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- Efficiency of traditional and green cryptocurrencies: A comparative analysisPublication . Dias, Rui; Galvão, Rosa; Filho, Aloísio Machado da Silva; Teixeira, Nuno; Alexandre, Paulo; Gonçalves, SidalinaThe main objective of this research is to evaluate the efficiency, in its weak form, of digital currencies classified as "dirty", such as Bitcoin (BTC) and Ethereum (ETH), and the green ones, namely Lisk (LISK), Metaverse (METAVERSE), Quantum (QTUM), Litecoin (LTC), Augur (REP), Cardano (ADA), Dash (DASH), EOS (EOS), Quantum (QTUM), Litecoin (LTC), Ripple (XRP), Augur (REP), Cardano (ADA), Dash (DASH), EOS (EOS), IOTA (IOTA), Monero (XMR), Neo (NEO), Omisego (OMG), Stellar (XLM) and Zcash (ZEC), for the period from 1 January 2018 to 23 November 2023. The results show that Bitcoin (BTC), Metaverse, Litecoin (LTC) and Cardano (ADA) have persistent behaviour with a long memory, which favours long-term strategies. Long memories indicate that markets are less efficient, where trends tend to continue, making long-term strategies more effective. On the other hand, cryptocurrencies such as Lisk, Quantum, Ethereum (ETH), Ripple (XRP), Augur, Dash, EOS, IOTA, Monero, Neo, Omisego, Stellar and Zcash show antipersistent behaviour, with rapid correction of deviations, suggesting more efficient markets, but with less predictability. This favours short-term strategies such as arbitrage and scalping. The analysis reveals that cryptocurrencies with long memory, such as BTC, LTC and ADA, are more predictable in the long term, while most others, such as ETH and XRP, are more suitable for short-term trading, reflecting structural differences in the market.
- Analysing Comovements Between Dirty and Green Energies: An Econometric ApproachPublication . João, Esperança; Dias, Rui; Galvão, Rosa; Alexandre, Paulo; Teixeira, Nuno; Gonçalves, SidalinaThis study analyses the movement patterns between clean energy indices and oil benchmarks such as Brent and WTI from 7 January 2022 to 8 November 2024, intending to verify whether clean energy indices can serve as effective risk diversification instruments. The research focuses on the Nasdaq Clean Edge Green Energy (CELS), S&P Global Clean Energy (SPGTCLEN), Clean Energy Fuels (CLNE) indices and the Invesco Wilderhill Clean Energy (PBW) ETF. The results show that Brent influences the prices of the CELS, CLNE and PBW indices but is unaffected by SPGTCLEN or WTI. WTI has a broad influence, influencing all the other indices. CELS only affects WTI and CLNE, while SPGTCLEN influences CELS and CLNE without influencing the oil markets. CLNE affects CELS, SPGTCLEN and PBW but not Brent or WTI. PBW influences WTI and CLNE but does not affect the other markets. WTI is a key indicator that affects all the other indices, while Brent is the most independent. This indicates that investors can reduce their exposure to oil risk by investing in clean energy indices such as CELS and CLNE, which have limited influences on each other. In conclusion, this study has contributed to understanding the dynamics of movement between clean energy indices and oil benchmarks over the period analysed, offering relevant implications for risk management and portfolio diversification.
- Are Precious Metals Hedging Assets for Clean Energy Indices?Publication . Amândio, Helena; Dias, Rui; Galvão, Rosa; Alexandre, Paulo; Gonçalves, Sidalina; Leote, FranciscoThis study aims to analyse whether precious metals can be hedged assets concerning green energy indices from 8 January 2019 to 6 December 2024. About precious metals, the futures market was analysed: copper (HGH5) and silver (SIH5), the gold spot market (XAU) was also included to provide robustness, and the green indices are S&P Global Clean Energy (SPGTCLEN), NASDAQ Clean Edge Green Energy (CELS), and the iShares Global Clean Energy ETF (ICLN). The sample was divided into four sub periods: 8 January 2019 to 31 December 2019, referred to as Pre-Covid-19; the second sub-period, referred to as the first Covid-19 Wave, comprises the period from 2 January 2020 to 31 December 2020; the second Covid-19 Wave includes the years from 2 January 2021 to 23 February 2022; Finally, the last sub-period, called Conflict, covers the years from 24 February 2022 to 6 December 2024. The green indices (CELS, ICLN, SPGTCLEN) showed extremely high correlations with each other in all periods, reducing the effectiveness of diversification in the sector. Gold remained a consistent, safe haven asset, with negative or very low correlations with the green indices, especially during global crises. Silver evolved from moderate to negative correlations with the green indices, reinforcing its usefulness as a hedging asset. Copper, initially positively correlated with green indices, has exhibited negative correlations recently, making it a strategic asset in portfolios with green energy assets. It was also found that only copper (HGH5) was contagious during the first wave of COVID-19, which validates the evidence found earlier through unconditional correlations. In conclusion, these results highlight that gold and silver effectively protect against market shocks, while copper can be used as a diversifying asset in green energy portfolios, thus requiring differentiated strategies to maximise diversification benefits.
- Testing the diversifying asset hypothesis between clean energy stock indices and oil pricePublication . Dias, Rui; Galvão, Rosa; Cruz, Sandra; Irfan, Mohammad; Alexandre, Paulo; Gonçalves, Sidalina; Teixeira, Nuno; Palma, Cristina; Almeida, LilianaIn theory, geopolitical risk and political uncertainty can directly affect energy markets. Fluctuations lead to the cost of clean energy sources as they compete with traditional energy. The purpose of this study is to analyse financial integration and test the diversifying asset hypothesis between clean energy indices, specifically the Clean Energy Fuels (CLNE), Nasdaq Clean Edge Green Energy (CELS), S&P Global Clean Energy (SPGTCLEN), TISDALE Clean Energy (TCEC.CN), Wilderhill (ECO) and West Texas Intermediate (WTI) stock indices, over the period from 1 January 2018 to 23 November 2023. Analysing the results reveals a scenario where most of the clean energy indices show cointegration with each other, indicating long-term relationships that reflect common trends in the clean energy sector. However, the relative independence of the WTI suggests that Oil still acts as an important and potentially diversifying external factor for investors focused on sustainable energy. Structural breaks in 2021 and 2022 in several indices point to significant events that have altered market dynamics, possibly including changes in environmental policies, technological innovations and the impacts of the COVID-19 pandemic. The cointegration evidence and structural breaks provide valuable information for building investment portfolios. Investors can consider the WTI to diversify portfolios dominated by clean energy assets, taking advantage of Oil’s relative independence. On the other hand, the high correlation between clean energy indices suggests that, within this sector, diversification options are more limited, requiring careful analysis of the specific characteristics of each index and the macroeconomic forces affecting them.
- Big Data as an emerging paradigm in organisations' management: a bibliometric analysisPublication . Gonçalves, Sidalina; Ventura, José Biléu; Rua, Orlando Lima; Dias, Rui; Galvão, RosaThe Big Data Age defines the present era, and the globalisation of business makes it pressing to derive valuable insights from data so that organisations can make sustained decisions. There is no consensus in the literature on how organisations should guide the vast volume of data in value creation or galvanise performance gains. The study aims to address these gaps by reviewing the literature searching WoS using R. Bibliometrix. 4,019 documents were identified between 2008 and early February 2022 through a current mapping of Big Data in management. The results indicate a strong collaboration network among authors and a notable trend in Big Data, Big Data Analytics, Machine Learning, and Artificial Intelligence. These keywords reveal a concern for the predictive analysis of data and the emergence of new research trends, namely management, performance, decision-making, business and value creation, supporting the thesis that Big Data is an emerging paradigm in organisational management.
- Determinants of auditor choice: evidence from Sharia Commercial Banks in IndonesiaPublication . Filianti, Dian; Dias, Rui; Rusmita, Sylva Alif; Irfan, Mohammad; Putri, Athifa Hafizha; Galvão, RosaThis research aims to determine the impact of corporate governance, firm complexity, foreign ownership, and ownership concentration towards auditor choice for Sharia commercial banks in Indonesia in 2016-2023. Firm size is also accounted for as a control variable. This research was conducted using a quantitative approach using the logit logistic regression analysis method through the Eviews 13 software. The sampling method was carried out using a purposive sampling method, which produced a sample of 9 Sharia commercial banks in Indonesia with a total of 72 observations. This study aims to provide an overview of the factors that Sharia commercial banks in Indonesia consider in choosing their external auditors, namely between Big 4 and non-Big Four auditors, which differ from other companies and industries. The results show that in partial analysis, corporate governance mechanisms and ownership concentration significantly and negatively affect auditor choice. Meanwhile, firm complexity and foreign ownership do not affect auditor choice. Low demands cause the negative influence of ownership concentration due to the private nature of the banks and efforts to achieve efficiency in audit fees while maintaining the same quality standards.
- Can renewable energy be a driving factor for economic stability? an inDepth study of sector expansion and economic dynamicsPublication . Agrawal, Manali; Irfan, Mohammad; Dias, Rui; Galvão, Rosa; Leote, Francisco; Gonçalves, SidalinaIndia has emerged as one of the world's most appealing locations for renewable energy development. It has set lofty renewable energy goals to reach 450 gigawatts (GW) capacity by 2030. These aims indicate India's determination to move to greener and more sustainable energy sources. India has been investing in R&D to promote technological innovation in renewable energy. This includes improvements to solar photovoltaic technology, wind energy, energy storage technologies, and smart grid systems. Innovation is critical for improving efficiency, lowering prices, and increasing the reliability of renewable energy sources. This paper aims to analyse the linkages between economic growth and renewable energy usage in India. For this, the Granger Causality technique is adopted, and it is found that no short-run causality exists among the economic growth and RE installed capacity. However, Industrial Production Granger Causes both GDP and Renewable Energy Capacity. When the stock price data of the last five years of top renewable energy companies was also collected, it was found that all the companies are showing an upward trend. While renewable energy is growing rapidly, especially solar and wind power, it is insufficient to meet the bulk of India's energy demands. Renewables contribute to reducing carbon emissions and diversifying the energy mix, but they still account for a smaller percentage compared to thermal power.
- Relating big data, value creation, performance and decision-making: multiple case studiesPublication . Gonçalves, Sidalina; Ventura, José Biléu; Rua, Orlando Lima; Dias, Rui; Galvão, RosaThis study aimed to understand how big data (BD) contributes to value creation in organisations and provides relevant, integrated, and timely information for the performance measurement/assessment model that supports top-management decision-making. The empirical study employs a qualitative methodology comprising five cases using the multiple-case study method. The data collection instrument was semi-structured interviews, and the MAXQDA software was used to treat and analyse the contents. The results show that BD creates value for organisations with positive effects on performance, namely on results, key indicators and turnover, confirming its contribution with relevant financial and non-financial information. It also highlights its innovative approach since the evidence found can be combined with the balanced scorecard (BSC) to identify the most appropriate and efficient key performance indicators (KPIs) for better organisational performance.
- Complex and multifaceted nature of cryptocurrency markets: a study to understand its time-varying volatility dynamicsPublication . Agrawal, Manali; Dias, Rui; Irfan, Mohammad; Galvão, Rosa; Gonçalves, SidalinaDecentralised Finance (DeFi) provides a new way to perform complex financial transactions by exploiting blockchain's ability to maintain a decentralised ledger of transactions without being constrained by centralised systems or human intermediaries. DeFi provides alternative financial instruments that might lessen portfolio risk, especially given the erratic state of the financial markets today. This study analyses the association between the year of the coin in which it was introduced and the market capitalisation of the respective companies. Furthermore, the study also tries to understand the volatility associated with cryptocurrencies using EGARCH & GJRGARCH models. The results reveal that market capitalisation is not similar for all three stages of the age of cryptocurrency. Also, negative news tends to impact Bitcoin more than positive news, and the volatility is persistent and long-lasting. Ethereum, BNB & Solana see more volatility from absolute past shocks; however, Tether exhibits low but persistent volatility as a stablecoin
- Exploring the relationship between clean energy indices and oil prices: a ten-day window approachPublication . Dias, Rui; Galvão, Rosa; Cruz, Sandra; Irfan, Mohammad; Teixeira, Nuno; Gonçalves, SidalinaThis paper aims to assess the comovements between clean energy indices, namely the Clean Energy Fuels (CLNE), Nasdaq Clean Edge Green Energy (CELS), S&P Global Clean Energy (SPGTCLEN), TISDALE Clean Energy (TCEC.CN), Wilderhill (ECO), West Texas Intermediate (WTI) stock indices, over the period from 1 January 2018 to 23 November 2023. We used 10-day windows to analyse the duration and nature of the shocks. Granger causality tests revealed that 20 of the 30 possible pairs showed significant movements, with the WTI influencing all the clean energy indices, highlighting its global importance. CELS also showed a robust influence on all pairs, while SPGTCLEN had a significant but less far-reaching influence. The CLNE and ECO indices showed limited influences, suggesting the potential for diversification, the TCEC.CN proved to be independent and a determining factor for portfolio diversification. The Impulse Response Functions (IRF) confirmed significant movements between CELS, SPGTCLEN and WTI, reflecting the market's response to policies and adjustments in expectations. Fluctuations in oil prices substantially affect clean energy indices, highlighting the interconnectedness and volatility of these markets. In conclusion, these results indicate that despite the growth of clean energy, the sector is still influenced by fluctuations in the fossil fuel market.