Using Gaussian Processes for Financial Time Series Forecasting

The Python Lab
5 min readDec 1, 2023

In the field of finance, accurate forecasting of stock prices and other financial time series data is of utmost importance. Traders and investors rely on these forecasts to make informed decisions and maximize their profits. Traditional forecasting methods, such as ARIMA and GARCH models, have been widely used, but they often fail to capture the complex patterns and non-linear relationships present in financial data.

In recent years, Gaussian Processes (GPs) have gained popularity as a powerful tool for time series…

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