Traditionally, volatility is modeled using parametric models. This project focuses on predicting EUR/USD volatility using more flexible, machine-learning methods.
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Updated
Oct 20, 2021 - R
Traditionally, volatility is modeled using parametric models. This project focuses on predicting EUR/USD volatility using more flexible, machine-learning methods.
Estimation of realized quantities
R code and Realized Volatility (RV) series set for fitting NN-based-HAR models to multinational RV series.
Intraday volatility estimation using High-Frequency Financial Data
Replication of "Variance Risk Premia in the Interest Rate Swap market" paper (2016) by Desi Volker PhD
Code for the paper "Volatility is (mostly) path-dependent - Guyon, Lekeufack (2022)".
The workings for a very interesting exercise from the Econometrics of Financial Markets module of the MSc Quantitative Finance 2023/24 course at Bayes Business School (formerly Cass).
Calculation of stock realized variance based on trade data on WRDS cloud
R package to estimate and forecast the HAR (Heterogeneous Autoregressive) model and its extensions.
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