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This study examines the Granger causal flow from implied oil volatility to US high-yield and investment-grade corporate bonds. The results show that the Granger causality differs over investment time horizons, with evidence of a more lasting effect for high-yield bonds. The oil price crash of mid-2014 intensifies the causal effect from oil price volatility to the high-yield bond market and its energy segment. Further analyses show that the US default risk and credit spread heterogeneously drive causalities from oil to high-yield and investment-grade bonds. These findings are useful to credit market participants for risk management and the design of appropriate asset allocation strategy. They are also important for policymakers regarding policy and regulatory formulations to manage the effects of volatility transmission.

This paper investigates the interconnectedness among 95 tourism firms in the U.S. over the 2018–2020 period with a focus on the impact of the Covid-19 pandemic. The results using tail risk spillove...

Foaling is a process of giving birth to foal which is prompt and forceful event in equine breeding. Dystocia is declared when 2nd stage of parturition exceeds from 20 min without fetal movements in mare. Dystocia is very challenging situation for both mare and veterinarian. Survivability of mare and foal, and subsequent fertility of mare depends on efficient management. Therefore, the current report described a rare case of wry neck (torticollis or unilateral bent neck) resulted in dystocia, that was efficiently resolved by partial fetotomy and repulsion technique in mare under field conditions. Intensive post operative care was performed to avoid infection and to achieve fertility subsequently.

India has one of the world’s largest transport networks, with the dominant share being road transportation. India’s transport sector consumes oil products for more than 95% of its energy needs and is a significant contributor to environmental deterioration in urban areas. Therefore, we examine the driving factors of transport CO2 emissions in India, incorporating road transport energy, economic growth, industrialization, urbanization, oil prices, and road infrastructure, over the period 1980 to 2015. The findings indicate that economic growth and road sector energy use cause an upsurge in transport emissions. Likewise, industrialization and road infrastructure stimulate transport emissions. Urbanization mitigates transport emissions, while oil prices have no influence on transport emissions. One-way causality is shown from economic growth, urbanization, and road sector energy to transport emissions. Finally, suitable policy implications are proposed to reduce transport CO2 emissions for a sustainable environment.

We uncover the hedging and safe-haven properties of eight cryptocurrencies against down movements in the S&P 500 and its 10 equity sectors. Evidence from the cross-quantilogram approach supports many cryptocurrencies as a potentially valuable digital asset class. However, a significant heterogeneity is reported in many cases. Bitcoin, Ripple and Stellar are safe-havens for all US equity indices, while Litecoin and Monero are safe-havens for the aggerate US equity index and selected sectors. As for Ethereum, Dash and Nem, they are hedges for few equity sectors. Our findings help investors in improving their ability to offset equity losses with new cryptocurrencies.

This paper uses the novel quantile coherency approach to examine the tail dependence network of 49 international stock markets in the frequency domain. We find that geographical proximity and state of market development are important factors in stock markets networks. Both the short- and long-run connectedness significantly increased after the global financial crisis and spillover is higher during bearish market states, highlighting the possibility of contagion effect mainly among developed markets. Frontier and emerging markets are relatively less connected. These findings have implications for international equity market diversification and risk management.

Our work examines the relationship between socially responsible funds and the traditional energy market over daily returns data ranging from December 2015 to April 2019. We apply quantile cross-spectral analysis to measure returns correlation under different market conditions in the short, medium, and long run to measure the connectedness between both markets. Our results highlight that correlation based on different quantile distributions yields different investment opportunities. In the short run, investors can benefit from diversifying assets under extreme market conditions. No significant diversification opportunities are available in the medium- and long-run periods. Our findings provide implications for individual investors making investments under different horizons and dynamic market conditions.

This paper examines the nonlinear impact of oil prices and inflation on residential prices in the US, the UK and Canada using quarterly data from 1975 to 2017. The study uses nonlinear autoregressive distributed lag (NARDL) bounds testing approach that allows possible asymmetric effects in both short- and long-run. Our results highlight that oil prices, interest and inflation rates and income have asymmetric relationship with residential prices in US, UK and Canada; however, the extent and magnitude of this relationship varies. Long run coefficients of Inflation rate highlights significance for residential prices in all three economies i.e. US, UK and Canada. For international oil prices however, the asymmetric effect is more pronounced in US as compared with UK and Canada. In case of US, long-run asymmetric relationship of residential prices with inflation and gross domestic product (GDP) per capita is also witnessed however, interest rate seems to influence residential prices in both UK and Canada. Our paper has implications for the investors in residential housing markets and government authorities regulating housing sectors.

This paper examines the quantile-dependent short- and long-run impact of the FFR, VIX index and crude oil prices on the credit risk of the U.S. banking, financial services and insurance sectors. Using the quantile autoregressive distributed lag model, we find that the federal funds rate and the equity volatility mainly increase the credit risk of the financial sector when the credit risk is on a rising trend. However, oil prices, and to a lesser extent, decrease the credit risk. The short- and long-run impacts of the considered risk factors are time-varying and heterogeneous across the different credit market states.

In this article, we investigate the impact of geopolitical risk (GPR) on international tourism demand in emerging economies. We have found that impact of GPR is not homogeneous for every country in our sample; for example, some countries are affected heavily by GPR and others are mostly immune to GPR shocks. In general, for countries that have attractive tourism destinations, the impact of GPR is minimal, indicating that if international tourists desperately want to go a destination, they do not take GPR seriously. In addition, the tsunami impact of GPR is not the same for all affected countries. For some countries, the GPR shocks have an impact within 2 to 3 months of its ‘first hit’, while for other countries, the impact is felt over longer periods.

We examine the effect of regulatory capital and ownership structure on banks’ liquidity creation in emerging Asian economies. We find a positive association between regulatory capital and bank liquidity creation, which is consistent with the risk-absorption hypothesis. Bank size has a positive relation with liquidity creation, implying that large banks have more capacity to create liquidity as they enjoy more of the safety net provided by lenders of last resort in the event of crisis, the advantage of reputational benefit, and easier access to external market funding. The negative effect of the bank funding structure is that, as the subordinate debt is typically uninsured, higher funding costs lead banks to reduce liquidity creation. The results imply that an increase in interest rates worsens liquidity creation. For ownership structure, the results show the significance of the impact of ownership concentration on liquidity creation. Banking institutions having higher equity and higher concentration ownership leads to improved liquidity creation.

Probiotics have been the core area of study since last few decades due to their immense beneficial effects on human health. They are widely incorporated as a verity of products in food industry. Prebiotics are the commonly used fibers and when used in combination with probiotics are called as synbiotics, thus enhancing the probiotic activity. Several in vitro and in vivo studies have revealed the application of these microbiota management tool for the prevention and cure of diseases. Diarrhea prevention, atopiceczema, dental care, cancer therapy and treatment of bowel syndrome are the various health benefits provided by probiotic activity. These wonderful microorganisms have the enzymatic activity of breakdowning the food macromolecules, secretion of anti rnicrobial substances, anti-carcinogenicability, enhancing immune system, improved ability in producing short-chain fatty acid, anti atherogenicability, allergen regulation, anti-virulence activity, treatment of urinary tract infections and many more. In the light of this remarkable ongoing trend and the scientific evidence obtained on these microbiota, it is the need of hour to do further research on dose and optimal probiotic for specific diseases. This narrative review present the current documentation on enteric disease management stratagies and antivirulence studies focusing on quantum sensing inhibition, anti-toxin effects and anti-invasion effects.

We examine the relationship between financial inclusion and carbon emissions. For this purpose, we develop a composite indicator of financial inclusion based on a broad set of attributes through principal component analysis (PCA) for 26 countries in the Asia region. Our robust panel regression analysis reveals a significant positive long-term impact of financial inclusion on carbon emissions. The pairwise causality test reveals unidirectional long-term causality running from financial inclusion to carbon emissions. The study suggests that policy makers may design policies that integrate accessible financial systems into climate change adaptation strategies in order to neutralize the side effect of financial inclusion deteriorating environmental quality and inclusive sustainable economic growth. JEL ClassificationO16; O44, Q54

This paper investigates the interconnectedness between sovereign credit risk based on the tail event and network dynamics technique. Specifically, we examine the interdependence in upper tails of sovereign credit default swap in the case of fifteen most COVID-19 affected countries. Empirical findings indicate that connectedness among SCDS spreads changed over time and is higher during the COVID19 outbreak. Russia, Brazil, and China are the most credit risk emitter and receiver during the COVID-19 pandemic.

This study investigates the structure of the tail dependence between the United States (US) and Gulf Cooperation Council (GCC) banking sectors for the period February 2010 to July 2017. Conditional value at risk and conditional diversification benefits are calculated. The GCC banking sectors show lower tail dependence with the US banking sector. This is confirmed by the fact that GCC banking sectors receive higher downside risk spillover from the US banking system during downside market movements compared to upside risk spillover effects. Interestingly, an equally weighted portfolio of US and GCC banking stocks can provide relatively higher diversification benefits. These findings have implications for portfolio diversification, asset allocation and hedging strategies.

The corona virus disease being aware commonly as Covid-19 in passing days among common masses is a novel viral illness of the systema respiratorium, causing a sustained pandemic which is in particular characterized by atypical pneumonia with specific symptoms of mild fever, runny nose with secreted fluid similar to flu, hypoxia, myalgia, anosmia, ageusia, shortness of breath, normal or decreased leukocyte count, ground glass opacities, sore throat and cough without phlegm. It is caused by an epidemic referred as SARS CoV-2 with abbreviation of severe acute respiratory syndrome coronavirus-2 nowadays. The procedures to be adopted for the diagnosis of COVID-19 should be based not only on clinical but epidemiological agents also and anyways stand on the link to an assessment and likelihood of the infection. The SARS CoV-2 is diagnosed with different test techniques like serological, molecular and others but most common for it is RT-PCR which is widely used and most reliable one to authenticate the findings of this disease. In the earlier times its detection was too an issue but luckily soon after its threat the scientists and organizations involved themselves and developed strong techniques to get reliable and accurate results with peaceful outcomes. The including such techniques are like immunological assay, amplification technique like RT-PCR (Spin column-and poly amino ester magnetic nanoparticle (pcMNPs) extraction method. Real-time nanopore target sequencing (NTS) and amplification methods) while on the other hands latest in use techniques are Isothermal nucleic acid amplification (as their subcategories include transcription-mediated amplification (TMA), Loop-mediated isothermal amplification (LAMP), rolling circle amplification (RCA) and clustered regularly interspaced short palindromic repeats (CRISP), and TMA assay). The novel techniques developed for this particular purpose are Biosensors, Localized surface plasma resonance (LSPR) sensor, the Field effect transistor (FET) and Cell-based potentiometric biosen.

The studies aimed to evaluate the pregnancy rate (PR) for timed artificial insemination (TAI) after G7G-Ovsynch, modified G7G-Ovsynch (MG7G-Ovsynch) and Ovsynch protocols and to assess the accuracy of using pregnancy-associated glycoproteins (PAGs) and plasma progesterone (P4) in pregnancy diagnosis compared with ultrasonography (US). In study 1, Holstein cows (n = 37) were bred by TAI following the G7G-Ovsynch protocol (n = 19) or MG7G-Ovsynch (n = 18). Pregnancy was evaluated by US at days 31, 59, and 87 after breeding. The PR was not different for the G7G-Ovsynch and MG7G-Ovsynch. Blood and milk samples were collected on day 3 after insemination and then weekly through day 59 post TAI in cows diagnosed as not pregnant on day 31 and through day 87 in pregnant cows. PAGs were measured using ELISA and P4 by radioimmunoassay (RIA). In the second study, Holstein cows (n = 212) were bred by TAI following G7G-Ovsynch protocol (n = 110) or standard Ovsynch (n = 102). Cows were subjected to pregnancy diagnosis on days 30, 60, and 90. A subset (n = 15 in each group) was subjected to blood and milk samples on days 30, 45, 60, 75, and 90 to measure PAGs and P4. In study 2, PR was not significantly different between synchronization protocols on days 30, 60, and 90. Pregnancy loss averaged 15% between day 30 and day 90. The use of PAGs and P4 proved equally effective in diagnosis of pregnancy. Thus, G7G-Ovsynch was deemed the protocol of choice in postpartum cows, and PAGs assayed in milk or plasma could be used to diagnose pregnancy.

This paper examines spillover effects among international tourism growth, economic growth and a group of major macroeconomic and financial variables in the US. The empirical results show significant interactions among tourism growth, economic growth and the selected macro-finance factors, which have notably increased following the intensification of the global financial crisis in the fall of 2008. Furthermore, international tourism growth in the US appears as the main net receiver of spillovers from macroeconomic factors, thus providing evidence contrary to the empirical validity of the tourism-led growth hypothesis for the US. However, real GDP growth is identified as a net transmitter of spillovers to the tourism growth, which supports, at least partly, the economic-driven tourism growth hypothesis for the US. Novel to the literature, global economic policy uncertainty is the most important transmitter of shocks to US tourism growth, suggesting that heightened uncertainty about economic policy may have especially harmful effects on international tourism flows. info:eu-repo/semantics/publishedVersion

International audience; In a first step, we model the multivariate tail dependence structure and spillover effects across energy commodities such as crude oil, natural gas, ethanol, heating oil, coal and gasoline using canonical vine (C-vine) copula and c-vine conditional Value-at-Risk (CoVaR). In the second step, we formulate portfolio strategies based on different performance measures to analyze the risk reduction and diversification potential of carbon assets for energy commodities. We identify greater exposure to losses arising from investments in heating oil and ethanol markets. We also find evidence of carbon asset providing diversification benefits to energy commodity investments. These findings motivate for regulatory adjustments in the trading and emission permits for the energy markets most strongly diversified by carbon assets.

This paper applies a bivariate cross-quantilogram approach to examine the spillover network structure in the stock markets of 58 countries according to bearish, normal and bullish market scenarios. Our aim is to identify the strongest interdependencies, the directionality of the spillover risk effects, and to detect those equity markets with the potential to cause global systemic risk. The results highlight the role of the US and Canadian equity markets as major spillover transmitters, while the stock markets of Romania, Taiwan and Mexico act mainly as spillover receivers. Particularly strong spillovers are observed from the Canadian and US equity markets towards the Irish market, and from the Brazilian equity market towards the Kenyan equivalent. The equity market networks suggest that only the US equity market can trigger systemic risk on a global scale. Implications of the results are discussed.

We examine the asymmetric and extreme tail dependence between five energy markets (crude oil, natural gas, heating oil, gasoline, and coal) and green bonds using a time-varying optimal copula (TVOC) model. The results indicate the existence of multiple tail dependence regimes, implying the unsuitability of applying static or dynamic models to entirely describe the extreme dependence between energy markets and green bonds. There is an extreme negative tail dependence between green bonds and four energy commodities (crude oil, heating oil, gasoline, and coal), whereas an extreme positive tail dependence is shown for green bonds and natural gas. Largely, stressful periods such as the COVID19 outbreak, shape the tail dependence, which is also the case for extreme risk spillovers involving, especially, crude oil. Hedging effectiveness analysis indicates that green bonds can effectively hedge most of the energy commodities. The conditional diversification benefits seem to vary with time, especially for natural gas, and differ across the energy markets. Notably, green bonds provide higher conditional diversification benefits when combined with coal for several portfolio weights.

We examine the dependence structure among the metals and mining companies of the US and Europe. We employ several dependency measures, comprising network dependency and spillover approaches, using daily data from May 14, 2010 to July 10, 2020. We estimate the minimum spanning tree and conduct sub-sample analyses for the European sovereign debt crisis and COVID19 pandemic lockdown periods. Our results show high dependence among US metals and mining stocks and no dependence among such companies based in Poland, the UK or Italy. During European crises, UK and Austrian metals and mining companies are shown to be major risk transmitters, whereas Austrian, US and Finnish companies are major recipients of spillover. We also observe a significant increase in the transmission effect from Austrian, US and Finnish companies during the COVID19 period. This study is the first to show spillover and contagion effects among the metals and mining companies of the US and Europe, and thus provides useful information for market players in this domain.

Purpose This study aims to examine the impact of terrorism on return and systematic risk of Pakistan’s equity industries. Daily data from 1 January 2000 to 31 December 2014 for 12 industries based on the specific types of companies listed on Karachi Stock Exchange are used for the empirical analysis. Design/methodology/approach A multiplicative (additive) term is introduced in the standard capital asset pricing model to examine the change in systematic risk (industry returns) in response to the terrorist activities. The authors use the multiscale beta approach (Yamada, 2005) and the maximal overlap discrete wavelet transform (MODWT) to test the heterogeneous market hypothesis. Findings Terrorism activities increase the systematic risk for most of the industries and the negative impact on returns of banks and the financial industry. It is noted that terrorism positively impacts (increases) the industrial systematic risk mainly in short-run (between two and four days-time horizon). Originality/value The paper examines the impact of terrorism on a broad list of industries’ (banks, basic materials, chemicals, construction, consumer goods, consumer services, financials, industrials, minerals, oil and gas, textile and utilities) risk and return in Pakistan, using the multiscale beta approach (Yamada, 2005) and the MODWT methods.

This study examines the empirical relationship of electricity generation (EGEN) and economic growth (IPI) in Singapore by using the flexible properties of the wavelet approach. This innovative technique allows the decomposition of time-series across time scales. In this study, we used continuous wavelet transform, cross wavelet and wavelet coherence ratios to investigate the relationship between EGEN and IPI by using the monthly data from 1983(1) to 2016(1). Results of autoregressive distributed lag and Johansen Juselius cointegration tests show that there is a significant long-run relationship the mentioned variables in Singapore. Furthermore, results indicate that there is a unidirectional causal relationship running from EGEN to IPI in the long run while a bidirectional causal interplays are depicted between the of EGEN on IPI in medium run. Thus it can be recommended that government needs to increase electricity generation and further providing and nurturing the expansion of electricity supply in country which will ultimately benefits the economic growth.

This paper re-examines the specification of the environmental Kuznets curve (EKC) for the US economy by accounting for the presence of a major renewable energy source and trade openness over the period 1960–2016. Biomass energy consumption and trade openness as well as oil prices are considered as additional determinants of economic growth, and consequentially of CO 2 emissions. The bounds testing approach to cointegration is used to examine the long-run relationship between the variables in the presence of structural breaks. The causal relationship between the variables is investigated by applying the VECM Granger causality test and accommodating structural breaks. The results confirm the presence of cointegration between the variables. Moreover, the relationship between economic growth and CO 2 emissions is not only inverted-U shaped but also N-shaped in the presence of structural breaks and biomass. Biomass energy consumption lowers CO 2 emissions. Exports, imports and trade openness are also environment-friendly. The causality analysis underscores a feedback effect between biomass energy consumption and CO 2 emissions. Economic growth still Granger causes CO 2 emissions in this new setup.

This paper investigates the interaction between energy consumption and oil shocks in the U.S. from 1974 to 2018 using monthly data. Its contributions rely on the double disaggregation of energy consumption and oil shocks in a time-varying context. Oil shocks are disaggregated into oil supply, oil demand and aggregated demand shocks following the method of Kilian (2009). Energy consumption is disaggregated according to the production source in distinguishing between renewable and non-renewable energy consumption (hydropower, geothermal, wood, waste, coal, natural gas and petroleum). The impulse response function results show that renewable energy consumption responds the most to aggregate demand and oil supply shocks while for non-renewable energy consumption, it is oil demand shocks. The dynamic connectedness results show that oil supply and demand shocks spillover the most to hydropower consumption while aggregate demand shocks spillover the less. However, these relationships change over time and recommend the flexibility of energy policies.

Estrus synchronization and suitable resynchronization intervention is crucial part of improved reproductive management in dairy industry. Our objectives were to appraise CIDR-EB based estrus synchronization and used CIDR-Ovsynch based resynch protocol in lactating Holstein cows at two different geographical locations. On location A, 160 postpartum cows were enrolled in standard CIDR-EB protocol. Cows were subjected to timed AI and randomly assigned into two groups: 1) control (n=70), subjected to AI on detected estrus (AIDE) from d18-d30 post TAI. Pregnancy rate was diagnosed on d30, d60 and d90 post TAI, 2) resynch (n=90) received CIDR from d14-d21 post TAI. On day 23, all cows received GnRH shot and open cows received remaining Ovsynch protocol. Blood was collected on d14,d16 and d30 for P4 profile. Cross-sectional area of luteal tissue was measured on d30 in pregnant animals in both groups. In experiment II, both control (n=64) and resynch (n=54) groups were similarly treated as in experiment I, without P4 profile and luteal cross-sectional area measurement. Pregnancy rate(PR) was compared by PROC FREQ of SAS. Effect of treatment on circulatory P4 profile and luteal tissue cross-sectional area were analyzed using GLM procedures (P

Our objectives were to appraise three ovulation synchronization protocols and Pregnancy diagnosis(PD) methods in lactating dairy cows. Cows (n=184;4.2 ± 1.2 lactations and average daily milk yield>28 kg with 3X milkings) were randomly assigned to 1 of 3 timed artificial insemination(TAI) protocols: 1)Ovsynch protocol (n=66), GnRH-PGF(2α)-GnRH; 2)G7G-Ovsynch (n=63) protocol, PGF(2α),GnRH 2 days later followed by Ovsynch; 3)PG7G-Ovsynch(n=55) protocol, PGF(2α) 14d before the start of G7G-Ovsynch protocol.Pregnancy rate(PR) was determined on d30, d60 and d90 post TAI using ultrasonography(US), P4(RIA), milk and Plasma PAGs(ELISA). The PR was compared using chi-square. Milk, plasma PAGs and plasma P4 profiles were analyzed using REG procedures of SAS(P

This paper re-examines the static and time-varying asymmetries in quantile-specific relationship between gold returns and gold mining companies' stock returns. In doing so, we use novel cross-quantilogram approach that is built on quantiles of both distributions and control for the effect of crude oil price changes, overall stock market movements, stock market volatility and economic policy uncertainty. We find that the gold returns negatively predict the gold stock returns around the median quantile. Whereas the gold returns positively depend on the gold mining companies’ stock returns in the low and high quantiles. We therefore, support for an embedded real option in gold for gold mining companies which is time-varying and occurs in very short-run. This finding is useful for devising portfolio allocation and diversification strategies.

We explore the nexus between tourism, exchange rate and economic growth in Sri Lanka over the period 1980–2014. Using the augmented Solow (Q J Econ 70(1):65–94, 1956) framework and the ARDL bounds procedure whilst accounting for structural breaks using Bai and Perron (J Appl Econ 18(1):1–22, 2003) multiple break tests, the short-run and long-run association and impacts are examined. The results confirm the presence of a long-run association between tourism receipts (% of GDP), exchange rate, capital per worker and output per worker. The regression results show a 1% increase in tourism receipts results in a 0.03 and 0.06% increase in output per worker in the short-run and long-run, respectively. A unidirectional causality is noted from tourism to output per worker; from exchange rate to output per worker and capital per worker; and from output to capital, in per worker terms. Finally, we note that although structural breaks periods have negative association with economic growth, they are not statistically significant.

Purpose The assessment of interdependence between stock markets is an important aspect of international portfolio management. The purpose of this paper is to examine and highlight the diversification potential of South Asian stock markets vis-à-vis developed and European stock markets. Design/methodology/approach The developed stocks markets include USA and UK, and South Asian stock markets include India, Pakistan and Sri Lanka while DJ STOXX 600 index is used to represent the European stock markets. Monthly data are used to examine long-run relationship through ARDL bound testing approach and estimates are obtained using DLOS. Short-term dynamics are captured through vector error correction-based Granger causality. Findings South Asian stock markets are closely linked with each other; similarly, developed/European markets are interlinked. US stock market not only impacts European stock markets, it also Granger cause South Asian stock markets. The findings suggest increase in comovement of South Asian stock markets with the global markets after financial crises of 2007-2008. Practical implications The diversification benefits of South Asian stock markets for international investors are still evident due to their low relationship (in both long and short run) with developed/European stock markets. Originality/value Given the emergence of South Asian stock markets, new insight on their relationship with developed stock markets can provide interesting findings for international portfolio diversification. The South Asian equity markets are an important source of investment because of their immense growth and weak correlation with international markets.

This research work is based on the relationship that exists between the capital structure and performance of different sector's firms currently operating in the Pakistan. Capital structure decisions can be considered as the most important financial performance and risk management tools which are available to the companies' management. Capital structure can also play an important role in performance assessment, in performance management and in effective handling of ownership claims. The extensive use and heavy dependence on debt has exposed many companies to potential risk of declined performance and also to the risk of insolvency. This study analyzes the relationship between various capital structure indicators and dependence of financial performance of companies on these indicators using a broad sample covering 202 non-financial firms listed on Karachi Stock Exchange (KSE) over the period of 1999-2012. The sample firms are divided into five sectors i.e. Textile, Chemical, Cement, Food and Fuel & Energy. Financial performance of firms is quantified by Return on Assets (ROE), Return on Equity (ROE), Price-Earnings ratio (PE) and Tobin's Q (TQ). The relationship between financial performance measures and capital structure measures i.e. total debt, short term debt and long term debt is estimated using GLS fixed and random effect model. Sector wise comparison shows that majority of the sectors have similar capital structure. The impact of capital structure on the financial performance is also similar across sectors with few variations. Overall the relationship is found to be negative among capital structure and firm performance measured by ROA, ROE and PE except TQ which is positively related to Long Term Debt to total Assets (LTDA). The result of industry wise comparison contributes significantly to the existing stream of knowledge. The results indicate that lower reliance on the debt financing improves the performance of the firm whereas dependence and exposure of debt financing reduce performance. The research can be useful for the management of companies in different sectors that want to improve their performance.

Highlights • Spillovers, portfolio allocation and diversification potential of bank returns are examined. • Spillover index, tail-event driven network and nonlinear portfolio optimization are applied to bank returns data. • Spillovers among banks from emerging America are noticeably smaller than those from developed America. • The largest emerging market spillover transmitters and receivers are the banks from Brazil. • Portfolio of banks from emerging America offers greater diversification potential and lower portfolio allocation risk., We examine the network spillovers, portfolio allocation characteristics and diversification potential of bank returns from developed and emerging America. We draw our results by applying a directional spillover index, the tail-event driven network (TENET) and nonlinear portfolio optimization methods on bank returns. We find that the spillovers and connectedness among banks from emerging America are noticeably smaller than those among banks from developed America. The largest emerging market spillover transmitters and receivers are the banks from Brazil, followed by the banks from Chile. The largest developed market spillover transmitter is JP Morgan Chase. The connectedness among banks from developed America is dominated by the banks from the USA, relative to those from Canada. The total connectedness of the emerging market banks is more intensified than that of the banks from developed America due to the effect of the COVID-19 pandemic. The portfolio optimization shows that in developed America, the largest banks from the USA are the largest risk contributors to total portfolio risk, whereas the banks from Canada contribute the least risk. In emerging America, the banks from Brazil contribute the most risk to total portfolio risk while the banks from Peru and one bank from Colombia contribute the least risk. The portfolio of banks from emerging America offers greater diversification potential and lower total portfolio allocation risk.

This paper examines the time and frequency dynamics of connectedness between oil price shocks (demand and supply), and energy, electricity, carbon and clean energy markets using the methodology developed by Diebold and Yilmaz (2012) and Barunik and Krehlik (2018). The empirical findings show that there is time-varying connectedness among all variables in the sample. We find increased connectedness during the global financial crisis as well as in the shale oil revolution period. The total connectedness is more significant and higher in the short-term compared to the long-term. Net pairwise directional connectedness become more important during the shale oil revolution among oil supply, oil demand and clean energy index. The findings of the static full sample and sub-samples (GFC and SOR) provide significant evidence of the electricity futures as diversifier and safe-haven asset for oil shocks. These results can have important implications for investors and policymakers with different time horizons.

We examine connectedness among three types of uncertainties, financial, consumer and industrial uncertainties, in EU member states. The monthly series span the period January 2005 to March 2018, which includes the global financial crisis and the European sovereign debt crisis. The time and frequency spillover approaches based on generalized forecast error variance decomposition are used. We propose decomposing the connectedness tables into symmetric and skew-symmetric parts, for a better and more comprehensive interpretation. The results show that spillover among uncertainties is higher during crises. More spillover is observed within a specific type of uncertainty. The pairs of countries that transmit uncertainty to one another are geographically related, i.e. neighbouring countries. Financial uncertainty is a net transmitter to both industrial and consumer uncertainties.

In this paper, we re-examine the safe haven, hedge, and diversification potentials of 21 commodities belonging to various commodity groups for 49 international stock markets belonging to countries in various stages of economic development. Using daily data from 2001 to 2018, we conduct an extensive analysis that considers the tails of the return distributions. Our main results show valuable hedge and safe haven roles for specific commodities, especially precious and industrial metals. Some of the results seem to be both commodity and country specific, suggesting the need to combine each stock market index with its best commodity match to get the highest benefits. Unsurprisingly, gold is indisputably the strongest safe haven asset, especially in many developed stock markets, confirming previous studies. The hedge effectiveness is highest for advanced emerging and a few developed stock markets. Commodities offer the highest conditional diversification benefits in an equally weighted portfolio for the stock markets of New Zealand and Norway, secondary emerging and frontier market groups.

We investigate the impact of energy commodity uncertainties on the systematic risk of twelve industries in the US. The dynamic betas using the dynamic conditional correlation – generalized auto-regressive conditional heterosckedasticity (DCC-GARCH) model, indicate that real estate, financials, and basic materials are the high-risk industries. Notably, the systematic risk of oil and gas sector was significantly affected during the Global Financial Crisis (GFC) and the Shale Oil Revolution (SOR) sub-periods. Our results provide convincing evidence of the positive impact of energy uncertainties on basic material, basic resources, financials, oil and gas, and real estate. On the other hand, we identify the negative impact on consumer goods, consumer services, health care, industrials, and technology industries. These findings have implications for investment and risk management.

This paper aims to analyze the interaction between renewable energy consumption and industrial production for the U.S. over the 1981–2018 period. We contribute to the existing literature by the disaggregation of renewable energy sources (hydropower, geothermal, and biomass), by the consideration of time and frequency through wavelet techniques and the time-varying Granger causality test recently proposed by Shi et al. (2018). Based on monthly data, wavelet results show a positive co-movement between industrial production and biomass energy consumption at low frequencies, meaning in the long term only. The bootstrap rolling-window Granger causality test indicates a bi-directional predictability between renewable energy consumption and industrial production in crisis and turmoil periods only. These results are found to be robust to the inclusion of control variables (non-renewable energy consumption and crude oil prices) and to the selection of the lag length for the corresponding VAR model.

Objectives were to evaluate three timed AI presynch-based synchronization protocols in lactating Holstein-Frisian cattle. Lactating cows (n = 207) were randomly divided into one of the three treatments: 1)PG-PG-Ovsynch (n = 71), cows were subjected to PG(PGF2α;i.m) at 11-d apart. On 11d post 2nd PG shot, standard Ovsynch (GnRH PG–GnRH) was introduced, 2) G7G-Ovsynch(n = 59), PGF2α-2d-GnRH-7d-Ovsynch, 3) Ovsynch-Ovsynch(n = 67), Ovsynch-7d-Ovsynch. Progesterone profile was measured on d30 and d60 post TAI. For monitoring of ovarian status ultrasonography was done at 1st GnRH, PG and 2nd GnRH of the breeding protocol. Pregnancy was diagnosed on d30, 60 and 90 post TAI and pregnancy loss was also on d60 and 90 post TAI. Pregnancy data was analyzed using Chi-square test and plasma P4 profile by ANOVA in SAS. Ovulatory follicle diameter (mean± SD) was 15.02±1.05 in PG-PG-Ovsynch, 15.41±1.28 in G7G-Ovsynch and 15.23±1.23 in Ovsynch-Ovsynch, respectively (P = 0.167). Plasma P4 profile (ng/mL;Mean±SD) on d30 post TAI was 6.46±1.54,7.07±1.19 and in 6.65±1.40 PG-PG-Ovsynch, G7G-Ovsynch and Ovsynch-Ovsynch groups, respectively (P = 0.08). On d60 post TAI, P4 profile was recorded to be 7.35±1.16,8.06±1.27 and 7.81±0.91 in PG-PG-Ovsynch, G7G Ovsynch and Ovsynch Ovsynch, respectively (P = 0.005). Pregnancy rate on day 30 was 50.70(36/71), 58.20(39/67) and 52.50(31/59) in PG-PG-Ovsynch, G7G-Ovsynch and Ovsynch-Ovsynch, respectively (P = 0.88). Similarly,PR on d60 and d90 post TAI was 46.50(33/71):43.70(31/71), 55.20(37/67): 53.70(36/67) and 50.80(30/59):47.50(28/59) in PG-PG-Ovsynch, G7G-Ovsynch and Ovsynch-Ovsynch groups (P = 0.84:0.78), respectively. Pregnancy loss on d60 post TAI was 8.30,5.0 and 3.20% in PG-PG-Ovsynch, G7G-Ovsynch and Ovsynch-Ovsynch, respectively (P = 0.69). Although statistically non-significant (P = 0.73), overall pregnancy loss on d90 post TAI was also numerically higher in PG-PG-Ovsynch(14.0%) protocol as compared to G7G-Ovsynch (8.30%) and Ovsynch-Ovsynch (9.70%). We concluded that G7G-Ovsynch protocol has resulted in increased PR, P4 profile in comparison with PG-PG-Ovsynch and Ovsynch Ovsynch. Similarly, reduced pregnancy loss,ease and economics makes G7G-Ovsynch as a protocol of choice for improved reproductive management in postpartum dairy cows.

This paper aims to analyze the interaction between renewable energy consumption and the industrial production of the USA over the 1981-2015 period. Its contributions are related to the disaggregation of renewable energy sources (hydroelectric, geothermal, and biomass energy from wood, waste, and biofuel), to the consideration of industrial production instead of economic growth and to the impact of time and frequency. Based on monthly data, wavelet results show a positive comovement at low frequencies between industrial production and biomass energies only. The bootstrap rolling causality test shows that only hydroelectric and wood energy consumption Granger cause industrial production. However, this causal relationship is timevarying and renewable energies are particularly important in crisis periods because they help maintaining the energy independence of the country. Further policy implications are analyzed in the paper.

Do gold prices influence gold mining stocks? In this paper, we evaluate the hypothesis that the relationship between the prices of gold and gold mining stocks should be asymmetric due to the embedded real option characteristics associated with gold mining stocks. We use the cross-quatilogram to measure the relationship, we control for the effect of crude oil price changes and overall stock market movements, and examine the relationship in fixed-window rolling subsamples. Results reveal strong support for an asymmetric relationship as we find heterogenous dependence structure across quantiles and lag orders. This result remains robust for the whole sample period, the global financial crisis subperiod, and rolling subsamples.

The study examines cointegration and causal relationship between FDI, terrorism and economic growth in Pakistan using quarterly frequencies for the period 1988–2010. For empirical analysis data is divided into two sub-periods i.e. pre 9/11 (1988–2001) and post 9/11 (2002–2010) periods. The results show that long run cointegration holds between FDI, terrorism and economic growth. Granger causality results indicate that there is bidirectional short and long run causality between economic growth and FDI for both sub-samples. These findings are supported by variance decomposition and impulse response analysis. The findings suggest applicability of modernization theory to explain FDI and economic growth relationship. The results also reveal that terrorism has a deteriorating impact on FDI.

Efficient use of resources depends on better allocation through financial systems. Development of financial systems can be measured through the performance of banks, financial markets and insurance companies. This paper identifies several key attributes to measure the level of financial development in Europe using data from 1990 to 2011. First, an index is constructed by employing the method of Principal Component Analysis to measure the strength of financial systems in European countries. Second, based on relative raking a comparison is made for better interpretation of results in European countries. The top five countries include Switzerland, United Kingdom, Netherlands, Spain and Germany. The results of this study can be helpful to assess the relative strength of European economies and frame future policies to promote efficiency of financial systems.

In the literature, there is a clear gap between the number of studies about the nature of leadership practices and studies reporting about the impact of leadership training programs. The aim of the empirical study reported in this article was to raise academic leaders� awareness in view of adopting transformational leadership behavior. Leaders from a public university were involved in a training intervention program. Content analysis of interviews data collected before and after the training helped to check the impact of the training program. Compared to the �before� training situation, we find clear differences in the awareness level of leaders reflecting an impact of the training intervention program related to TL-behaviors. Next to limitations of the study, the article focuses on the design of future research.