source
RETRACTED: Artificial intelligence for emergency medical care
Health Care Science, EarlyView., 2023 ‘Applications of artificial intelligence in emergency medical service’. Abstract There is increasing research into the potential benefits of incorporating artificial intelligence (AI) and machine learning algorithms into emergency medical services. AI is finding new applications across a wide range of sectors, one of which is healthcare, where it is ...
Shivam Rajput +2 more
wiley +1 more source
Stochastic Volatility and Pricing Bias in the Swedish OMX-Index Call Option Market [PDF]
This paper investigates the pricing bias in the Swedish OMX-Index Option market and how a stochastic volatility affects European call option prices. The market is purely European and without dividends for the period studied. A CIR square-root process for
Byström , Hans
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