JRO Futures bridges the gap between mathematical theory and financial practice, providing the essential tools and techniques needed to implement the key quantitative models adopted in the financial markets, including:
Stochastic process, Wiener and Itô’s processes, geometric Brownian motions, Ornstein-Uhlenbeck processes, stochastic interest rate.
JRO Futures helps to Implementing investment strategies using financial econometrics such as econometrics of derivatives, vector autoregressive moving average (VARMA) process, building and testing a multiple linear regression model, hypothesis testing, portfolio return measurement, multifactor models.
Cos-Ross-Rubinstein model, martingale, The Bates model, derivative pricing.
Derivative valuation, portfolio valuation.
Volatility options, VaR (Parametric VaR, Historical VaR), GARCH, VGARCH, ARIMA, interest rate derivatives.
JRO Futures provides analytical, technical and programming skills relevant to the analysis of risk and return in financial institutions and large corporations. In addition, JRO Futures provides quantitative models in R Programming, Python, Matlab, and Stata, as well as Stochastic Calculus, Investment and Market Risk Forecasting and Control, as well as algorithmic trading models. Quantitative methods for investment analysis, including:
- Hypothesis testing concerning mean and variance, two quantities used in investments.
- Correlation and regression, confidence intervals and testing hypotheses in investments.
- Multiple regression and issues in regression analysis in investments.
- Time series analysis, portfolio mean-variance analysis and diversification, multifactor models.