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This study aims to investigate the dynamics between exogenous shocks, financial stress and economic performance in the USA from January 1995 to August 2023.

Granger-causality tests and impulse response analyses are used to examine causal relationships and dynamic responses among crude oil prices, real M2 money supply, financial stress and key economic indicators.

This study reveals a significant correlation between elevated financial stress and reduced real output, along with disruptions in the labor market, potentially leading to economic recessionary trends. Failure to address these challenges could perpetuate labor market difficulties, weaken capital accumulation within the loanable funds market and ultimately hinder long-term economic growth prospects in the USA.

This study offers insights for policymakers to mitigate financial stress. Recommendations include enhancing financial surveillance, strengthening regulatory frameworks, promoting economic diversification and implementing countercyclical policies to stabilize the economy and support labor markets. In addition, proactive monitoring of financial stress indicators can serve as early warning signals, aiding in timely interventions and effective risk management strategies.

This research provides a comprehensive analysis of how the financial stress index (FSI) mediates the effects of external shocks on the US economy, addressing a gap in existing literature. The integration of the FSI into the analysis enhances the understanding of the transmission channels through which external shocks influence the economy.

This study explores key factors influencing individuals' intentions to invest in NFTs, focusing on personal innovativeness, reward sensitivity, knowledge, subjective norms, perceived value and perceived risk. The aim is to provide insights into what motivates investors within this emerging market, addressing a gap in the understanding of NFT adoption from an investor perspective.

An online survey collected data from 272 participants in China and Hong Kong. The research employs partial least squares-structural equation modeling (PLS-SEM) to assess the relationships between various individual, social and market factors and NFT investment intentions.

The results suggest that personal innovativeness, reward sensitivity, NFT knowledge, subjective norms and perceived value positively impact NFT investment intentions. Additionally, age and income moderate the effects of subjective norms and perceived value on investment intentions, highlighting demographic influences.

For practitioners, insights into investor motivators can inform strategies to promote NFT investments, such as promoting the high reward potential, enhancing investor knowledge, leveraging social proof and emphasizing NFTs' perceived value. For academics, the findings open pathways for further research into investor psychology and the evolving dynamics of NFT and traditional investment markets.

This study advances NFT literature by identifying determinants of NFT investment behavior, a relatively uncharted area. By incorporating theories from investment behavior and technology adoption, it provides a new framework to understand the psychological and social drivers specific to NFT investments.