How 'bout buying it? Not too expensive ...Rgds.

<t>Duly noting that Aaron and David already ended the topic with market savvy answers, I can't help adding a short anecdote on convensions in the bond market. Take for example Bloomberg and the yields, dirty prices etc that it generates for bonds all over the world. Are all conventions correct you t...

<t>doubleV,does correlation really imply dependency? Or wasn't it the other way around.And no, correlation has nothing to do with normal distribution. Its only when you get around to summing up the parts that you have to use the appropriate method for the chosen distribution.However, I must say, the...

<t>I used to think long and hard on what the correlation between the price series might imply (if anything...) and have decided that correlation of price series will only tell you that the price have been on the "same side" of its period average compared with the other price more than vice versa. Th...

Depends on if the sigma is calculated using log prices or not. If so you should invert back using exponent. Otherwise your second setup is correct./Rutger

<t>Hi,depending on your underlying security you might use a different set of methods.1. For stockmarket or optionmarket holidays might not be relevant and hence the vol should be upscaled with about 250 trading days and not 365. If your in the energy business pricing is around the clock also on holi...

Many thanks!I obviously didn't get the search engine to work for me the first time. Trying once more gave results.I'm going to do some homework now... talk to you later (in a few years time or so /Rutger

I'm looking for some pointers and/or material on pricing PRDCs.What underlying termstructure models would be used (market practise)?Apart from not being able to find relevant market quotes to calibrate the model from, any other major pitfalls?Thanks!Rutger

<t>Bayes,I fooled around with your halton code and it directly resulted in some questions...When generating say 100 number in say 50 dimensions the first "columns" seem quasi random as I guess they should, but when looking at higher dimensions the columns seem to converge to "the same" random number...

Nicol,That's certainly one way to do it ...Will try the smoothing model for some other data (for a bit more illiquid examples),and see how it looks.Thanks for the link!Rgds,Rutger

<t>Sorry about being unclear. I'll exemplify from building zero curves from interest rate data. Then I see two options;1) use the actual zero yields (read impl. volatilities) and connect the points on the surface with some algorithm (usually bootstrap, but could be linear interpolation or some sort ...

<t>I'm working on a project to test different vol surface models based on ordinary B&S implied vols. The idea is similar to that taken when creating zero coupon curves, either an economic model with a "no arb constraint" or functional smooth models with weighted best fit approaches. There should...

<t>A good paper on modeling weather derivatives:On modelling and pricing weather derivatives by Peter Alaton , Boualem Djehiche , David Stillberger Abstract: The main objective of the work described is to find a pricing model for weather derivatives with payouts depending on temperature. Historical ...

<t>I have some experience from using a modified version of the Black-Litterman model to get the correct starting point and then adjusting the initial guess with own market view. This will give quite nice behaving portfolios. Remaining problems in the real world are, solving the mixed integer problem...

<t>Have you had a look at the commercial product 'Quantlab'? This is a complete developer environment with a totally open interface for real-time, timeseries and libs. It will give drag and drop functionality for all Qlang code you want to present in a workspace (i.e. tables or graphs). Regards, Rut...