A Note on Hugo
My comments on how Hugo compares to Pelican for static site generation
My comments on how Hugo compares to Pelican for static site generation
Using PyTorch to easily compute Option Greeks first using Black-Scholes and then Monte Carlo methods.
Using a mixture density neural network implemented in PyTorch to forecast the distribution of future realized volatility.
Using a simple bayesian autoregressive model to forecast future volatility
Comparing Garman-Klass estimator to 5-minute Realized Volatility estimator.
Constructing a portfolio from a selection of ETFs to maximize the diversification ratio