Browsing by Author "Tiwari, A.K."

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Analyzing time-varying tail dependence between leveraged loan and debt markets in the U.S. economy
(International Review of Finance, 2023) Tiwari, A.K.; Abakah, E.J.A.; Trabelsi, N.; Lee, C.
This 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 quarters. Based on daily closing price data from November From October 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.
Connectedness and directional spillovers in energy sectors: international evidence
(Applied Economics, 2021) Tiwari, A.K.; Dwumfour, R.A.; Abakah, E.J.A.; Mefteh-Wali, S.
This paper provides a comparative analysis of how the energy-sector stocks of 20 regional blocs (Americas, Australasia, BRIC, Southeast Asia, Scandinavia, Southern Europe, Far East, Europe, European Union, Emerging Europe, Asia, G7, G12, Economic and Monetary Union (EMU), CCARBNS (Latin America, North America, PIIGS, Asia-Pacific and NORCS) are connected from 5 July 1994 to 21, 2020. It uses various techniques: Diebold and Yilmaz (2014) (DY 2014, hereafter) spillover indices, TVP-VAR, and LASSO-VAR. Our main results are as follows: First, the DY approach results show that the biggest net contributor of volatility is the CCARBNS region. followed by the G12 and G7 regions, while the biggest receiver of volatility is Southeast Asia region. Second, the TVP-VAR and LASSO-VAR results reveal that Scandinavia, Far East, and America’s regions are net receivers of energy shocks, with net transmitters being CCARBNS, G7, G12 and Emerging European regions. Third, during the 2007–2008 financial crisis and recent COVID-Since the COVID-19 outbreak, energy stock market spillovers have reached unprecedented high levels. Fourth, world policy uncertainty greatly influenced the magnitude of volatility spillovers across regional energy stock markets.
Dynamic spillover effects among green bond, renewable energy stocks and carbon markets during COVID-19 pandemic: Implications for hedging and investments strategies
(Global Finance Journal, 2021) Tiwari, A.K.; Dwumfour, R.A.; Abakah, E.J.A.; Gabauer, D.
This study has been inspired by the emergence of socially responsible investment practices in mainstream investment activity as it examines the transmission of return patterns between green bonds, carbon prices, and renewable energy stocks, using daily data spanning from 4th January 2015 to September 22, 2020. In this study, our dataset comprises the price indices of S&P Green Bond, Solactive Global Solar, Solactive Global Wind, S&P Global Clean Energy and Carbon. We employ the TVP-VAR approach to investigate return spillovers and connectedness, and various portfolio techniques, including minimum variance portfolio, minimum correlation portfolio, and the recently developed minimum connectedness portfolio, to test portfolio performance. Additionally, a LASSO dynamic connectedness model is used for robustness purposes. The empirical results from the TVP-VAR indicate that the dynamic total connectedness across the assets is heterogeneous over time and economic event-dependent. Moreover, our findings suggest that clean energy dominates all other markets and is seen to be the main net transmitter of shocks in the entire network, with Green Bonds and Solactive Global Wind emerging to be the major recipients of shocks in the system. Based on the hedging effectiveness, we show that bivariate and multivariate portfolios significantly reduce the risk of investing in a single asset, except for Green Bonds. Finally, the minimum connectedness portfolio reaches the highest Sharpe ratio, implying that information concerning the return transmission process is helpful for portfolio creation. The same pattern has been observed during the COVID-19 pandemic period.
The effect of global volatility, uncertainty and geopolitical risk factors on international tourist arrivals in Asia
(International Journal of Tourism Research, 2022) Dogan, B.; Abakah, E.J.A.; Ghosh, S.; Tiwari, A.K.
The major tourist destinations in the Asian region are promoting and maintaining a conducive tourism environment. The susceptibility of the major tourist destinations in Asia, the uncertainties may encumber the arrival of international tourists. However, to the best of our understanding, the research in this area is scant. Further though the tourism-uncertainty nexus has been widely explored in the literature, the deliberations in a time-varying and frequency-domain framework continue to be ignored. Thus, building upon the earlier deficiencies this study investigates in a time and scale-varying framework the tourism uncertainty/risk nexus for Singapore and Malaysia is one of the two major tourist destinations in the Asian region. This article endeavors to investigate the role of world policy uncertainty, US Monetary Policy Uncertainty, geopolitical risk, Global Financial Stress Index and market volatility on international tourist arrivals in Malaysia and Singapore. To the best of our understanding, this study is the foremost to scrutinize the interrelatedness between these variables in a multivariate wavelet causality framework, from January 2000 to April 2020. Our results show that global uncertainties manifested through different macro-based indicators affect international tourism demand for the destination countries. During the subprime crisis, Euro-crisis and the pandemics significant coherencies are perceivable. The major empirical findings of the impact of uncertainty indicators and geopolitical risk on international tourist arrivals over the recent period have important implications for policy makers and practitioners.
The effects of public sentiments and feelings on stock market behavior: Evidence from Australia
(Journal of Economic Behavior and Organization, 2021) Tiwari, A.K.; Karikari, N.K.; Abakah, E.J.A.; et al.
This paper investigates the empirical evidence of the effects of public sentiments on industry stock returns and volatility dynamics in Australia based on the states of the market that relates to the conditional quantiles of public sentiments and sectoral stocks, using the robust nonparametric causality-in-quantile test. We adopt the monthly overall consumer sentiments index and four of its components, including sentiments for rural Australia and the age groups 18–24, 25–44, and 45 and above. Our nine industry stocks include Health Care, Consumer Discretionary, Consumer Staples, utilities, financials, and real Estate, Industrials, Basic Materials and Energy, with data spanning from October 1974 to October 2020. The results from the nonlinear causality test show a directional and bidirectional causality between measures of consumer sentiments and returns of industry stocks. Interestingly, we note that the sentiments of individuals aged 45 and above cause the returns of all nine sectors. Next, we explore the predictive power of sentiments on industry stock returns using the nonparametric causality-in-quantile test. We find that the predictability between sentiments and industry stock returns is high in the normal market state but drops when consumers’ perceptions enter into the extreme bearish and bullish states. Additionally, the findings show a risk (volatility) transfer from sentiments to the industry's stock returns in some cases under different market conditions. We offer some implications based on our findings for the stakeholders and market participants who develop their strategies depending on market conditions and sentiments
Extreme Connectedness between Green Bonds, Government Bonds, Corporate Bonds and Other Asset Classes: Insights for Portfolio Investors
(Journal of Risk and Financial Management, 2022) Abakah, E.J.A.; Tiwari, A.K.; Sharma, A.; Mwamtambulo, D.J.
This paper aims to examine the connectedness between green and conventional assets. particularly during a period of economic downturn. Specifically, we examine quantile-based time-varying connectedness between the green bond market and other financial assets using quantile vector autoregression (QVAR) from 9, 2018 to 10, 2021. We use daily prices of S&P U.S. Treasury Bond Index, S&P US Aggregate Bond Index, S&P US Treasury Bond Current 10Y Index, S&P 500 Bond Index, S&P 500 Financials index, S&P 500 Energy Bond Index and S&P 500, giving a total of 784 observations, and using Composite Index as a representative of conventional assets classes and S&P Green Bond Index to denote the green bond market. The results show the connectedness between green bonds and the conventional asset classes intensified during the outbreak of the Coronavirus pandemic (COVID-19) as investors shifted their investment towards fixed income assets due to the plunge in the prices of stocks and commodities. The results also shows that green bonds are strongly connected with treasury bonds, aggregate bonds and bond index, as they share similarities with respect to issuance, risk and governance. Connectedness is weak in the case of composite index and energy bond index, as their prices do not have substantial influence on the green bond market. The study highlights the hedging and diversification benefits of green bonds. We have several implications for portfolio managers, policymakers, and researchers.
Integration between emerging market equity and global markets; is it fundamental or noisy? Evidence from wavelet denoised volatility spillover analysis in time and frequency domain
(Applied Economics, 2022) Jena, S.K.; Abakah, E.J.A.; Tiwari, A.K.; Roubaud, D.
The study investigates the integration between the five largest emerging stock markets, Morgan Stanley Capital Emerging Market Index, and global financial markets like the US S&P 500, Brent Crude Oil and Dollar Index based on wavelet denoised volatility spillover in time and frequency domain using forecasted error variance decomposition framework. It is found that the impact of noise on connectedness is more pronounced in the short run and declines in the longer term. Further, long-term connectedness which is much higher than that of short-term connectedness confirms the existence of fundamental (noisy) concernedness in the long (short) term. The impact of noise varies by time and frequency. The policy implications are discussed.
The outbreak of COVID-19 and stock market liquidity: Evidence from emerging and developed equity markets
(North American Journal of Economics and Finance, 2022) Tiwari, A.K.; Abakah, E.J.A.; Karikari, N.K.; Gil-Alana, L.A.
The outbreak of the novel corona virus has heightened concerns surrounding the adverse financial effects of the outbreak on stock market liquidity and economic policies. This paper contributes to the emerging strand of studies examining the adverse effects of the virus on varied aspect of global markets. The paper examines the causality and co-movements between COVID-19 and the aggregate stock market liquidity of China, Australia and the G7 countries (Canada, France, Italy, Japan, Germany, the UK and the US), using daily three liquidity proxies (Amihud, Spread and Traded Value) over the period December 2019 to July 2020. Our empirical analysis encompasses wavelet coherence and phase- differences, as well as a linear Granger causality test. Linear causality test results suggest that a causal relationship exists between the number of cases of COVID 19 infections and stock market liquidity. To quantitatively examine the degree of causality between COVID-19 outbreak and stock market liquidity, we employ the continuous wavelet coherence approach, with results revealing the unprecedented impact of COVID-19 on stock market liquidity during the low frequency bands for countries that were hard hit with the COVID-19 outbreak, i.e., Italy, Germany, France, the UK and the US. Further, evidence shows that there is a heterogeneous lead-lag nexus across scales for the entire period of the study
Quantile risk spillovers between energy and agricultural commodity markets: Evidence from pre and during COVID-19 outbreak
(Energy Economics, 2022) Tiwari, A.K.; Abakah, E.J.A.; Adewuyi, A.O.; Lee, C.
The spillover effect is a significant factor impacting the volatility of commodity prices. Unlike earlier studies, this research uses the rolling window-based Quantile VAR (QVAR) model to describe conditional volatility spillover between energy, biofuel and agricultural commodity markets. Since the magnitude of connectedness and spillover effects may switch between bearish and bullish market states over time, a QVAR model is a relatively realistic and appropriate approach to capture connectedness as compared to the mean-based approaches of Diebold and Yilmaz (DY; 2009, 2012, & 2014), which are mostly used in the literature. To this end, we employ volatility estimates by using the realized variance advanced by Parkinson (1980). Specifically, we investigate the time-varying volatility spillovers and connectedness among agricultural markets (wheat, corn, sugar, soyabean, coffee, and cotton), energy markets (gasoline, crude oil, and natural gas) and biofuel (ethanol) markets from January 12, 2012, to May 10, 2021. By comparing our empirical analysis with results from the DY spillover model, we establish that connectedness is stronger in the left and right quantiles than those in the mean and median of the conditional distribution, emphasizing the importance of systematic risk spillovers during extreme market movements. Furthermore, results find that volatility spillovers and connectedness in the right tail is higher than in the left tail. In particular, we document significant volatility spillovers from agricultural markets to energy markets during extreme markets conditions and observe the dominance of agricultural markets over energy markets. To ascertain the impact of COVID-19 on the volatility of markets examined, we divide our sample into sub-samples and observe significant variation in the level of volatility spillovers and connectedness across the markets before and during the outbreak of COVID-19. Finally, some useful implications are summarized for investors’ portfolios and risk avoidance.
Quantile time–frequency price connectedness between green bond, green equity, sustainable investments and clean energy markets
(Journal of Cleaner Production, 2022) Chatziantoniou, I.; Abakah, E.J.A.; Gabauer, D.; Tiwari, A.K.
In this study, we propose a novel quantile frequency connectedness approach that enables the investigation of propagation mechanisms by virtue of quantile and frequency. This approach allows for the analysis of connectedness measures considering either different frequencies for a given quantile or different quantiles for a given frequency. We investigate dynamic integration and return transmission among a set of four well-established environmental financial indices, namely the S&P Green Bond Index, MSCI Global Environment, Dow Jones Sustainability Index World and S&P Global Clean Energy over the period from November 28th, 2008 to January 12th, 2022. S&P Green Bond Index and S&P Global Clean Energy appear to be both short-term and long-term net receivers of shocks, while MSCI Global Environment and Dow Jones Sustainability Index The world is both a short-term and long-term transmitters of shocks. We also find that total connectedness indices (TCIs) are heterogeneous over time and economic event-dependent. Furthermore, while the time-domain TCI is rather symmetric across quantiles; this is not the case for either the short-run or the long-run TCI.
Tail risk dependence, co-movement and predictability between green bond and green stocks
(Applied Economics, 2022) Tiwari, A.K.; Abakah, E.J.A.; Yaya, O.S.; Appiah, K.O.
This paper examines the coherence of extreme returns between green bonds and a unique set of green stocks. We use the novel quantile cross-spectral coherence methodology of quantile spectral coherency model, cross-quantilogram correlation approach, windowed time-lagged cross-correlation, and windowed scalogram difference models as estimation techniques. The study period spans from 28 November 2008 to 23 September 2020. Our measure of green stocks comprises the constituents of the MSCI Global Environment Price Index: Alternative Energy, Green Building, Pollution Prevention or Clean Technology while our green bond market is proxied by S&P Green Bond Index. We find the dependency between Green Bonds and green stocks to be weak, and this is high during market downturn periods in the short- to medium-term dynamics. This suggests that Green Bonds do act as a hedge, diversifier, or safe-haven instrument for environment portfolio in the short-term, medium-term and long-term dynamics during bearish market conditions. We conclude that green bonds and green stocks are two distinct asset classes with a distinct risk-return profile despite their common climate-friendly nature.
Time-varying dependence dynamics between international commodity prices and Australian industry stock returns: a Perspective for portfolio diversification
(Energy Economics, 2022) Tiwari, A.K.; Abakah, E.J.A.; Karikari, N.K.; Hammoudeh, S.
This paper investigates the time-varying dependency dynamics between the international commodity prices of Brent crude oil, natural gas, cocoa, and Australia's sectoral stock returns, using daily prices ranging from 1st December 2011 to April 23, 2020. The considered sector stocks include Technology, Telecom, Real Estate, Energy, Basic Materials, Utilities, Industrials, Financials and Health Care. We employ the time-varying Markov switching copulas to investigate the dynamic dependence between those international commodity prices and the Australian industry stocks returns, as well as using various portfolio techniques, including the minimum variance portfolio, the minimum correlation portfolio and the recently developed minimum connectedness portfolio to test portfolio performance. We establish that the dependence between commodities and sectoral stock returns is Markov switching and time-varying. Our results further show that Brent crude oil is a good hedge for the financial sector, natural gas is a good hedge for all sectors except real estate, and cocoa co-crashes with the technology, industrials and real estate sectoral returns. Based on the hedging effectiveness of the competing portfolios, we show that bivariate and multivariate portfolios significantly reduce the risk of investing in a single asset. In particular, the results indicate a significant role for commodities, with weights ranging from approximately 25% to 50%, depending on the portfolio construction of choice. Australian stocks typically have the lowest portfolio weights under all competing portfolios, thus confirming their hedging role to a commodity investment portfolio. Our analysis contributes unique evidence to the literature on the role of commodity assets as a complement to mainstream investment.