Join us on :
Home >> News & Events >> Press Release >> The Paris Finance International Meeting - Dec 07
The Paris Finance International Meeting - Dec 07

 

 

Pricing Partners Derivatives-Pricing-Analytics-Independent-Valuation  
 

December 4th, 2007 – Zaizhi Wang (Cerna, Ecole des Mines de Paris), quant analyst for Pricing Partners speaks at the Paris Finance International Meeting held on the 20th and 21st of December.

Subject of discussion: “Effective” parameters for stochastic volatility models.

The paper presented by Zaizhi wang tackles the issue of approximated formula for stochastic model with time dependent model parameters, using an averaging principle.

The idea lies in finding a similar model but with constant parameters that is the closest to our initial process, along the same lines as results proven by Gyöngy (1986) for general stochastic processes. We extend previous results found by Piterbarg (2005) for the particular case of SABR model (Hagan (2002)). The resulting formula can be evaluated very quickly solving the implied Riccati equations. We compare the approximation with the exact solution of the corresponding partial differential equation using an ADI method. Numerical results show that the approximation works well for short term maturities.

Sponsored by: 

 

 

 

 

About Pricing Partners

Founded by professionals of the trading floor industry, Pricing Partners provides software solutions and consulting services for derivatives independent valuation. Pricing Partners proposes Price-it®, an independent analytic library solution to price complex financial products on different markets (IR, Equity, Credit, Inflation, Hybrids, Commodities and FX). 

The Pricing Partners solution enables users to comply with accounting standards evolution as well as regulation evolutions in a capital market industry related to independent valuation issues of OTC products. Price-it® principally targets asset-managers, financial departments of large banks, dealing rooms and audit firms. The company is based in Paris.