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In this paper a method is developed and implemented to provide the simulated maximum likelihood estimation of latent diffusions based on discrete data. The method is applicable to diffusions that either have latent elements in the state vector or are only observed at discrete time with a noise....
Persistent link: https://www.econbiz.de/10010539803
In this paper a method is developed and implemented to provide the simulated maximum likelihood estimation of latent diffusions based on discrete data. The method is applicable to diffusions that either have latent elements in the state vector or are only observed at discrete time with a noise....
Persistent link: https://www.econbiz.de/10009274322
We develop an asymptotic expansion technique for pricing timer options in stochastic volatility models when the effect of volatility of variance is small. Based on the pricing PDE, closed-form approximation formulas have been obtained. The approximation has an easy-to-understand...
Persistent link: https://www.econbiz.de/10010785478
We provide two new closed-form approximation methods for pricing spread options on a basket of risky assets: the extended Kirk approximation and the second-order boundary approximation. Numerical analysis shows that while the latter method is more accurate than the former, both methods are...
Persistent link: https://www.econbiz.de/10005619404
In this paper a method is developed and implemented to provide the simulated maximum likelihood estimation of latent diffusions based on discrete data. The method is applicable to diffusions that either have latent elements in the state vector or are only observed at discrete time with a noise....
Persistent link: https://www.econbiz.de/10010704589
In this paper, we develop a framework for pricing two dimensional derivatives under stochastic correlation. Closed form approximations for the price of these derivatives are provided based on Taylor's expansions of known price function under constant correlation. Two families of stochastic...
Persistent link: https://www.econbiz.de/10010817012
This paper develops a maximum likelihood (ML) method to estimate partially observed diffusion models based on data sampled at discrete times. The method combines two techniques recently proposed in the literature in two separate steps. In the first step, the closed form approach of Aït-Sahalia...
Persistent link: https://www.econbiz.de/10011052260