Which market integration measure?

This paper compares the dynamics of the financial integration process as described by different empirical approaches. To this end, a wide range of measures accounting for several dimensions of integration is employed. In addition, we evaluate the performance of each measure by relying on an established international finance result, i.e., increasing financial integration leads to declining international portfolio diversification benefits. Using monthly equity market data for three different country groups (i.e., developed markets, emerging markets, developed plus emerging markets) and a dynamic indicator of international portfolio diversification benefits, we find that (i) all measures give rise to a very similar long-run integration pattern; (ii) the standard correlation explains variations in diversification benefits as well or better than more sophisticated measures. These findings are robust to a battery of robustness checks.     

Can energy predict the regional prices of carbon emission allowances in China?

The carbon emission trading is an important market-oriented tool in the process of China's carbon neutrality, which makes companies face tremendous pressure to reduce emissions while having strong energy demands. In order to evaluate whether energy prices can be robust predictors of the prices of emission allowances, this study perform extreme bounds analysis (EBA) in four representative markets. The empirical results reveal that energy prices can indeed predict the prices of emission allowances, but the robustly predictive capabilities of different energy prices vary with regions. Among them, thermal coal is the robustly positive predictor for Guangdong, Hubei and Shanghai market; natural gas is the robustly negative predictor for all the four chosen regions; and crude oil can only positively predict Hubei market with robustness. Meanwhile, the horizons that predictions from energy to emission allowance can be performed as well as the predictive coefficients also vary with energy types and regions. And some trading implications are also provided alongside.     

Initial and Long-Run IPO Returns in Central and Eastern Europe

ABSTRACT

This article provides original evidence on IPO underpricing and long-run underperformance in Central and Eastern Europe (CEE) and compares results to the European Union’s developed capital markets from 2000 to 2009. Using both index-adjusted and CAPM-adjusted returns, we find significant underpricing that is significantly higher than underpricing of comparable IPOs in the European Union’s developed capital markets. We show that the CEE’s initial IPO returns also exhibit significantly higher volatility. In line with the asymmetric information theory, we indicate that smaller IPOs in the CEE region have greater underpricing than the larger IPOs. Contrary to the literature, we unambiguously confirm long-run underperformance toward the benchmarks. In some model specifications, we also find that IPO long-run underperformance in the CEE region is less present than in the European Union’s developed capital markets.     

Integration of emerging stock markets with global stock markets

Financial integration for emerging economies should be seen as a long-term objective. In this paper, we examine stock market integration among five selected emerging stock markets (Brazil, China, Mexico, Russia and Turkey) and developed markets of the US, UK and Germany. The bounds testing approach to cointegration and error-correction modeling are used on monthly data from January 2001 to December 2014 to determine the short-run and long-run relationship between emerging stock market returns and the returns of the developed stock markets. The results show evidence of the existence of short-run integration among stock markets in emerging countries and the developed markets. However, the long-run coefficients for stock market returns in all emerging countries show a significant relationship only with Germany stock market return. The empirical findings in this study have important implications for academicians, international investors, and policymakers in emerging markets.     

Conditional VaR using EVT - Towards a planned margin scheme

This paper constructs a robust Value-at-Risk (VaR) measure for the Indian stock markets by combining two well-known facts about equity return time series — dynamic volatility resulting in the well-recognized phenomenon of volatility clustering, and non-normality giving rise to fat tails of the return distribution. While the phenomenon of volatility dynamics has been extensively studied using GARCH model and its many relatives, the application of Extreme Value Theory (EVT) is relatively recent in tracking extreme losses in the study of risk measurement. There are recent applications of Extreme Value Theory to estimate the unexpected losses due to extreme events and hence modify the current methodology of VaR. Extreme value theory (EVT) has been used to analyze financial data showing clear non-normal behavior. We combine the two methodologies to come up with a robust model with much enhanced predictive abilities. A robust model would obviate the need for imposing special ad hoc margins by the regulator in times of extreme volatility. A rule based margin system would increase efficiency of the price discovery process and also the market integrity with the regulator no longer seen as managing volatility.     

Equity market integration in emerging Balkan markets

This paper examines long-run relationships among five Balkan emerging stock markets (Turkey, Romania, Bulgaria, Croatia, Serbia), the United States and three developed European markets (UK, Germany, Greece), during the period 2000-2009. Conventional, regime-switching cointegration tests and Monte Carlo simulation provide evidence in favour of a long-run cointegrating relationship between the Balkan emerging markets within the region and globally. Moreover, we apply the Asymmetric Generalized Dynamic Conditional Correlation (AG-DCC) multivariate GARCH model of Cappiello et al. (2006), in order to capture the impact of the 2007-2009 financial crisis on the time-varying correlation dynamics among the developed and the Balkan stock markets. Results show that stock market dependence is heightened, supporting the herding behaviour during the 2008 stock market crash period. Our findings have important implications for international portfolio diversification and the effectiveness of domestic policies, as these emerging markets are exposed to external shocks.     

Emerging markets and heavy tails

Emerging countries are held to be subject to more frequent and more pronounced external and internal shocks than their developed counter-parts. This suggests that key variables pertaining to their markets, including their exchange rates, will be marked by greater likelihood of extreme observations and large fluctuations. We focus on the hypothesis that compared to developed country exchange rates, emerging country exchange rates will be more pronouncedly heavy-tailed. We find support for the hypothesis using recently proposed robust tail index estimation methods which, in particular, perform well under heavy-tailed dependent GARCH processes that are often used for modeling exchange rates. According to the estimation results reported in the paper, variances may be infinite for several emerging country exchange rates. Tail index values ζ = p ∈ (2.6, 2.8) appear to be at the dividing boundary between the two sets of countries: while the moments of order p ∈ (2.6, 2.8) are finite for most of the developed country exchange rates, they may be (or are) infinite for most of the emerging country exchange rates. We also study the impact of the on-going financial and economic crisis, and find that heavy-tailedness properties of most exchange rates did not change significantly with the onset of the crisis. At the same time, some foreign exchange markets have experienced structural changes in their heavy-tailedness properties during the crisis.     

The Dynamic Extreme Co-Movement between Chinese Stock Market and Global Stock Markets

ABSTRACT

We use time-varying Symmetrized Joe-Clayton Copula model to study the extreme co-movement (boom or crash together) between the Chinese stock market and major stock markets in the world from 2007 to 2017, including developed markets and stock markets on “Belt and Road Initiative” (hereafter B.R.I.). We find that the extreme co-movement probability between Chinese market and “Belt and Road Initiative” markets is higher than developed markets at both tails. Then we study important “real” and “non-fundamental” factors affecting the excess co-movement probability, including bilateral trade openness, financial integration, and economic policy uncertainty. The results of panel regression analysis show that: the bilateral financial integration has significant effects over the lower tail dependence between Chinese and developed markets, but does not affect the extreme co-movement between Chinese and B.R.I. markets. And the bilateral trade openness is an important factor for the extreme co-movement at both tail between Chinese and global markets. The economic policy uncertainty index, especially China’s economic policy uncertainty, plays a key role in the extreme co-movement between Chinese and developed markets at both tails. However, it has sizable effects only at the upper tail co-movement between Chinese and B.R.I. markets.     

Historical Patterns of Inequality and Productivity around Financial Crises

To understand the determinants of financial crises, previous research focused on developments closely related to financial markets. In contrast, this paper considers changes originating in the real economy as drivers of financial instability. To this end, I assemble a novel data set of long-run measures of income inequality, productivity, and other macrofinancial indicators for advanced economies. I find that rising top income inequality and low productivity growth are robust predictors of crises, and their slow-moving trend components largely explain these relations. Moreover, recessions that are preceded by such developments are deeper than recessions without such ex ante trends.     

Multinationality and the value of green innovation

When do multinational corporations (MNCs) derive the most from internalizing the transfer of proprietary technological knowhow? We revisit this question, which lies at the core of theories on multinationality and performance, from the perspective of corporate strategy involving a mix of green versus nongreen innovation effort and foreign operations focusing on countries with high versus low environmental standards. We find that high exposure to foreign markets with more stringent environmental regulations stimulates MNCs' green patent applications. Predictably, the pursuit of green innovation is positively associated with firm value in the long run. This long-run advantage produces higher economic rents when MNCs' home countries rely on more clean energy for power generation, have a more developed economy and have a more effective government. We further show that this long-run value enhancement effect is more pronounced in Mining & Oil and energy sectors (i.e., more polluting) than sales and service sectors (i.e., less polluting). In addition, MNCs' environmental competitive advantage obtained through green innovation activities is coupled with exposure to MNCs' host countries with high long-term and femininity orientations. Overall, our study highlights that green technology development is a main source of value creation for multinationals.     

Overreaction and underreaction in the foreign exchange market

Research has documented overreaction and underreaction for stocks and stock market indices, but it has not yet analyzed these phenomena with regard to currency exchange rates. This paper examines exchange rate changes following extreme 1-day fluctuations for currencies in industrialized and emerging markets. In this study, the exchange rate is defined as the number of foreign currency units per US dollar. An overreaction phenomenon for currencies in emerging markets and an underreaction phenomenon for currencies in industrial markets are found. Each extreme 1-day currency fluctuation event is classified according to the type of underlying reason as described in the Wall Street Journal. Events for which no announcements (undefined events) were found are associated with a stronger tendency toward overreaction than those events for which an explanation was given (defined events). This suggests that investors overreact more when the source of the extreme fluctuation is largely unknown. The defined events are classified into two groups: economic events and political events. There is some evidence that political events are associated with a stronger tendency toward overreaction than economic events. These findings can be attributed to uncertainty. Political events (e.g., civil uprising) should be more difficult to assess than economic events (e.g., the release of an inflation report), and undefined events should be associated with the largest degree of uncertainty. Cross-sectional analysis is used to relate post-event exchange rate changes to the magnitude of the initial exchange rate change, leakage, day of the week effects, type of currency (from emerging or industrial market), and the type of announcement (economic, political, or undefined) that appeared in the Wall Street Journal. The cross-sectional analysis confirms that currencies in emerging markets experience stronger degrees of overreaction than those of industrial markets, even after controlling for potentially confounding factors. Moreover, it confirms that undefined events experience stronger degrees of overreaction than defined events, even when controlling for other factors.     

Extreme observations and risk assessment in the equity markets of MENA region: Tail measures and Value-at-Risk

The standard “delta-normal” Value-at-Risk methodology requires that the underlying returns generating distribution for the security in question is normally distributed, with moments which can be estimated using historical data and are time-invariant. However, the stylized fact that returns are fat-tailed is likely to lead to under-prediction of both the size of extreme market movements and the frequency with which they occur. In this paper, we use the extreme value theory to analyze four emerging markets belonging to the MENA region (Egypt, Jordan, Morocco, and Turkey). We focus on the tails of the unconditional distribution of returns in each market and provide estimates of their tail index behavior. In the process, we find that the returns have significantly fatter tails than the normal distribution and therefore introduce the extreme value theory. We then estimate the maximum daily loss by computing the Value-at-Risk (VaR) in each market. Consistent with the results from other developing countries [see Gencay, R. and Selcuk, F., (2004). Extreme value theory and Value-at-Risk: relative performance in emerging markets. International Journal of Forecasting, 20, 287–303; Mendes, B., (2000). Computing robust risk measures in emerging equity markets using extreme value theory. Emerging Markets Quarterly, 4, 25–41; Silva, A. and Mendes, B., (2003). Value-at-Risk and extreme returns in Asian stock markets. International Journal of Business, 8, 17–40], generally, we find that the VaR estimates based on the tail index are higher than those based on a normal distribution for all markets, and therefore a proper risk assessment should not neglect the tail behavior in these markets, since that may lead to an improper evaluation of market risk. Our results should be useful to investors, bankers, and fund managers, whose success depends on the ability to forecast stock price movements in these markets and therefore build their portfolios based on these forecasts.     

Explaining banking stability in Sub-Saharan Africa

The study examined banking stability in Sub-Saharan Africa. The results reveal that banking spread (Net Interest Margin – NIM) is the main determinant of stability and the major means to achieve stability during crises periods. We however find the existence of a threshold effect in NIM.Crises in the banking sector consistently showed to reduce stability. While the results show that high percentage of foreign banks reduce stability, we find foreign banks help stabilize the banking sector in periods of crises. The results show that diversification could also have a positive impact on stability (Z-score) even though this relationship was not robust enough. The results also largely support the competition-fragility view. Particularly, we find that less competition during crises periods can help improve stability. Again, we find evidence for both concentration-stability and concentration-fragility hypotheses depending on the stability measure used. We however find that when large banks in concentrated markets are well regulated, stability could be improved. Weak regulatory environment reduces stability (Z-score) directly and matters during crises periods. Our results are robust to the use of different indicators of stability and estimation methods.     

Determinants of global spillovers from US monetary policy

This paper assesses the global spillovers from identified US monetary policy shocks in a global VAR model. US monetary policy generates sizable output spillovers to the rest of the world, which are larger than the domestic effects in the US for many economies. The magnitude of spillovers depends on the receiving country's trade and financial integration, de jure financial openness, exchange rate regime, financial market development, labour market rigidities, industry structure, and participation in global value chains. The role of these country characteristics for the spillovers often differs across advanced and non-advanced economies and also involves non-linearities. Furthermore, economies that experience larger spillovers from conventional US monetary policy also displayed larger downward revisions of their growth forecasts in spring 2013 when the Federal Reserve upset markets by discussing tapering off quantitative easing. The results of this paper suggest that policymakers could mitigate their economies' vulnerability to US monetary policy by fostering trade integration as well as domestic financial market development, increasing the flexibility of exchange rates, and reducing frictions in labour markets. Other policies – such as inhibiting financial integration, industrialisation and participation in global value chains – might mitigate spillovers from US monetary policy, but are likely to reduce long-run growth.     

Modeling systemic risk and dependence structure between oil and stock markets using a variational mode decomposition-based copula method

This study combines the variational mode decomposition (VMD) method and static and time-varying symmetric and asymmetric copula functions to examine the dependence structure between crude oil prices and major regional developed stock markets (S&P500, stoxx600, DJPI and TSX indexes) during bear, normal and bull markets under different investment horizons. Furthermore, it analyzes the upside and downside short- and long-run risk spillovers between oil and stock markets by quantifying three market risk measures, namely the value at risk (VaR), conditional VaR (CoVaR) and the delta CoVaR (∆CoVaR). The results show that there is a tail dependence between oil and all stock markets for the raw return series. By considering time horizons, we show that there is an average dependence between the considered markets for the short-run horizons. However, the tail dependence is also found for the long-run horizons between the oil and stock markets, with the exception of the S&P500 index which exhibits average dependence with the oil market. Moreover, we find strong evidence of up and down risk asymmetric spillovers from oil to stock markets and vice versa in the short-and long run horizons. Finally, the market risk spillovers are asymmetric over the time and investment horizons.     

Dynamic linkages between emerging European and developed stock markets: Has the EMU any impact?

This paper investigates the short- and long-run behavior of major emerging Central European (Poland, Czech Republic, Hungary, Slovakia), and developed (Germany, US) stock markets and assesses the impact of the EMU on stock market linkages. Evidence of one cointegration vector in both a pre- and a post-EMU sub-period indicates market comovements towards a stationary long-run equilibrium path. Central European markets tend to display stronger linkages with their mature counterparts, whereas the US market holds a world leading influential role. No dramatic post-EMU shock is detected in stock market dynamics. The empirical findings have important implications for the effectiveness of domestic policy decisions, as the emerging Central European states have recently joined the EU and local stock markets may become less immunized to external shocks.     

Changing integration of EMU public property markets

This paper examines the impact of the European Monetary Union (EMU) on European public property market integration. Results indicate that the property markets are long-run independent and show little evidence of short-run relationships prior to the formation of the EMU. However, the degree of interdependence and the extent of convergence among the largest property markets have intensified substantially after the launch of the Euro as the common currency in January, 1999. Moreover, each of the property markets under consideration is endogenous in that none is found to “dominate” the others toward long-run equilibrium. Short-run results indicate substantial interrelationships among the markets after the adoption of the Euro. Finally, the study shows that stock markets, bond markets, and public property markets follow similar convergence patterns.     

Monetary policy and stock prices – Cross-country evidence from cointegrated VAR models

This study applies the Cointegrated Vector-Autoregressive (CVAR) model to analyze the long-run relationships and short-run dynamics between stock markets and monetary policy across five developed and three emerging economies. Our main aim is to check whether monetary policy plays an important role for stock market developments. As an innovation, monetary policy enters the analysis from three angles: in the form of a broad monetary aggregate, short-term interest rates and net capital flows. Based on this framework, we analyze whether central banks are able to influence stock market developments. Our findings suggest different patterns and causalities for emerging and industrial economies with the stock markets of the former economies more frequently related to monetary aggregates and capital flows. A direct long-run impact from short-term interest rates on stock prices is only observed for 3 out of 8 economies.     

Corporate social responsibility culture and international M&As

We examine the role of corporate culture in M&As by utilizing a unique corporate social responsibility (CSR) dataset, providing in-depth information on multiple dimensions of organizational culture in 22 developed markets. In accordance with the prediction of the culture clash theory, a wider divergence between the CSR corporate cultures of the acquiring and target firms is associated with lower acquirer announcement and long-run returns as well as synergistic gains for the combined firm. Cultural misalignment also increases the time required to finalise a deal, reduces the likelihood of deal completion and the percentage of stock payment. Our results are robust to alternative explanations (e.g., similarities in national culture, acquirer CSR performance, institutional configurations), different regression specifications, and additional cultural misalignment measures. Our findings highlight the importance of the need for a deeper understanding of the role of CSR for the target selection process, integration planning, and financing choice of M&As to corporations and their investors.     

经济开放与货币需求:国际金融风险及持币成本的测度

在中国开放经济体制下的基准货币需求模型中,本文将源于国际金融市场的持币成本设为遗漏潜变量,并构建特定的国际金融综合指数(CIFI)作为该潜变量的测度。借鉴机器学习与测度理论,本文利用对数误差修正模型提出了分步降维的CIFI构造算法,构造了长期CIFI和短期CIFI。结果表明,CIFI构造中的无监督降维步骤有助于减少高维金融数据中的冗余信息。实证分析发现,国际机会成本对中国货币需求具有规律性的前导影响,而在2007至2008年国际金融危机期间,央行的应急措施对长期CIFI所代表的非均衡冲击起到明显的阻截效果,对短期CIFI的影响基本是持续不变的。通过综合指数构造与宏观货币需求模型的算法连接,可以利用CIFI的构成结构从前导时间与影响强度两方面追踪冲击货币需求的国际金融风险的具体来源,这为宏观决策者监测国际金融市场提供了颇有规律的信息。在方法论上,本研究为如何利用模型监测国际金融市场影响宏观经济开辟了一条新路。