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Perhaps the question is a bit vague. So, I have a starting equation (Schwartz model) given by: . To estimate the parameters of the equation, first I use x=lnp, and using Ito lemma I transform this equation into an OU process given by: . For OU I estimate all the parameters. Now I need to go back to the initial equation. As I know E[x_t], I also know that E[p_t]=exp[E[x_t]]. Then I need to calculate the variance of p_t. I know...

You keep explaining that you have a pool of assets whose value only diminishes with jumps due to credit events. Of course, this pool *must* also be either throwing off some income to investors or accruing income -- otherwise no one would buy it. So, my suggestion is: - Explain in detail the nature of the product. - What exacty are the cash flows and terms for somebody (i) who holds the underlying assets?; (ii) who holds the option on the pool...

Hi J, I'm not too familar with real options; just had some thoughts in my head for what I would do. Concerning the closed form for vanilla options on OU that's not to hard - you'll find an analytical formula for at page 11 of http://www.wiwi.uni-muenster.de/vwt/organisation/veroeffentlichungen/5_WP_Pricing_Electricity_Derivatives.pdf. Calibration could be found at http://sitmo.com/doc/Calibrating_the_Ornstein-Uhlenbeck_model....

To my knowledge any sophisticated model is rubbish for cms spd options. Because of the simple correlation structure used in sophisticated models.

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The paper below deals with modelling the basis swaps spreads by the counteparty risk embed in Libor, not in the basis swap itself which is collateralized. The point here however is not the credit risk itself, that alone does not explain market patterns, but the fact that Libor flows with different tenors involve different options on the credit quality of the counterparty. In the application to market data, what is captured is probably a mix...

Hello Costeanu, thanks for your detailed answer. We had a similar discussion, using historical volatility of the same asset and adjust our implied volatility with it. The problem is, that the historical volatility is not well correlated for the product or say not stable. We get illiquid market data for our commodity products and at the moment it is not so easy to find a well correlated asset/index, because we are often rely on the broker...

Ok, my mistake. The correction is around a couple of bps.

Thanks for the reply so far. I have implemented DD and have approx formulae for swaptions and exact ones for caplets. The same with CEV. But I do not trust my prices coming from CEV. I have matched the prices from Andersens 98 paper but I thought that DD and CEV with well chosen parameters should lead to nearly the same prices for European vanillas, i.e. caplets... But they don't in my setup. If someone has set up this setting I would be...