Aditya Vyas

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Modelling Uncertainty: The Laplace’s Rule of Succession

The Laplace's Rule of Succession forms a very important cornerstone of probability and uncertainty theory. It aims to provide us with a way of associating some probability with an unobserved event based on previous observed events. I came upon it in the following textbook - Introduction to Probability by Bertsekas - in one of the exercise problems at the end of one of the chapters. Curiosity got the better of me and I soon found myself reading all about this rule/law and why is it so important.

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Aditya VyasProbability TheoryComment
Simulating a Reddit Thread using BERT and GPT2
Simulating a Reddit Thread using BERT and GPT2

Its a great time to follow the trends and research in natural language processing (NLP). Every other day researchers publish new model architectures and techniques which try to improve the current state-of-the-art (SOTA) models. However, even though there is an abundance of different architectures and methods, almost all of these are based on 2 main ideas - Attention Models and the Transformer Architecture.

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Aditya VyasMachine Learning, NLP, Data ScienceComment
The Hierarchical Risk Parity Algorithm: An Introduction
The Hierarchical Risk Parity Algorithm: An Introduction

Portfolio Optimisation has always been a hot topic of research in financial modelling and rightly so - a lot of people and companies want to create and manage an optimal portfolio which gives them good returns. There is an abundance of mathematical literature dealing with this topic such as the classical Markowitz mean variance optimisation, Black-Litterman models and many more. Specifically, Harry Markowitz developed a special algorithm called the Critical Line Algorithm (CLA) for this purpose which proved to be one of the many algorithms which could be used in practical settings.

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Quantitative FinanceAditya VyasQuantitative Finance, Machine Learning, Portfolio OptimisationComment