[PDF] Top 20 Stochastic Target Problem With Jump Diffusion.
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Stochastic Target Problem With Jump Diffusion.
... related stochastic differential equations in this model: the stock price process which is a forward stochastic differential equation and the wealth process which is a backward stochastic differential ... See full document
151
Optimal Portfolio Choice in a Jump Diffusion Model with Self Exciting
... (the jump intensity) following a Hawkes ...in jump intensity as ...of stochastic volatility and self-exciting, while the optimal investment problem is still solvable in sense of by an ... See full document
23
A Comparative Study of Equilibrium Equity Premium under Discrete Distributions of Jump Amplitudes
... under Jump-Diffusion Processes, and derived the appropriate characteri- zation of asset market equilibrium when asset prices follow jump-diffusion ...when jump risk is systematic and ... See full document
15
Sufficient stochastic maximum principle for the optimal control of semi Markov modulated jump diffusion with application to financial optimization
... of stochastic maximum principle and its application to finance has been credited to Cadenillas and Karatzas ...the stochastic maximum principle for jump-diffusion process and applied it to a ... See full document
26
Pricing Study on Two Kinds of Power Options in Jump Diffusion Models with Fractional Brownian Motion and Stochastic Rate
... optimal stochastic problem, in which the stochastic process sometimes follows jump-diffusion ...use jump-diffusion process instead of diffusion process to describe ... See full document
17
Analysis of Nonlinear Stochastic Systems with Jumps Generated by Erlang Flow of Events
... a problem of the probabilistic analysis for jump-diffusion ...the stochastic systems with jumps generated by Poisson flow of ...complex problem which assumes that we have Erlang flow of ... See full document
7
Option pricing under the double exponential jump‐diffusion model with stochastic volatility and interest rate
... In addition, we propose several other models that can explain the leptokurtic features and the volatility smile in option pricing. For example, Chen et al. (2016) proposed American option pricing under generalized mixed ... See full document
40
Exact Simulation of Jump Diffusion Processes with Monte Carlo Applications
... computational problem in financial ...a jump- diffusion stochastic interest rate pricing framework (see ...a jump-diffusion ... See full document
32
Pricing Options in Jump Diffusion Models Using Mellin Transforms
... The application of Mellin transforms for the purpose of option pricing was firstly introduced in [16] in the geometric Brownian motion economy. It was extended to the stochastic volatility model of Heston by ... See full document
8
Stochastic Volatility Jump Diffusion Model for Option Pricing
... In this paper, we would like to consider the problem of finding a closed-form formula for a European call option where the underlying asset and volatility follow the Model (3). This formula will be useful for ... See full document
8
Jump Diffusion Calibration using Differential Evolution
... The estimation of a jump-diffusion model via Differential Evolution is presented. Finding the maximum likelihood estimator for such processes is a tedious task due to the multimodality of the likelihood ... See full document
7
Duopolistic Competition and Capacity Choice with Jump Diffusion Process
... a standard Brownian motion. We assume ρ µ > to ensure that the option is exercised within a finite period of time. We assume random sudden events follow the Poisson jump process of intensity λ . This means ... See full document
10
THE MIXING APPROACH TO STOCHASTIC VOLATILITY AND JUMP MODELS
... This book provides an advanced treatment of option pricing for traders, money managers, and researchers. Providing largely original research not available elsewhere, it covers the new generation of option models where ... See full document
22
Solution of Stochastic Cubic and Quintic Nonlinear Diffusion Equation Using WHEP, Pickard and HPM Methods
... sidered as the main disad tage of M. The idea of imbedded parameter can be utilized to solve nonlinear problems by imbedding this parameter to the problem and then forcing it to be unity in the obtained approxi- ... See full document
16
On the calculation of price sensitivities with jump diffusion structure
... an approach that can be used to remedy the shortcomings of the Black and Scholes model. This is achieved by developing a method for the computation of the price sen- sitivities of a trading position with respect to four ... See full document
22
Derivatives pricing in a Markov chain jump diffusion setting
... this diffusion process jumps in the asset price which occur when the market changes state, and the jump sizes are dependent on the states the market is transiting to and transiting ...a jump in the ... See full document
242
Coupling polynomial Stratonovich integrals : the two dimensional Brownian case
... In this article, we have constructed a successful Markovian coupling for the two- dimensional Brownian motion along with a finite collection of its monomial Stratonovich integrals. In the context provided by Theorem 3, ... See full document
45
Taylor approximation of stochastic functional differential equations with the Poisson jump
... initial equation increases when the number of degrees in Taylor approximations of coef- ficients increases. Although the Poisson jump is concerned, the rate of approximation to the true solution by the numerical ... See full document
10
Computational Studies on Detecting a Diffusing Target in a Square Region by a Stationary or Moving Searcher
... diffusing target in the presence of a stationary or moving ...the target diffuse with significant diffusion coefficients, the decay rate of the non-detection probability only de- pends on the sum of ... See full document
23
Scatter Search With Trio Population For Solving Stochastic Weapon-Target Assignment Problem
... Weapon Target Assignment (WTA) problem is a well-known combinatorial integer programming problem of the operations research and optimization ...a stochastic nonlinear integer programming ... See full document
6
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