approaches to calibrating a Heston model

The characteristic function of the Heston model, as modified according to Gatheral (2006), is given by:

φ_H(t; w) = exp[C(t,w)̅V + D(t,w)V₀ + iwln(S₀e^(rt))]

whereV ̅ is the long-term variance, V₀ is the initial variance, S₀ is the initial stock price, r is the risk-free rate, and w is the frequency variable. The coefficients C(t,w) and D(t,w) are given by:

C(t,w) = ((r i w - λ θ)/σ^2) * (1 - e^(-λ t)) + (θ/(2λ)) * ((λ - r i w) t - 2 ln((1 - g e^(-λ t))/(1 - g)))

and

D(t,w) = (1/σ^2) * (1 - e^(-λ t)) * ((r i w - λ θ)/λ - 1/2) + (1/λ^2) * {(λ - r i w)(1 - e^(-λ t)) - 2(ln(1 - g e^(-λ t)) - g e^(-λ t))}

where λ is the mean reversion rate, θ is the long-term variance, σ is the volatility of volatility, and g = (λ - r i w)/(λ + r i w) is the damping factor.
 
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I always wondered about these insane statistical analyses equations I have seen for the BSM options...Do they predict where your option is going to go tomorrow, when Powell opens his mouth and testifies. or the NFP report on Friday?

It is a 1:1 bet on the market (or individual stock) going up or down. WTF does this nuclear particle physics math have to do with that?
 

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well, it works, great, now to test the inversion and implement the heston characteristic... then expand that out into the lifted heston then i'll have a rough volatilty model up and going ready to be calibrated.. then the joint SPX/VIX calibrator not far behind
 

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you have to finagle it, and treat it like its some autistic genius savant who took a bunch of acid and takes everything literally and lives by the lyrics of this song

 
I don't know how well this method works. I prompted chatgpt like this:

Please read the document at https://ocw.mit.edu/courses/18-s096...de23e5c59c04512954a8b_MIT18_S096F13_pset3.pdf and answer question 2(b).

Here is her response:

Code:
Sure, I'd be happy to help!

In question 2(b) of the document you provided, we are asked to find the
expected value and variance of the maximum of two random variables.

[snip] ...

In summary, we have found that the expected value of the maximum of two
iid random variables X and Y is twice the expected value of X (or Y), and
the variance of the maximum is twice the variance of X (or Y).


This response of course has absolutely nothing to do with the query posed.
Question 2(b) involves Sherman-Morrison-Woodbury and LOO cross validation betas, not expected values of iid random variables.

Note also the tone of confidence. Chatgpt seems never to answer "I don't know" or "I'm not that good with linear algebra so I can't answer your question." In this way she resembles the biggest bullshitters (aka best salesmen) I have come across in my years in this field.

I've attached the relevant document in case anyone wants to verify this or might
want to venture a guess on the genesis of such a non-answer.
previous reply was meant for you KS
 
previous reply was meant for you KS
You mean the post where you say that to get a good answer out of chat gpt you have to "treat it like its some autistic genius savant who took a bunch of acid and takes everything literally...?"

That sounds like a lot of work! How many hours of back and forth before you were able to get it to produce the FourierTransform in the FourierTransformTest class in the screengrab posted above?
 
You mean the post where you say that to get a good answer out of chat gpt you have to "treat it like its some autistic genius savant who took a bunch of acid and takes everything literally...?"

That sounds like a lot of work! How many hours of back and forth before you were able to get it to produce the FourierTransform in the FourierTransformTest class in the screengrab posted above?
more than I'd like but i was moving quite slow damn neck pinched. piece of cake now that i figured out the technique, i could see it becoming a more streamlined feature
 
more than I'd like but i was moving quite slow damn neck pinched. piece of cake now that i figured out the technique, i could see it becoming a more streamlined feature

I still apparently haven't got it down:

Q) ChatGPT, can you prove the Riemann Hypothesis for me?

A) I'm sorry, but I cannot prove the Riemann Hypothesis for you. The Riemann Hypothesis is one of the most famous unsolved problems in mathematics, and it has remained unproven for over 160 years despite the best efforts of many mathematicians...
 
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