Quant

Crisil

1. Validation of financial models (Counterparty Credit Risk desk)
2. o Modeling and methodologies used to estimate PFE for different derivatives within asset classes,
3. including Forward Contracts, FX, IR and Equity Swaps and Options (Vanilla, American & Exotic
4. such as Asian, Cliquets and Bermudan Options). Assessment of EE, MPE and PFE up to 30Y in the
5. future for each derivative. Typically using the 97,5 percentile of prices in the future for PFE.
6. Worked with data bases in the Big Data range, performed SQL queries and preliminary data
7. analysis with pandas’ Python library. Use of Black-Scholes differential equation and derivativespecific variants of this equation. Whenever possible, back-tested the models to assess past
8. performance.
9. o Benchmarking with CVA measures and other pricing models. PFE pricing models tend to be less
10. accurate than other pricing models but with a faster performance. Impact assessment of the
11. differences in business Portfolio.
12. o Impact of interest rates simulation models. Interest rates simulation is a fundamental key used to
13. estimate PFE and so the choices made in the simulation model used to price the derivatives in
14. the future have a great impact on PFE. Worked with Monte Carlo simulations for Vasicek,
15. Exponential Vasicek, & Hull-White models using numpy and scipy python libraries.
16. o Impact of stochastic volatility simulation models. Worked with Heston and SABR models.
17. o Use of FRTB. Tested if the PFE models used are under these regulations.
18. o Statistical testing of multiple hypothesis. Benchmarking development and back-testing.
19. o Mathematical research applied to finances to help making desk better decisions.
20. o Validation of the following models:
21. PFE FX Forwards/Swaps/Window Swaps pricing models. Developed python tools to calculate PFE
22. on these derivatives using simulated interest rate matrices as inputs.
23. PFE Equity Swaps, PFE Equity European Vanilla Options, PFE Equity American Options, PFE Equity
24. Asian Options, PFE Equity Variance Swaps, Equity Basket Options. Developed python tools to
25. calculate PFE on these derivatives using simulated interest rates, simulated stock prices and
26. simulated stochastic volatility matrices as inputs. Worked with 3 different models to calibrate
27. SABR parameters used in ATM stochastic volatility simulation and with simulated VIX.
28. PFE Equity Cliquets, PFE Equity Barrier Options (KO and NKO). P-value approach to hypothesis
29. testing.
30. PFE IR Bermudan Options. P-value approach to hypothesis testing.
31. o Monte Carlo simulations. Interest Rates Simulation models used to simulate USD-OIS and LIBOR
32. curves, among others. Impact assessment of the calibration modeling choices for Vasicek and
33. Exponential Vasicek parameters. Benchmarking with multivariate Ornstein-Uhlenbeck and HullWhite process. Worked with correlated random variables.
34. o Monte Carlo simulations. Geometric Brownian Motion used to simulate stocks and index prices.
35. Volatility surface simulation and SABR calibration.
36. o Contributed with thousands of lines of code (using Git) to develop pricing and simulation libraries.

Instituto Balseiro

Physics