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WealthTech | Artificial Intelligence | Machine Learning | Look-Through | Risk

Part I - Introduction to Artificial Neural Networks

In this article series, we present a machine learning-based approach to solving a common problem in financial modelling where one is faced with the task of estimating the value of a function which requires a significant amount of computation to evaluate. More specifically, a function that corresponds to a so-called nested simulation aimed at, for example, estimating a capital requirement for a financial institution or the risk associated with a structured product for a retail investor.
2020-11-05
The approach we present is based on Artificial Neural Networks (ANNs) which previously have been successfully applied in many contexts such as Image recognition and Natural Language Processing. As we shall see later in the series, this fairly modern technique has the potential to improve the accuracy of more traditional methods.
The first article in the series therefore introduces ANNs in terms of how they are defined and what considerations to make when training them.
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Part II - Artificial Neural Networks as a Substitute to LSMC and Nested Simulations
Part III - Portfolio Construction - The Real World Analysis
Beyond Modern Portfolio Theory: Expected Utility Optimisation
Part II - Portfolio Construction - Sampling & Optimisation
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