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arXiv:2310.13357stat.AP

The M6 forecasting competition: Bridging the gap between forecasting and investment decisions

Spyros Makridakis, Evangelos Spiliotis, Ross Hollyman, Fotios Petropoulos, Norman Swanson, Anil Gaba

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Abstract

The M6 forecasting competition, the sixth in the Makridakis' competition sequence, is focused on financial forecasting. A key objective of the M6 competition was to contribute to the debate surrounding the Efficient Market Hypothesis (EMH) by examining how and why market participants make investment decisions. To address these objectives, the M6 competition investigated forecasting accuracy and investment performance on a universe of 100 publicly traded assets. The competition employed live evaluation on real data across multiple periods, a cross-sectional setting where participants predicted asset performance relative to that of other assets, and a direct evaluation of the utility of forecasts. In this way, we were able to measure the benefits of accurate forecasting and assess the importance of forecasting when making investment decisions. Our findings highlight the challenges that participants faced when attempting to accurately forecast the relative performance of assets, the great difficulty associated with trying to consistently outperform the market, the limited connection between submitted forecasts and investment decisions, the value added by information exchange and the "wisdom of crowds", and the value of utilizing risk models when attempting to connect prediction and investing decisions.

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stat.APApplications (Statistics)

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    • That was true in the first Makridakis competition ("M1") in 1982, and possibly until M4 in 2018, but both M5 and M6 were won by what would generally be considered relatively sophisticated methods (e.g. LightGBM). The Wikipedia article doesn't have that much detail on M5 or M6…

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