Faculty Publications
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Item Asymmetric spillover effects in energy markets(International Review of Economics & Finance, 2024-04) Tiwari, Aviral Kumar; Abakah, Emmanuel Joel Aikins; Doğan, Buhari; Adekoya, Oluwasegun B.; Wohar, MarkThis paper explores the asymmetric relationship between clean and dirty energy markets. The study uses the time-varying and frequency-domain spillover approaches, while accounting for asymmetries. We use natural gas, gasoline, gas oil, heating oil, crude oil, coal, petroleum, kerosene, propane, and diesel to denote dirty energy markets and wind, solar and clean energy markets to denote clean energy markets. We use daily data running from May 18, 2011, to August 12, 2020. According to the results obtained, good news in fluctuations in global energy market indices increases the integration of international energy markets in the long run compared to bad news. Our result show that transmission of good and bad volatilities in global energy market indices are dispersed with different time-varying intensities. Empirical evidence further reveals that good news increases integration of international energy markets in the long run compared to bad news. Additionally, markets transmit more bad volatility on average than good volatility during global events. According to the results of the research, we foresee that portfolio managers and investors may experience difficulties in diversifying opportunities in financial volatility periods in the short term. Overall, our findings reveal asymmetric risk effects in investment opportunities between clean and dirty energy. As a result of this information, investors can diversify their investments in the clean energy sector in the long term by using the asymmetry in good and bad fluctuations.Item A cross-quantile correlation and causality-in-quantile analysis on the relationship between green investments and energy commodities during the COVID-19 pandemic period(Studies in Economics and Finance, 2024) Sharma, Aarzoo; Tiwari, Aviral Kumar; Abakah, Emmanuel Joel Aikins; Owusu, Freeman BrobbeyPurpose This paper aims to examine the cross-quantile correlation and causality-in-quantiles between green investments and energy commodities during the outbreak of COVID-19. To be specific, the authors aim to address the following questions: Is there any distributional predictability among green bonds and energy commodities during COVID-19? Is there exist any directional predictability between green investments and energy commodities during the global pandemic? Can green bonds hedge the risk of energy commodities during a period of the financial crisis. Design/methodology/approach The authors use the nonparametric causality in quantile and cross-quantilogram (CQ) correlation approaches as the estimation techniques to investigate the distributional and directional predictability between green investments and energy commodities respectively using daily spot prices from January 1, 2020, to March 26, 2021. The study uses daily closing price indices S&P Green Bond Index as a representative of the green bond market. In the case of energy commodities, the authors use S&P GSCI Natural Gas Spot, S&P GSCI Biofuel Spot, S&P GSCI Unleaded Gasoline Spot, S&P GSCI Gas Oil Spot, S&P GSCI Brent Crude Spot, S&P GSCI WTI, OPEC Oil Basket Price, Crude Oil Oman, Crude Oil Dubai Cash, S&P GSCI Heating Oil Spot, S&P Global Clean Energy, US Gulf Coast Kerosene and Los Angeles Low Sulfur CARB Diesel Spot. Findings From the CQ correlation results, there exists an overall negative directional predictability between green bonds and natural gas. The authors find that the directional predictability between green bonds and S&P GSCI Biofuel Spot, S&P GSCI Gas Oil Spot, S&P GSCI Brent Crude Spot, S&P GSCI WTI Spot, OPEC Oil Basket Spot, Crude Oil Oman Spot, Crude Oil Dubai Cash Spot, S&P GSCI Heating Oil Spot, US Gulf Coast Kerosene-Type Jet Fuel Spot Price and Los Angeles Low Sulfur CARB Diesel Spot Price is negative during normal market conditions and positive during extreme market conditions. Results from the non-parametric causality in the quantile approach show strong evidence of asymmetry in causality across quantiles and strong variations across markets. Practical implications The quantile time-varying dependence and predictability results documented in this paper can help market participants with different investment targets and horizons adopt better hedging strategies and portfolio diversification to aid optimal policy measures during volatile market conditions. Social implications The outcome of this study will promote awareness regarding the environment and also increase investor’s participation in the green bond market. Further, it allows corporate institutions to fulfill their social commitment through the issuance of green bonds. Originality/value This paper differs from these previous studies in several aspects. First, the authors have included a wide range of energy commodities, comprising three green bond indices and 14 energy commodity indices. Second, the authors have explored the dependency between the two markets, particularly during COVID-19 pandemic. Third, the authors have applied CQ and causality-in-quantile methods on the given data set. Since the market of green and sustainable finance is growing drastically and the world is transmitting toward environment-friendly practices, it is essential and vital to understand the impact of green bonds on other financial markets. In this regard, the study contributes to the literature by documenting an in-depth connectedness between green bonds and crude oil, natural gas, petrol, kerosene, diesel, crude, heating oil, biofuels and other energy commodities.Item Analyzing time-varying tail dependence between leveraged loan and debt markets in the U.S. economy(International Review of Finance, 2024-06) Tiwari, Aviral Kumar; Trabelsi, Nader; Abakah, Emmanuel Joel Aikins; Lee, Chi-ChuanThis study analyzes the time-varying dependence between U.S. leveraged loan and debt markets within a highly linked financial system using a quantile-based time-varying connectedness framework to determine the hedging benefits of leveraged loans for financial investors at various quantiles. Based on daily closing price data from November 28, 2008 to October 3, 2023, the evidence demonstrates considerable (moderate) spillovers across the leveraged loan and debt markets for severe (normal) occurrences, with additional results indicating symmetric interaction. In terms of risk spillover, we also affirm the dominance of short-term fixed-income instruments over leveraged loans and long-term bonds. These findings indicate that no hedging or diversification occurred among the investigated markets.Item Real-world asset tokens and commodities: static and dynamic linkages(China Accounting and Finance Review, 2025-08) Tiwari, Aviral Kumar; Abdullah, Mohammad; Sarker, Provash Kumer; Abakah, Emmanuel Joel AikinsPurpose – This study explores the static and dynamic interconnectedness between real world asset (RWA) tokens and traditional commodities. Additionally, the study examines the role of uncertainty factors in explaining the interconnectedness. Finally, the study examines portfolio diversification opportunities. Design/methodology/approach – A novel R-squared based time-frequency connectedness approach is used to examine interconnectedness using data from March 14, 2018, to June 9, 2023. To compute optimal portfolio weights and hedging ratios for each pair, the DCC-GARCH model is utilized and the best weights and hedge ratios are estimated. Findings – The static connectedness result shows that RWA tokens and commodities demonstrate a relatively lower level of interconnectedness. The dynamic connectedness measures unveil time-varying interconnectedness, particularly heightened during economic events. Moreover, global uncertainty factors are positively associated with connectedness, emphasizing the multifaceted channels through which shock is transmitted. Portfolio analysis underscores potential diversification opportunities between RWAs and commodities, offering insights for informed decision-making in navigating the evolving landscape of blockchain-based assets and traditional commodities. Originality/value – The main novelty of this manuscript is the exploration of RWA tokens, an emerging asset class that has received limited academic attention compared to cryptocurrencies, NFTs and DeFi. Unlike prior studies, this research employs a novel R-Squared-based time-frequency connectedness approach to analyze the static and dynamic linkages betweenRWA and traditional commodities.It also examines global uncertainty factors and incorporates portfolio backtesting, providing insightsfor investorsseeking diversification in tokenized assets.Item Asymmetry in returns and volatility between green financial assets, sustainable investments, clean energy, and international stock markets(Research in International Business and Finance, 2025-01) Doğan, Buhari; Jabeur, Sami Ben; Tiwari, Aviral Kumar; Abakah, Emmanuel Joel AikinsThis paper presents empirical evidence on the asymmetric relationship between green investments and international stock markets. We employ the asymmetric versions of Diebold and Yilmaz (2012) and Barunik and Krehlik (2018) for time-frequency connectedness, analyzing daily returns and volatilities from June 23, 2009, to June 23, 2022. Our study reveals significant time-frequency asymmetries in returns and volatility spillovers between green investments and developed equity markets in the short and long term. Regarding net directional spillovers, the equity markets in the United States, the United Kingdom, Italy, Germany, and France emerge as net transmitters of shocks. In contrast, green investments, notably those in sustainability and the environment, act primarily as net emitters of shocks. China and Japan are the primary recipients of these shocks. Meanwhile, green bonds generally function as net receivers of shocks, with occasional exceptions.Item Analyzing the static and dynamic dependence among green investments, carbon markets, financial markets and commodity markets(International Journal of Managerial Finance, 2025-01-17) Abakah, Emmanuel Joel Aikins; Tiwari, Aviral Kumar; Oliyide, Johnson Ayobami; Appiah, Kingsley OpokuPurpose This paper investigates the static and dynamic directional return spillovers and dependence among green investments, carbon markets, financial markets and commodity markets from January 2013 to September 2020. Design/methodology/approach This study employed both the quantile vector autoregression (QVAR) and time-varying parameter VAR (TVP-VAR) technique to examine the magnitude of static and dynamic directional spillovers and dependence of markets. Findings Results show that the magnitude of connectedness is extremely higher at quantile levels (q = 0.05 and q = 0.95) compared to those in the mean of the conditional distribution. This connotes that connectedness between green bonds and other assets increases with shock size for both negative and positive shocks. This further indicates that return shocks spread at a higher magnitude during extreme market conditions relative to normal periods. Additional analyses show the behavior of return transmission between green bond and other assets is asymmetric. Practical implications The findings of this study offer significant implications for portfolio investors, policymakers, regulatory authorities and investment community in terms of carefully assessing the unique characteristics offered by each markets in terms of return spillovers and dependence and diversifying the portfolios. Originality/value The study, first, uses a relatively new statistical technique, the QVAR advanced by Ando et al. (2018), to capture upper and lower tails’ quantile price connectedness and directional spillover. Therefore, the results possess adequate power against departure from mean-based conditional connectedness. Second, using a portfolio of green investments, carbon markets, financial markets and commodity markets, the uniqueness of this study lies in the examination of the static and dynamic dependence of the markets examined.Item Markov-switching multifractal volatility spillovers among European stock markets during crisis periods(Applied Economics, 2025) Tiwari, Aviral Kumar; Abakah, Emmanuel Joel Aikins; Dwumfour, Richard Adjei; Lee, Chi-ChuanThis research investigates time-varying volatility spillovers and connectedness among European stock markets during the COVID-19 pandemic and the Russia – Ukraine war, two events that destabilized global markets. With data from 20 European stock markets spanning 17 December 2019, to 17 March 2022, we employ the TVP-VAR model and estimate volatility using the Markov-switching multifractal volatility technique. Findings from log-volatility estimates suggest that markets are highly connected, with price movement driven mainly by spillover effects from other markets in the same region. Most emerging markets are net receivers of volatility, with most of Europe’s major markets being net transmitters of shocks. The COVID-19 pandemic appears to have impacted European stock markets more than the Russia – Ukraine war. Shifting to the results obtained based on MSM volatility estimates, we find that markets strongly correlate for both high and low volatility. In the case of a high volatility regime, we document the dominance of Finland, Denmark, and Iceland over major European markets. In contrast, under a low volatility regime, we note the dominance of major markets, including the UK and France, over emerging markets in Europe. The findings reveal the diversification potential of emerging European stock markets.Item Geopolitical risk and real estate stock crash(Finance Research Letters, 2025-06) Abakah, Emmanuel Joel Aikins; Abdullah, Mohammad; Akinsomi, Omokolade; Tiwari, Aviral KumarWe investigate the effect of geopolitical risk (GPR) on real estate stock crashes while accounting for the impact of cash holdings and financial constraints in this relationship. Using a dataset from 28 countries covering the period of 2000 to 2023 from 1805 firms, we document that geopolitical risk increases real estate stock price crash risk. Our result remains consistent using an alternate proxy of geopolitical risk and even after considering endogeneity concerns using 2SLS and Entropy balanced samples. Our result shows the negative impact of GPR is stronger for firms with high cash holdings and high financial constraints.Item Quantile correlation between fintech stocks and crypto-assets(Applied Economics, 2024-11-11) Abakah, Emmanuel Joel Aikins; Tiwari, Aviral Kumar; Karikari,Nana Kwasi; Agbloyora,Elikplimi Komla; Lee, Chi-ChuanThis research explores the dependence, directional predictability and dynamic co-movement between fintech and cryptocurrency markets from July 2016 to March 2021 using a series of quantile-based coherency techniques. The causality-in-quantiles results show a considerable difference between causality-in-mean and in-variance under different market conditions. For cross-quantilogram analysis, we observe minimal directional predictability between cryptocurrencies and fintech both in the short-run and in the long-run under bearish and bullish market states. From wavelet multiple cross-correlation models, we show that cryptocurrencies maximize multiple correlation compared to fintech across all time scales, denoting that cryptocurrencies are most dependent on fintech for all wavelet scales.Item Asymmetric dynamics between geopolitical conflict sentiment and cryptomarkets(Research in International Business and Finance, 2024-04) Abakah, Emmanuel Joel Aikins; Abdullah, Mohammad; Tiwari , Aviral Kumar; Ullah, G M WaliThis study investigates the influence of Russia-Ukraine war and associated economic sanctions sentiments on the returns of cryptocurrencies, NFTs, and DeFi assets. We analyse daily returns of twelve blockchain-based assets by employing quantile-on-quantile regression (QQR) and an asymmetric time-varying parameter vector autoregression (TVP-VAR) connectedness approach. The QQR reveals that the war sentiment has varying effects on the returns of digital assets, with negative (positive) impacts in bullish (bearish) markets. Notably, there is a heterogeneous effect observed in normal market conditions. Results from the TVP-VAR-based asymmetric connectedness approach demonstrate a time-varying influence of war sentiment, particularly heightened post-invasion. The war sentiment emerges as a significant transmitter (receiver) of price shocks in bullish (bearish) market conditions. These findings offer extensive implications for investors and policymakers when modelling market behavior during geopolitical events.