The Structure of a Machine-Built Global Macro
Forecasting System

Abstract

This article presents an automated forecasting system that provides a macroeconomic forecasting approach that some hedge funds may find useful. The authors describe the structure of an econometric forecasting system designed to produce multiequation econometric forecasting models of national macroeconomies. They also describe the functioning of an automatic model-building system that builds the forecasting equation for each series submitted and produces forecasts of the series without human intervention. The automatic model-building system employs information criteria and cross-validation in the equation building process, and it uses Bayesian model averaging to combine forecasts of individual series. The system outperforms standard benchmarks for a variety of macroeconomic datasets. To demonstrate its use, the automatic system is used to build a fixed-income macro trading system.

TOPICS: Real assets/alternative investments/private equity, global, big data/machine learning, performance measurement