Algorithmic trading on the MIB based on investor sentiment, measured by fan tokens of Italian football teams

Abstract

The objective of this research is to investigate the utility of football teams' fan tokens as an indicator of investor sentiment and, consequently, as a leading predictor of financial market movements. This study falls within the domain of behavioral finance, which has previously demonstrated how investor sentiment, influenced in part by sports outcomes, can impact financial markets and serve as an early barometer of market trends. We have developed an algorithmic trading system that takes long or short positions in the Italian MIB (Milano Italia Borsa) index, utilizing futures contracts, or alternatively, direct and inverse Exchange-Traded Funds (ETFs). The investment strategy is guided by the performance of fan tokens associated with Italian first division football teams. The backtesting results of the trading system, spanning from March 2021 to December 2022, have yielded a net profit of €5,885.78, translating to a profit factor of 1.12, outperforming the market benchmark represented by the MIB index. Consequently, it can be inferred that the sentiment-driven trend of fan tokens can effectively serve as a leading indicator of market developments. This research highlights yet another instance of market inefficiencies that have already been identified by behavioral finance.