An integrated analysis for digital financial assets and artificial intelligence-based financial management using AI-based neuro quantum picture fuzzy rough sets and econometric modeling

Abstract The objective of this article is to delve into the digital financial asset (DFA) portfolio price of institutional investors, such as hedge funds. The aim is to make a significant contribution by providing methods (statistical methods and fuzzy logic) for investors to identify and select the best long-term portfolio from the pool of 218 digital financial assets that are available in the Russian market. Importantly, companies listed as digital financial asset operators often offer multiple classes of these assets for trading, and as such, investors are only able to trade floating digital financial assets. By the time we reach the conclusion of the year 2024, it has been estimated that the total volume of the Russian DFA market that is currently in circulation will amount to a staggering 1.54 billion USD. Additionally, it is worth noting that 708 different issues are currently actively circulating in the market, showcasing a rather extensive array of options for potential investors. In December alone, an impressive total of 147 new DFAs were introduced and successfully placed, contributing a notable 0.7 billion USD to the market, which is certainly a remarkable feat. The sustainability of the price premium remains uncertain, a consequence of the digital asset market's inherent volatility and relatively short history. When this volatility is considered, the observed premium lacks statistical significance for the sample period. Therefore, the novelty of this study is the creation of new effective tools for researching the effectiveness of portfolio management for time series, which includes 416 daily observations for the period March 2022–October 2023.