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The purpose of the study is to find out the impact of gold and oil prices on the stock market.

This study uses the data on gold prices, stock exchange and oil prices for the period 1991–2016. This study applied descriptive statistics, augmented Dickey–Fuller test, correlation and autoregressive distributed lag test.

The data analysis results showed that gold and oil prices have a significant impact on the stock market.

Following empirical evidence of this study, the authors recommend that investors should invest in gold because the main reason is that hike in inflation reduces the real value of money, and people seek to invest in alternative investment avenues like gold to preserve the value of their assets and earn additional returns. This suggests that investment in gold can be used as a tool to decline inflation pressure to a sustainable level. This study was restricted to use small sample data owing to the availability of data from 1991 to 2017 and could not use structural break unit root tests with two structural break and structural break cointegration approach, as these tests require high-frequency data set.

This study provides information to the investors who want to get the benefit of diversification by investing in gold, oil and stock market. In the current era, gold prices and oil prices are fluctuating day by day, and investors think that stock returns may or may not be affected by these fluctuations. This study is unique because it focusses on current issues and takes the current data in this research to help investment institutions or portfolio managers.

This study aims to explore empirical evidence of the impact of greenhouse gas (GHG) emissions on stock market volatility.

Using panel data of 35 Organization for Economic Co-operation and Development countries from 1992 to 2018, we conduct both fixed effects panel model and Prais-Winsten model with panel-corrected standard errors.

The authors document that there is a significant positive relationship between GHG emissions and stock market volatility. The results remain robust after controlling for potential endogeneity problems.

This study contributes to the literature in that it provides additional empirical evidence for the financial risk posed by climate change.

This paper aims to study the daily returns and volatility spillover effects in common stock prices between China and four countries in Southeast Asia (Vietnam, Thailand, Singapore and Malaysia).

The analysis uses a vector autoregression with a bivariate GARCH-BEKK model to capture return linkage and volatility transmission spanning the period including the pre- and post-2008 Global Financial Crisis.

The main empirical result is that the volatility of the Chinese market has had a significant impact on the other markets in the data sample. For the stock return, linkage between China and other markets seems to be remarkable during and after the Global Financial Crisis. Notably, the findings also indicate that the stock markets are more substantially integrated into the crisis.

The results have considerable implications for portfolio managers and institutional investors in the evaluation of investment and asset allocation decisions. The market participants should pay more attention to assess the worth of across linkages among the markets and their volatility transmissions. Additionally, international portfolio managers and hedgers may be better able to understand how the volatility linkage between stock markets interrelated overtime; this situation might provide them benefit in forecasting the behavior of this market by capturing the other market information.

This paper would complement the emerging body of existing literature by examining how China stock market impacts on their neighboring countries including Vietnam, Thailand, Singapore and Malaysia. Furthermore, this is the first investigation capturing return linkage and volatility spill over between China market and the four Southeast Asian markets by using bivariate VAR-GARCH-BEKK model. The authors believe that the results of this research’s empirical analysis would amplify the systematic understanding of spillover activities between China stock market and other stock markets.

Exchange rate uncertainty leads to an indecisive environment for imports and exports that would condense international trade, foreign direct investment, trade earnings, trade volumes, economic growth and welfare. This study aims to examine, empirically, the effect of exchange rate uncertainty on bilateral trade performance, focusing on eight SAARC member economies using the popular modified gravity model of trade.

The paper includes eight SAARC members – Afghanistan, Bangladesh, Bhutan, Maldives, Nepal, Pakistan and Sri Lanka panel data set over the period 2005–2018. The authors consider both standardized value (standard deviation) and conditional variance model to determine volatility of exchange rate. Primarily, ordinary least squares, random effects and fixed effects estimation techniques are employed to investigate the impact of exchange rate volatility. Endogeneity and robustness of the findings have been tested using the simultaneity-adjusted model and dynamic panel data two-step system GMM estimation techniques.

Empirical findings endorse the view that exchange rate volatility lowers trade flows in the SAARC regions. However, this adverse effect of exchange rate uncertainty on trade is pretty small. The negative correlation between exchange rate volatility and bilateral trade remains consistent and significant after controlling of simultaneous causality, autocorrelation, year effects, country-pair heterogeneity and endogeneity irrespective of panel data estimation techniques and different measures of volatility.

The present paper is original work.

This paper aims to examine how the volatility of foreign direct investment (FDI) inflows affects the volatility of corporate income tax revenue.

The study has used an unbalanced panel data set of 129 countries over the period 1981–2016 and the two-step system generalized methods of moment approach to perform the empirical analysis.

The main findings are that FDI volatility enhances the volatility of corporate income tax revenue in less advanced economies, but reduces it in relatively advanced countries. The positive corporate income tax revenue volatility effect of FDI inflows is far higher in non-tax haven countries than in tax haven countries. Additionally, FDI volatility exerts a higher positive effect on corporate income tax revenue volatility as countries experience greater dependence on natural resources. Finally, the positive effect of FDI volatility on corporate income tax revenue volatility is further amplified by higher FDI volatility.

One important limitation of the present analysis is the use of aggregate FDI inflows because of the lack of data over a long period on greenfield FDI inflows and cross-border mergers and acquisitions FDI inflows. Therefore, an avenue for future research could be to explore separately the effect of the volatility greenfield FDI inflows and the volatility of cross-border mergers and acquisitions FDI inflows on the volatility of corporate income tax revenue, when long-time series data (covering many countries) would be available.

These outcomes particularly shed light on the role of FDI volatility on the volatility of corporate income tax revenue, particularly in countries that are highly dependent on natural resources. Foreign capital flows, notably FDI flows, play an essential role for countries’ economic development through, inter alia, technology transfer, jobs creation and economic growth. Policymakers should aim to attract FDI, while also reducing their volatility, by designing and implementing policies and measures (such as those in favor of business environment improvement, property rights enforcement and political stability) that would assure foreign investors of the continuous high returns of their investments.

To the best of the author’s knowledge, this is the first time this topic is being addressed empirically in the literature.

This paper investigates the effect of the volatility of resource revenue on the volatility of non-resource revenue.

The empirical analysis has utilized an unbalanced panel data set comprising 54 countries over the period 1980–2015. The two-step system generalized methods of moments (GMM) is the main economic approach used to carry out the empirical analysis.

Results show that resource revenue volatility generates lower non-resource revenue volatility only when the share of resource revenue in total public revenue is lower than 18%. Otherwise, higher resource revenue volatility would result in a rise in non-resource revenue volatility.

In light of the adverse effect of volatility of non-resource revenue on public spending, and hence on economic growth and development prospects, countries whose total public revenue is highly dependent on resource revenue should adopt appropriate policies to ensure the rise in non-resource revenue, as well as the stability of the latter.

Economic diversification in resource-rich countries (particularly in developing countries among them) could contribute to reducing the dependence of economies on natural resources, and hence the dependence of public revenue on resource revenue. Therefore, policies in favour of economic diversification would contribute to stabilizing non-resource revenue, which is essential for financing development needs.

To the best of our knowledge, this topic has not been addressed in the literature.

This study aims to analyze the effect of change in trading volume on the short-term mean reversion of the stock price in the Korean stock market. Through the variance ratio test, this paper finds that the market shows the mean reversion pattern after 2000, but not before. This study also confirms that the mean reversion property is significantly reduced if the effect of change in trading volume is excluded from the return of a stock with a significant contemporaneous correlation between return and change in trading volume in the post-2000 market. The results appear in both the Korea Composite Stock Price Index and Korea Securities Dealers Automated Quotation. This phenomenon stems from the significance of the return response to change in trading volume per se and not the sign of the response. Additionally, the findings imply that the trading volume has a term structure because of the mean reversion of the trading volume and the return also has a partial term structure because of the contemporaneous correlation between return and change in trading volume. This conclusion suggests that considering the short-term impact of change in trading volume enables a more efficient observation of the market and avoidance of asset misallocation.

This paper analyzes the impact of macroeconomic variables such as real exchange rate, exchange-rate volatility, and economic growth of the UK and Norway on Norway’s bilateral trade flow to the UK via maritime and other transport modes. The first two models considered trade volume (import and export) via only maritime transport, while the third and fourth models considered trade volume via modes other than maritime transport. The empirical validity of the Marshall-Lerner condition is tested to see whether a devaluation of the real exchange rate improves the trade balance in the long term. In addition to the long-term relationship among variables, short-term effects are also evaluated. The results show that the real income of Norway and its trading partner (the UK) is the main determinant of bilateral trade flow via maritime and other transport modes. Moreover, the results indicate that in the long run, the Marshall-Lerner condition is satisfied only for bilateral trade via modes other than maritime transport.

This paper focuses on Ṣukūk issuance determinants in Gulf Cooperation Council (GCC) countries. Given the dual characteristic of debt and equity of Ṣukūk as well as their unique benefits of social responsibility, the author questions whether the theories of capital structure, the trade-off and the pecking order are able to well explain the Ṣukūk issuance.

First, the author verifies these theories using capital structure determinants and regresses the Ṣukūk change on these determinants. Second, the author tests the trade-off theory with the target debt model and third, verifies the pecking order theory using the fund flow deficit model.

The empirical results show that capital structure determinants fail to explain both theories. The author confirms that the Ṣukūk change is significatively linked to the deviation from a Ṣukūk target. So, issuing firms balance the marginal costs of Ṣukūk and their benefits of religiosity and social responsibility toward a target debt. The author finds no evidence of the pecking order theory.

This study contributes to corporate finance theory and corporate social responsibility. It verifies if capital structure theories proved in conventional financing can well explain Islamic bonds issuance given their social responsibility benefits.

Managers and investors would pay attention to the social factors explaining Ṣukūk issuance in their finance and investment decisions. They would be enhanced to use this financing tool knowing its social unique benefits. This also should encourage governments to enhance this socially responsible financing. Rating agencies would be motivated to evaluate Ṣukūk and firms would improve the quality and relevance of disclosure to get the best rating.

The author highlights the social factors explaining Ṣukūk issuance and enhances corporate social responsibility (CSR).

The author extends the few literature testing capital structure theories for Islamic bonds and highlights the specific social responsible features of Ṣukūk that would bridge their issuance to capital structure theories. So the author enhances the concept of Islamic CSR. Tying capital structure theories to CSR would also help developing Islamic finance theory as a unique social responsible framework.

This study examines the inter-linkages between Bitcoin prices and CEE stock markets (Hungary, the Czech Republic, Poland, Romania and Croatia).

The dynamic contemporaneous nexus has been analyzed using both the multivariate DECO-GARCH model proposed by Engle and Kelly (2012) and quantile on quantile (QQ) methodology proposed by Sim and Zhou (2015). Our study is implemented using the daily data spanning from 6 September 2012 to 12 August 2019.

First, the findings show that the average return equicorrelation across Bitcoin prices and CEE stock indices are positive, even though it is found to be time-varying over the research period shown. Second, the Bitcoin-CEE stock market association has positive signs for most pairs of quantiles of both variables and represents a rather similar pattern for the cases of Poland, the Czech Republic and Croatia. However, a weaker and primarily negative connectedness is found for Hungary and Romania, respectively. Furthermore, the interconnectedness between the co-movements in the Bitcoin market and stock returns changes significantly across quantiles of both variables within each nation, indicating that the Bitcoin-stock market relationship is dependent on both the cycle of the stock market and the nature of Bitcoin price shocks.

The evidence documented in this study has significant implications for divergent economic agents, including global investors, risk managers and policymakers, who would benefit from a comprehensive knowledge of the Bitcoin-stock market relationship to build efficient risk-hedging models and to conduct appropriate policy reactions to information spillover effects in different time horizons.

This paper is the first study employing both the multivariate DECO-GARCH model and QQ methodology to shed light on the nexus between Bitcoin prices and the stock markets in CEE countries. The DECO model uses more information to compute dynamic correlations between each pair of returns than standard dynamic conditional correlation (DCC) models, declining the estimation noise of the correlations. Besides, QQ approach allows us to capture some nuanced features of the Bitcoin-stock market relationship and explore the interdependence in its entirely. Therefore, the main contribution of this article to the related literature in this field is significant.

本研究旨在探討比特幣的價格與中東歐股市(匈牙利、捷克共和國、波蘭、羅馬尼亞和克羅地亞) 之相互聯繫.

研究使用恩格爾與凱利(2012)(Engle and Kelly (2012)) 提出的多變量DECO-GARCH模型及Sim 與Zhou(2015)(Sim and Zhou ( 2015)) 研製的分位數-分位數方法來分析動態同期的聯繫。我們的研究使用由2012年9月6日至2019年8月12日期間取得的每日數據來進行.

首先、研究結果顯示、跨比特幣價格與中東歐股價指數的平均回報當量關聯是正相關的，即使在研究期間被發現是隨時間而變化的。第二、比特幣與中東歐股市之聯繫在大多數兩變數分位數對而言出現正相關跡象，而且，這聯繫在波蘭、捷克共和國及克羅地亞而言表現一個頗相似的模式。唯就匈牙利而言、這聯繫則較弱、而羅馬尼亞則主要是負聯繫。研究結果亦顯示: 比特幣市場內的聯動與股票回報間之內在關聯會在每個國家內跨兩個變數的分位數而顯著地改變，這顯示比特幣-股市關係是取決於股市的週期和比特幣價格衝擊的本質.

本研究所記載的證據、對不同的經濟行為者而言極具意義 (這包括國際投資者、風險管理經理和政策制定者)，因他們會受惠於對比特幣-股市關係的全面認識，他們可建立有效的風險對沖模型、及在不同時間範圍對資訊溢出效應進行適當的政策反應.

本文為首個研究使用多變量DECO-GARCH模型和分位數-分位數(QQ)方法、來解釋比特幣價格與中東歐國家之股市的關係。這DECO模型使用比標準動態條件關係模型更多資訊，來計算每對回報間之動態關係，這能減少估測雜訊，而且，QQ方法讓我們可以取得比特幣-股市關係的一些細微特徵及全面地探索其相互依賴性。因此，本文的主要貢獻是在這學術領域內有關的文獻上.