SKILLS and COMPETENCIES

Computing and data science applied to finance

Data exploration and mining, with particular emphasis on handling large and complex financial
data sets.
Derivative pricing models. Theory and practice of Binomial trees and Montecarlo methodology
for European and American options and the Greeks.
R, Matlab and Python implementation of financial models and evaluation of different types of
derivative securities: European, American, standard, barrier and path dependent options on
stocks and interest rates.

Brownian motion, martingales, Ito integrals and Ito’s formula applied to Black-Scholes model
Fundamental statistical tools useful for fitting models to financial data, including those with complex
multivariate form. Basic statistical and probability theory, statistical distributions, copulas,
Bayesian inference, hypothesis testing, and regression.
Optimization models and their applications to finance problems ranging from asset allocation to
risk management.
Financial time series analysis including ARIMA modeling, forecasting, seasonality,
model identification and diagnostics. GARCH and stochastic volatility modeling

Investment Strategies: Options strategies for investment purposes.
Managing Option Positions
Volatility trading: Various strategies including Long and Short Straddles, Long and Short
Strangles, Butterflies, and Condors.