@article {Chen1, author = {Jiaqi Chen and Michael Tindall}, editor = {Aidan Byrne, John}, title = {Practical Applications of The Structure of a Machine-Built Global Macro Forecasting System}, volume = {4}, number = {3}, pages = {1--4}, year = {2017}, doi = {10.3905/pa.2016.4.3.201}, publisher = {Institutional Investor Journals Umbrella}, abstract = {The Structure of a Machine-Built Global Macro Forecasting System Jiaqi Chen Michael Tindall Jiaqi Chen and Michael Tindall, both of the Federal Reserve Bank of Dallas , sidestepped the controversy surrounding automated model-building systems in their approach to developing their unique {\textquotedblleft}theory-free{\textquotedblright} system.In The Structure of a Machine-Built Global Macro Forecasting System , the authors explain how they used empirical investigation of model construction to develop their automatic model-building system, rather than starting with an existing theory.Tindall explains that their system can produce forecasting models for foreign economies that don{\textquoteright}t require users to have any prior knowledge of the institutional frameworks of those economies. {\textquotedblleft}Obviously, the machine system should be of interest to global macro hedge funds since those funds, by definition, focus on the market effects of international macroeconomic data,{\textquotedblright} he points out.}, issn = {2329-0196}, URL = {https://pa.pm-research.com/content/4/3/1.3}, eprint = {https://pa.pm-research.com/content/4/3/1.3.full.pdf}, journal = {Practical Applications} }