Investigating the effects of illiquidity on credit risks via new liquidity augmented stochastic volatility jump diffusion model

Optimization ◽  
2021 ◽  
pp. 1-29
Author(s):  
Esma Gaygısız ◽  
Abdullah Karasan ◽  
Alper Hekimoğlu
Keyword(s):  
Stochastic Volatility ◽  
Diffusion Model ◽  
Jump Diffusion ◽  
Credit Risks ◽  
Jump Diffusion Model

scholarly journals LONG MEMORY VERSION OF STOCHASTIC VOLATILITY JUMP-DIFFUSION MODEL WITH STOCHASTIC INTENSITY

2020 ◽  
Vol 38 (2) ◽  
Author(s):  
Somayeh Fallah ◽  
Farshid Mehrdoust
Keyword(s):  
Stochastic Volatility ◽  
Long Range ◽  
Diffusion Model ◽  
Long Memory ◽  
Stock Price ◽  
Real Data ◽  
Jump Diffusion ◽  
Heston Model ◽  
Long Range Dependence ◽  
Jump Diffusion Model

It is widely accepted that certain financial data exhibit long range dependence. We consider a fractional stochastic volatility jump diffusion model in which the stock price follows a double exponential jump diffusion process with volatility described by a long memory stochastic process and intensity rate expressed by an ordinary Cox, Ingersoll, and Ross (CIR) process. By calibrating the model with real data, we examine the performance of the model and also, we illustrate the role of long range dependence property by comparing our presented model with the Heston model.

scholarly journals Equilibrium Asset and Option Pricing under Jump-Diffusion Model with Stochastic Volatility

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Xinfeng Ruan ◽  
Wenli Zhu ◽  
Shuang Li ◽  
Jiexiang Huang
Keyword(s):  
Option Pricing ◽  
Stochastic Volatility ◽  
Diffusion Model ◽  
Jump Diffusion ◽  
Transformation Method ◽  
Exact Expression ◽  
Risk Neutral ◽  
Jump Diffusion Model ◽  
Fourier Transformation Method ◽  
Relationship Of

We study the equity premium and option pricing under jump-diffusion model with stochastic volatility based on the model in Zhang et al. 2012. We obtain the pricing kernel which acts like the physical and risk-neutral densities and the moments in the economy. Moreover, the exact expression of option valuation is derived by the Fourier transformation method. We also discuss the relationship of central moments between the physical measure and the risk-neutral measure. Our numerical results show that our model is more realistic than the previous model.

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