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....

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...

We provide an accurate approximation method for inverting an option price to the implied volatility under arithmetic Brownian motion, which is widely quoted in Fixed Income markets. The maximum error in the volatility is in the order of 10-10 of the given option price and much smaller for the...