Universitat Rovira i Virgili, Reus, Spain
Multi-period decision making applied to cryptocurrency investment scenario
Romina Torres, Miguel A. Solis, Rodrigo Salas and Aurelio F. Bariviera
In this article, we present a contemporary case of study for dynamic linguistic information aggregation approaches. We show the capabilities of the dynamic decision models as a tool to support decision making in changing environments, in this article we made an application where a cryptocurrency investor needs to choose the best investment alternative. We validate our approach using a cryptocurrency investment scenario where investors need to choose the best investment alternative through time based on several attributes considered relevant. Moreover, experimental results obtained with real data shows good performance in terms of the economic profit (or loss), and although behavior of many cryptocurrencies may change abruptly depending on politics or regulatory contingencies just like stock markets, this method represents a computational approach for obtaining recommendations based on quantitative data. Keywords: Multi-period multi-attribute decision making, Fuzzy information aggregation, Cryptocurrency
Aurelio F. Bariviera holds a PhD in Economics and is associate professor at Universitat Rovira i Virgili (Spain). Previously, Aurelio worked as teaching assistant at National University of La Plata (Argentina) and was student intern at SRI International (Arlington, VA). His research is focused in quantitative finance, econophysics, time series analysis, dynamical systems and data mining. He has published in Economics Letters, Physica A, Physics Letters A, Philosophical Transactions of the Royal Society, among others. He has two highly cited papers indexed in the Web of Science.