Loading...
11 results
Search Results
Now showing 1 - 10 of 11
- Intraday Volatility Spillovers among European Financial Markets during COVID-19Publication . Aslam, Faheem; Ferreira, Paulo; Khurrum, Muhammad; Mughal, Khurrum
- Cross-correlations between economic policy uncertainty and precious and industrial metals: A multifractal cross-correlation analysisPublication . Aslam, Faheem; Huma , Zil E; Bibi, Rashida; Ferreira, Paulo
- Is Brazilian music getting more predictable? A statistical physics approach for different music genresPublication . Ferreira, Paulo; Quintino, Derick; Wundervald, Bruna; Dionísio, Andreia; Aslam, Faheem; Cantarinha, Ana
- Modeling Dynamic Multifractal Efficiency of US Electricity MarketPublication . Naqi, Hyder Ali; Aslam, Faheem; Ferreira, Paulo
- Network analysis of global stock markets at the beginning of the coronavirus disease (Covid-19) outbreakPublication . Aslam, Faheem; Mohmand, Yasir Tariq; Ferreira, Paulo; Memon, Dr. Bilal Ahmed; Khan, Maaz; Khan, Mrestyal
- The footprints of COVID-19 on Central Eastern European stock markets: an intraday analysisPublication . Aslam, Faheem; Nogueiro, Francisca; Brasil, Marina; Ferreira, Paulo; Mughal, Khurrum; Bashir, Beenish; Latif, Saima
- Investigating efficiency of frontier stock markets using multifractal detrended fluctuation analysisPublication . Aslam, Faheem; Ferreira, Paulo; Mohti, Wahbeeah
- Investigating Long-Range Dependence of Emerging Asian Stock Markets Using Multifractal Detrended Fluctuation AnalysisPublication . Aslam, Faheem; Latif, Saima; Ferreira, Paulo
- Evidence of Intraday Multifractality in European Stock Markets during the Recent Coronavirus (COVID-19) OutbreakPublication . Aslam, Faheem; Mohti, Wahbeeah; Ferreira, Paulo
- THE NEXUS BETWEEN TWITTER-BASED UNCERTAINTY AND CRYPTOCURRENCIES: A MULTIFRACTAL ANALYSISPublication . Aslam, Faheem; Huma, Zil-e-; Bibi, Rashida; Ferreira, PauloWe take the novel Twitter-based economic uncertainty (TEU) to examine if it has crosscorrelation characteristics with four major cryptocurrencies i.e. Bitcoin, Ethereum, Litecoin, and Ripple. To conduct a more thorough analysis, we apply multifractal detrended crosscorrelation analysis (MFDCCA) on seasonal-trend decomposition using Loess (STL) decomposed series as well as without decomposed series on the daily data, ranging from 1 June 2011 to 30 June 2021. The findings of this study indicate that: (i) all pairs of TEU with cryptocurrencies are multifractal and have power-law behavior; (ii) the pairs of Ethereum and Bitcoin with TEU are found to be the most multifractal while Litecoin with TEU has the lowest multifractal characteristics; (iii) all STL decomposed series of cryptocurrency have persistent cross-correlation with TEU with the exception of Ethereum which has anti-persistent crosscorrelation with TEU; (iv) all without decomposed series of cryptocurrencies show significant persistent cross-correlation characteristics with TEU; (v) the highest linkage is found for the pair of Bitcoin with TEU. Moreover, to reveal the dynamic characteristics in the cross-correlation of TEU with cryptocurrencies, the rolling window is employed for MFDCCA. These findings have important managerial and academic implications for policymakers, investors, and market participants.