Neural Differential Equations in Financial Modelling with Python.

Financial modelling is a crucial aspect of decision-making and risk management in the world of finance. Traditionally, time-series prediction techniques have been fundamental in forecasting financial trends. However, with the advancements in machine learning and deep learning, the application of neural differential equations has brought about a paradigm shift in financial modelling.

In this tutorial, we will explore the significance of neural differential equations in financial modelling and its potential to surpass the limitations of traditional time-series prediction techniques. We will delve into the background and theory behind both traditional methods and neural differential equations, followed by a comprehensive implementation of neural differential equations using Python.

Subsequently, we will apply these techniques to a case study in financial modelling, demonstrate the experimental results and finally, conclude with a summary of the benefits and potential of neural differential equations in financial modelling with Python.

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Table of Contents

1. Background and Theory: Explaining traditional time-series prediction techniques and their limitations
2. Implementation of Neural Differential Equations in Python: Discussing…