Analyzing the Co-movement of FinTech market efficiency and oil Resource efficiency: An Input-Output study

This complicated study of two abstracts explores the fintech market's effectiveness. This analysis analyzes Thomson Reuters Datastream daily pricing data for four S&P Kensho Fintech indices. Distributed ledger technology, alternative finance, payment trajectory, and banking democratization are significant indicators under study. Hypotheses about the divergence of estimates from the market efficiency benchmark (Hurst exponent of 0.5) are tested in the research methodology. Financial Time series complexity boosts the robustness of these conclusions. The method consistently reveals market inefficiencies, helping financial time series research. The study evaluates fintech market efficiency using advanced multifractal detrended fluctuation analysis (MF-DFA) to understand financial markets and technology better. Transaction costs, knowledge diffusion, and market efficiency technology developments are also studied. Inefficiency from extreme values and autocorrelation. The research goes beyond fintech to evaluate oil extraction efficiency. Resource allocation, technology, environmental repercussions, and sector interdependencies affect intra- and inter-country dynamics. In conclusion, this integrated study examines the fintech market's efficacy and the oil extraction industry's complex dynamics and larger effects using modern approaches. The findings help practitioners, policymakers, and scholars understand fintech indices and market efficiency in complex financial systems and evolving technology.