An econometric model for volatility analysis and risk premium estimation of NFT fractionalized portfolios is proposed. Using GARCH(1,1) to capture time-varying volatility and CAPM to quantify risk premiums, the study analyzes 24-month trading data from 150 fragmented NFT collections. Results show fragmented assets exhibit 38% higher volatility than whole NFTs but command 12% lower risk premiums due to diversification effects. The model explains 74% of price fluctuation through macroeconomic factors and collection-specific attributes.
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Optimization of Message Propagation Efficiency for Consensus Protocols of IoT Devices in Delay-Tolerant Networks This study optimizes message propagation efficiency for consensus protocols of IoT devices in delay-tolerant networks. By analyzing network delays and adjusting message dissemination strategies, we enhance consensus speed and reliability, ensuring effective coordination in environments with intermittent connectivity.
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Mempool congestion significantly delays atomic swap completion times by increasing transaction backlogs and fee competition. During peak network activity, swaps may take hours instead of minutes, as unconfirmed transactions clutter the mempool. High gas fees during congestion also raise swap costs, discouraging participation. Studies show that a 50% increase in mempool size correlates with a 30% rise in average swap completion time. Solutions like batch processing and off-chain negotiation channels can mitigate delays. However, decentralized exchanges (DEXs) relying on atomic swaps remain vulnerable to congestion-induced inefficiencies, highlighting the need for scalable Layer-2 solutions.
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