[R-SIG-Finance] SPD and RND estimation
evgeny.panov at citi.com
Mon Jul 16 15:52:14 CEST 2007
Sorry, you are right. The concept of Black-Scholes implied volatility imposes parametric approach.
I tried to refer to it as a "cooking recipe" because this approach is indeed not perfect theoretically.
From: Brian G. Peterson [mailto:brian at braverock.com]
Sent: Monday, July 16, 2007 9:41 AM
To: Panov, Evgeny [CMB-EQTY]
Cc: Sankalp Upadhyay; R-sig-finance at stat.math.ethz.ch
Subject: Re: [R-SIG-Finance] SPD and RND estimation
Panov, Evgeny wrote:
> As a cooking recipe, will probably benefit a lot from first converting
> the prices into Black-Scholes implied volatilities and then smoothing
> the implied volatilities, after which you can go back into price space
> (don't worry about unknown dividend yield - you can back it out from
> put-call parity).
The problem with this approach is that the point of the cited
Ait-Sahalia and Lo paper is to do a non-parametric estimation of the
density function from prices. They propose the use of kernel smoothing
regression, although other non-parametric methods are cited in other papers.
Ait-Sahalia, Yacine and Lo, Andrew W., "Nonparametric Estimation of
State-Price Densities Implicit in Financial Asset Prices" (November
1995). NBER Working Paper No. W5351.
Available at SSRN: http://ssrn.com/abstract=225414
> -----Original Message-----
> From: Sankalp Upadhyay
> Sent: Sunday, July 15, 2007 8:55 AM
> I am trying to do an estimation of State Price Density (SPD) and Risk
> Neutral Density (RND) from a set of option prices - preferably in a
> non-parametric way.
> Is there some package in R that can help? fOptions does not seem to be have
> Alternatively, would you know a standard method or a very good research
> paper/article/reference on this topic? The utility being that a good
> paper/article can be changed to R code easily.
> Many thanks,
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