Faculty Publications
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Item Tracing the ties that bind: navigating the static and dynamic connectedness between NFTs and equity markets in ASEAN based on QVAR-approach(Financial Innovation, 2025-01-10) Naveed, Muhammad; Ali, Shoaib; Tiwari, Aviral KumarBased on market integration theory, we investigate the static and dynamic connectedness between nonfungible tokens (NFTs) and the Association of Southeast Asian Nations (ASEAN) equity markets using the Quantile Vector Auto Regressive model. We also compute optimal weights and hedge ratios for our variable of interest to establish their diversification and hedging potential. Our analysis infers a moderate level of return transmission at the median quantile, where equity markets evolved as the net recipients of return spillover from the system, while NFTs emerge as key transmitters. In extreme market conditions, transmission between variables is amplified, but the increase is symmetrical across extreme quantiles, suggesting a similar impact. However, the interlinkage among assets is symmetric across conditional quantiles. The dynamic analysis demonstrates that the system integration amplifies during uncertain times (e.g., COVID-19 and the Russia–Ukraine conflict). Our portfolio analysis shows that NFTs provide diversification and hedging in all market conditions. However, the period of turmoil dampened the diversification potential, and hedging became expensive. Our study offers detailed and insightful information about the transmission mechanism and enables the participants of financial markets to diversify and hedge their portfolio.Item Nexus of crude oil and clean energy stock indices: Evidence from time-vector-auto-regression in conjunction with conditional-autoregressive-value-at-risk(Heliyon, 2025-01-15) Trabelsi, Nader; Tiwari, Aviral Kumar; Ghallabi, Fahmi; Khemakhem, ImenThe current study aims to elicit information regarding the tail risk transmission mechanism between crude oil (CO) and selected clean energy (CE) stock indices across time and during certain economic events. A Time-Varying Parameter Vector Auto-Regressive model (TVP-VAR) paired with the conditional autoregressive value-at-risk (CAViaR) approach was used to investigate data from January 1, 2015 to December 29, 2022. Overall, we show that an increased vulnerability to tail risk and deficits might be linked to dynamic spillover over examined markets. We also provide evidence that connectedness rises during significant crisis situations, and the last epidemic has the potential to make a lasting impact on the various marketplaces of concern. According to the return and conditional variance time-series, CE stock indices are the most important source of return shocks to CO. However, the CO is the primary cause of volatility in CE stock indices. During the recent virus pandemic, the most significant volatility shock transmissions from CO to CE stock indices occurred. During the Russia-Ukraine war, volatility shocks to CO were mostly caused by CE stock indices. The results of our study offer concrete consequences and new perspectives to various market players in order to improve the management and understanding of risks.