Machine Learning in Fixed Income Markets

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The yield curve is the centrepiece in bond markets, a massive asset class with an overall size of USD 100 trillion that remains relatively under-investigated using machine learning. The objective of this project is to extend existing machine learning models to the fixed income asset class, by developing innovative applications of machine learning models and techniques for the financial industry, leading to better forecasting systems. Overall, it includes assessing and adapting existing techniques to model and forecast the yield curve (i.e. interest rates as a function of time to maturity) and evaluate potential benefits of multitask learning (i.e. simultaneous modelling of several dependent variables) when compared to single task learning, resulting from transformation of the problem into independent single-target processes. The main societal value of this research is directly related to the importance of bonds in pension fund and insurance portfolio holdings. But several sectors of society and industry could benefit directly from this research, including central banks' policy making, the asset and risk management industry, and academia.