So, I'm in need of some tips regarding a small project I'm doing. My goal is an implementation of a Fast Fourier Transform algorithm (FFT) which can be applied to the pricing of options. First ...
When applying the Heston model to generate the sample volatility surface, some of the volatility value will be negative. I am just wondering what do practioners normally do with these negative value. ...
Heston - How important are the initial guess in calibration and if it is very important, what would be a good way to get initial guess?
So I have been trying to implement a simple Heston calibration using crude MC with 10k scenarios and 1000 time steps and the best I could get is 3x of the observed implied volatility. I suspect it ...
Why do we model it as sqrt root of v(t)? Is that because we don't want the volatility to go negative? If this is the case, can we model it as square of v(t)?