We introduce a new methodology for forecasting which we call Signal Diffusion Mapping. Our approach accommodates features of real world financial data which have been ignored historically in existing forecasting methodologies. Our method builds upon well-established and accepted methods from...

Finding what causes pricing anomalies is an important step towards improving market efficiency. The favourite-longshot bias is one of the longest-standing pricing anomalies in state-contingent claims markets. However, existing models are unable to capture its full complexity. We develop a...

Motivated by the seasonality found in equity returns, we create a Turn-of-the-Month (ToM) allocation strategy in the U.S. equity market and investigate its value in asset allocation. By using a wide variety of portfolio construction techniques in an attempt to address the impact of estimation...

The yield curve is the centrepiece in bond markets, a massive asset class with an overall size of USD100 trillion that remains relatively under-investigated using machine learning. This paper is the first comprehensive study using artificial neural networks in the context of yield curve...