Pyxis has expertise in quantitative finance, analytical modeling, numerical methods and statistical analysis. Our research rests on advanced analytical library called ‘RisKanalytics’ developed in-house by Pyxis.

Pyxis experience in financial modeling and risk management ranges over Foreign Exchange, Interest Rate, Equity and Credit asset classes. Our quantitative abilities include:

Developing analytics for derivatives structures, structured products.
Index linked capital guaranteed products with long dated vanilla, barrier options, binary options, snowball options, Asian options, target redemption forward, range accruals and basket products.

Model calibration, implementation and back testing Models.
Models – Black-Scholes-Merton ( BSM), Variance Gamma(VG), Black-76, Garmann Kohlhagen, Constant Elasticity of variance ( CEV), Heston stochastic volatility model, UVUR(Uncertain Volatility Uncertain Rate) model, Vanna-Volga model for volatility smile, GARCH volatility forecast, Hull & White short rate models, Binomial/trinomial tree based pricing, static hedges for exotics etc.

Model Validation through historical back-testing and stress testing

• Pricing
  Binomial and trinomial trees, finite different method, Monte Carlo method with variance reduction techniques, static replication, dynamic hedging and closed forms.
• Value at Risk ( VaR) and credit exposure(CORE-KOMPASS)
  Historical, Monte Carlo and Parametric methods
• Statistical Models
  Time Series Analysis models (such as GARCH, eGARCH, ARMA, ARIMA)
• Analytics
  Random number generation, implied binomial and trinomial trees, multi-variate statistics (correlation, copulas), time series analysis, optimization, root finding.