mdsunivie/HARNet
TensorFlow implementation of the HARNet model for realized volatility forecasting.
This tool helps financial professionals, like quantitative analysts or traders, predict how much stock prices or other assets might fluctuate in the future. It takes historical data on asset price movements (realized volatility) and outputs a forecast for future volatility. This allows you to better understand and manage investment risk.
No commits in the last 6 months.
Use this if you need to generate accurate forecasts of market volatility for financial assets.
Not ideal if you're looking for a general-purpose time series forecasting tool outside of financial market volatility.
Stars
28
Forks
5
Language
Python
License
MIT
Category
Last pushed
Jul 16, 2023
Commits (30d)
0
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