Mixture Density Network for Forecasting Realized Volatility

Posted on Wed 07 April 2021 in Volatility • Tagged with volatility, forecasting, mixture-density-network, machine-learning, pytorch, model-building

Using a mixture density neural network implemented in PyTorch to forecast the distribution of future realized volatility.


Continue reading

Bayesian Autoregressive Volatility Forecasting

Posted on Wed 17 March 2021 in Volatility • Tagged with volatility, forecasting, bayesian, model-building

Using a simple bayesian autoregressive model to forecast future volatility


Continue reading

Comparison of Volatility Estimators

Posted on Sun 07 March 2021 in Volatility • Tagged with volatility, realized-volatility

Comparing Garman-Klass estimator to 5-minute Realized Volatility estimator.


Continue reading