Cover -- Title Page -- Copyright -- Contents -- Chapter 1 Do Algorithms Dream About Artificial Alphas? -- 1.1 Introduction -- 1.2 Replication or Reinvention -- 1.3 Reinvention with Machine Learning -- 1.4 A Matter of Trust -- 1.5 Economic Existentialism: A Grand Design or an Accident? -- 1.6...

Nowadays commodity investing is facing a tremendous interest from all kinds of investors, the surging amount invested in commodity related indices being one of the manifestations of this phenomenon. Due to their historical de-correlation with conventional securities and their hedging properties...

This paper examines the forecasting performance of GARCH's models used with agricultural commodities data. We compare different possible sources of forecasting improvement, using various statistical distributions and models. We have chosen to confine our analysis on four indices which are the...

We build regression trees to determine which firm characteristics are most likely to drive future returns. Out of 30 attributes, those related to momentum appear to have, by far, the most marked impact. This prominence is verified at the sector level as well. The second order effects are...

In this chapter, we apply a popular Machine Learning approach (extreme gradient boosted trees) to build enhanced diversified equity portfolios. A simple naïve equally-weighted portfolio of US stocks based on a boosted tree-based signal generates on average an excess return of 3.1% per annum,...

In this article, we investigate the impact of truncating training data when fitting regression trees. We argue that training times can be curtailed by reducing the training sample without any loss in out-of-sample accuracy as long as the prediction model has been trained on the tails of the...

Evolutionary algorithms are not new and have been developed, both their concepts and framework, since around the 1950's based on the idea that the evolutionary process could be used as a general-purpose optimization tool. The goal of this paper is to propose an alternative to classical...

This paper examines the forecasting performance of GARCH’s models used with agricultural commodities data. We compare different possible sources of forecasting improvement, using various statistical distributions and models. We have chosen to confine our analysis on four indices which are the...