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09:00 - 10:30: Eric Benhamou: CEO, Pricing Partners |  |
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Time dependent Heston model and fast calibration of stochastic volatility models:
- Introduction to the Malliavin small noise expansion
- Fast analytics for Time dependent Heston model
- Fast analytics for Piterbarg model with non zero correlation
- Deriving a fast and robust calibration for Heston and SABR
Break: 10:30 - 11:00
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11:00 - 12:30: Henrik Rasmussen: Global Head of Rates Quantitative Research & Dominique Bang: Quantitative Analyst, Bank of America Merrill Lynch | |
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Implied Volatility Asymptotics : A Twist On The Non-Linear PDE Approach (Rasmussen)
- In this talk, I will discuss short-time asymptotics for the implied volatility, starting from the non-linear PDE for the implied volatility
- This non-linear PDE is transformed into a non-linear integral equation that is more amenable to treatment
- Using formal short-time asymptotics, we obtain approximations for various models that have previously been considered in the literature
Quasi-Periodic and Periodic Decompositions: Alternatives to Transform Methods for Option Pricing (Bang)
- We present novel formulations for a call option as a periodic and quasi-periodic series
- These can be efficiently used for option pricing, as long as the characteristic function of the log-spot is known in closed form
- Bounds and error analysis are provided
- Eventually we apply the technique to Heston dynamics
Lunch: 12:30 - 13:30
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13:30 - 15:00: Julian Turc: Head of Cross-Asset Quantitative Research, Société Générale | |
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Using Changes of Measure to Estimate Arbitrage-Free Models of the Rates Curve
- We present a multi-factor affine model of the interest rate curve. The model leads to a specification of the curve that is similar to the Nelson-Siegel formula.
- The model involves three latent factors (level, slope and curvature), and considers risk premia between the historical and risk-neutral measures.
- We present an efficient way to estimate the model, using Kalman filtering and maximum quasi-likelihood.
This framework can be used to spot: relative value opportunities within the nominal curve, within the real curve, or between both curves. The model also leads to useful estimates of risk premia, and strips expected inflation out of market prices of inflation linked products. We also consider credit risk, and present credit-adjusted estimates for nominal risk premia.
Break: 15:00 - 15:15
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15:15 - 16:30: Manuel Torrealba: Head of Interest Rates Quantitative Analysis, Global Markets, BBVA | |
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Modelling the Spread and Applications to Callable Spread Options
- CMS Swaps and Spread Options
- Models for CMS Swaps
- Direct models for the spread
- Copula models for the spread
- Pricing CMS swaps and spread options with the LMM
- Adding Stochastic Volatility to the LMM
- Calibration of the LMM
- Application to the pricing of callable spread options
- Greeks analysis