Granger Causality In Risk Research Articles

Extreme risk spillovers between China and major international stock markets

We examine the complex dependence structure and risk spillovers between the Chinese stock market and twelve major international markets. To this end, we employ three types of vine copulas and tests for the Granger causality in risk of Hong et al. (2009). The results indicate that the R-vine copula is the optimal model to characterize the high-dimensional dependence structure of the markets after China joined the WTO, which suggests obvious structural differences with varying degrees of mainly positive dependences. Moreover, we identify unilateral extreme risk spillovers from China to the United States, France, and Germany, and either from Japan to China. We also detect bilateral spillovers between China and the United States, Japan, as well as Australia.

Extreme Spillover between Green Bonds and Clean Energy Markets

This paper examines green bonds (GB), which have received much attention for providing funding for clean energy (CE) market reforms. We investigate the extreme spillover effects between GB and CE markets by using both MVMQ-CAViaR and Granger causality in risk methods over the period from 5 July 2011 to 24 February 2020. Since there are usually extreme asymmetric spillovers between financial markets, we examined whether this phenomenon exists between GB and CE markets. Our empirical analysis results find the significant extreme spillovers from GB to CE markets. In addition, we find that the upside and downside risk spillovers between GB and CE markets are asymmetric. The upside spillover is greater than downside spillover from GB to CE markets and the impact of GB on CE markets is greater. However, the extreme spillover from CE to GB markets is not significant by either the Granger causality in risk or the MVMQ-CAViaR model. Our findings have important implications for investors, policy makers and researchers.

The use of range-based volatility estimators in testing for Granger causality in risk on international capital markets

This study utilizes the extreme value theory (EVT) approach to compare the performance of a wide variety of range-based volatility estimators in the analysis of causality in risk between emerging and developed markets. The AR(1)-GARCH(1,1) model with t-distribution is used as a benchmark. Regulator and firm loss functions are used to select the best volatility model. Two tests of causality in risk are used in our empirical study. The AR-GARCH model with EVT outperforms the other approaches in the case of huge risk. Among the most likely risk-taking markets are Standard & Poor's 500, CAC 40, Nikkei 225, Nasdaq and FTSE 100.

Oil Prices and Stock Markets in Europe: Detection of Extreme Risk Spillover

The goal of this paper is to check existence of Granger causality in risk between eleven European stock markets and crude oil market. We analyze bidirectional instantaneous and delayed Granger causality in tails test results, i.e. whether occurrence of the extreme returns on the crude oil market precede similar events on the main European stock markets and vice versa. Using Brent futures prices and main stock indices in Europe (Belgium, France, Germany, Greece, Italy, Netherlands, Norway, Poland, Spain, Sweden and United Kingdom), we apply testing procedure developed by Candelon and Tokpavi (2016). The main conclusion is that in the vast majority of cases instantaneous causality in tails was symmetrical. We also found that more long-lived reaction appeared as a result to the negative news from the oil market and from the stock markets.

Heterogeneous risk spillovers from crude oil to regional natural gas markets: the role of the shale gas revolution

ABSTRACTThis paper investigates the heterogeneous risk spillovers from crude oil to regional natural gas markets against the background of the North American shale gas revolution. The market risks are measured by the upside and downside VaR. We first confirm the existence of risk spillovers between oil and gas markets by using Granger causality in risk. Then, we employ the MVMQ-CAViaR model to reveal the tail-dependence patterns and propose the performance test to highlight the accuracy of the model for the construction of VaR. Furthermore, we construct quantile impulse-response functions and identify asymmetric features in the magnitude, duration, and direction of response by gas markets to extreme negative and positive oil price shocks. Our results show that the revolution actually affects the risk spillovers from oil to gas markets and exhibits the time-varying property. And the heterogeneous risk-transmission mechanisms depend on the regional characteristics and specific market scenarios. Finally, policy implications are discussed.

Measuring extreme risk of sustainable financial system using GJR-GARCH model trading data-based

This paper investigates the role of gold as a safe haven for stock markets and the US dollar by examining the extreme risk spillovers. The extreme risk is measured by Value at Risk (VaR), which is estimated by GJR-GARCH model based on skewed t distribution. Two test statistics of one-way and two-way Granger causality in risk are used to detect extreme risk spillovers. In general, the empirical results show that there are negative extreme risk spillovers between gold and stock markets and between gold and foreign exchange markets of US dollar, which indicate that gold can act as an effective safe haven against extreme stock and US dollar exchange rate movements. In addition, the global financial crisis can affect the safe haven role of gold.

Analiza zależności przyczynowych w ryzyku między rynkiem ropy naftowej a rynkami reprezentującymi inne klasy aktywów

Wraz z rosnącą zmiennością instrumentów finansowych, zwłaszcza kontraktów na ropę naftową będącą strategicznym surowcem energetycznym, pojawia się potrzeba objęcia rynków finansowych szerszym niż dotychczas spektrum analiz. Koncepcja przyczynowości w sensie Grangera w ryzyku stanowi jeden z możliwych kierunków analizy współzależności między rynkami finansowymi. Celem niniejszego opracowania jest zatem weryfikacja występowania zależności przyczynowych w ryzyku między kursem terminowym ropy naftowej a rynkami reprezentującymi inne klasy aktywów: akcje, obligacje, waluty. Wykorzystane dane dotyczą okresu od stycznia 2000 roku do stycznia 2015 roku. Wyniki przeprowadzonych analiz dostarczają argumentów potwierdzających istnienie związku przyczynowego między ceną ropy naftowej a notowaniami dziesięcioletnich obligacji japońskich. W odniesieniu do kursów walutowych występowanie zależności przyczynowych w ryzyku stwierdzono w przypadku tych walut, które kwotowane były w dolarach.

Extreme risk spillover effects in world gold markets and the global financial crisis

Using the approach of Granger causality in risk, we investigate extreme risk spillover effects among four major world gold markets (London, New York, Tokyo and Shanghai) before and after the recent global financial crisis. We find (i) that there are strong extreme risk spillover effects between London and New York, and London and Shanghai, (ii) that most of the extreme risk spillovers to Tokyo and Shanghai are from New York rather than from London, but London leads New York in risk spillovers, (iii) that extreme risk spillover effects from Tokyo and Shanghai to New York are limited, but those to London play an important role, and (iv) that extreme risk spillover effects between Tokyo and Shanghai are weak or negligible. We also find that extreme risk is more quickly transmitted in the post-crisis era than in the pre-crisis era, an effect that is related to the safe-haven or risk-hedging property or the speculative value of gold.

Extreme risk spillovers between crude oil and stock markets

This paper investigates the spillovers of extreme risks between crude oil and stock markets using daily data of the S&P 500 stock index and West Texas Intermediate (WTI) crude oil futures returns. Based on the method of Granger causality in risk, Value at Risk (VaR) is employed to measure market risk, and a class of kernel-based tests is used to detect negative and positive risk spillover effects. Empirical results reveal that there are significant risk spillovers between the two markets. Extreme movements, past or current, in one market may have a significant predictive power for those in the other market. Prior to the recent financial crisis, there are positive risk spillovers from stock market to crude oil market, and negative spillovers from crude oil market to stock market. After the financial crisis, bidirectional positive risk spillovers are strengthened markedly. The risk spillovers may occur instantaneously, and/or with a (long) time delay. Both positive and negative risk spillover effects exhibit asymmetric correlations.

Granger causality and systemic risk

Building on the concept of Granger causality in risk in Hong et al. (2009), and focusing on an international sample of large-capitalization banks, we test for predictability in comovements in the left tails of returns of individual banks and the global system. The main results show that large individual shocks (defined as balance-sheet contractions exceeding the 1% VaR level) are a strong predictor of subsequent shocks in the global system. This evidence is particularly strong for US banks with large desks of proprietary trading. Similarly, we document strong evidence of financial vulnerabilities (exposures) to systemic shocks in US subprime creditors.

Spillover from oil market to stock market in Nigeria: Evidence from granger causality in risk

It has been stated that the activities of the commercial banks on the Nigerian stock market exposed the economy to global economic crisis. This view is premised on the huge and disproportionate investment of the Nigerian commercial banks in the oil and gas sector, which was directly affected by the recession between 2007 and 2009. With falling oil price and asset value of the banks, the resulting mismatch in the balance sheets of these banks resulted in financial and economic crisis. The Central Bank of Nigeria (CBN) consequently responded by reconsolidating banking sector for effective monitoring. This study then examines the impact of global risk exposure on Nigerian economy by focusing on the connection between oil price and stock market activity. The study employs the method of Granger causality in risk. This method is used to infer the predictive information in risk of one variable from another. It makes use of the sample cross-correlation function (CCF) of the binary indicators for value at risk (VaR). The study successfully implements the method for the relationship between oil price and stock returns for Nigeria. This study uses daily data over the period January 2, 2003 through December 31, 2013. To clean the data of the holiday effects of daily data, we apply the Gallant-Rossi-Tauchen filter. The data were then transformed to obtain their daily returns by computing the first difference of their natural logarithm in percentage. The study finds that oil price return causes stock returns in extreme risk. This phenomenon is found absent prior to January 1, 2007 but present in the sub-sample between January, 2007 and December, 2013. The results indicate that the sudden and unprecedented fall in crude oil price during the global recession between 2007 and 2009 undermined the balance sheets of banks in Nigeria. The study further finds that the market participants not only care about the changes in the oil price and stock index but also in the rate of change in them. The study indicates the need to consolidate the financial sector for effective monitoring and to reduce the exposure to global risk in particular to oil price movement. The study suggests that the policymakers must avail themselves necessary forecasting tools to gauge the immediate and differed spillovers between the stock and the oil markets, and that the current bank consolidation policy should be made more effective to enhance monitoring.

Measuring Flight-to-Quality with Granger-Causality Tail Risk Networks

We introduce an econometric method to detect and analyze events of flight-to-quality by financial institutions. Specifically, using the recently proposed test for the detection of Granger causality in risk (Hong et al. 2009), we construct a bipartite network of systemically important banks and sovereign bonds, where the presence of a link between two nodes indicates the existence of a tail causal relation. This means that tail events in the equity variation of a bank helps in forecasting a tail event in the price variation of a bond. Inspired by a simple theoretical model of flight-to-quality, we interpret links of the bipartite networks as distressed trading of banks directed toward the sovereign debt market and we use them for defining indicators of flight-to-quality episodes. Based on the quality of the involved bonds, we distinguish different patterns of flight-to-quality in the 2006-2014 period. In particular, we document that, during the recent Eurozone crisis, banks with a considerable systemic importance have significantly impacted the sovereign debt market chasing the top-quality government bonds. Finally, an out of sample analysis shows that connectedness and centrality network metrics have a significant cross-sectional forecasting power of bond quality measures.

Extreme risk spillover among international REIT markets

This article studies extreme risk spillovers among international Real Estate Investment Trust (REIT) markets. We apply the procedure of Granger causality in risk to six major markets. Our full-sample (1991–2010) results suggest that strong risk spillovers, which could be unidirectional or bidirectional, are not universal across markets. Moreover, downside spillovers are found generally more common and stronger than upside spillovers. Further analyses based on three subsamples indicate that risk spillover has become more frequent and stronger over time. This adds onto the evidence of increasing financial integration. Taken together, our findings have important implications for international portfolio diversification and risk management.

Granger causality in risk and detection of extreme risk spillover between financial markets

Abstract Controlling and monitoring extreme downside market risk are important for financial risk management and portfolio/investment diversification. In this paper, we introduce a new concept of Granger causality in risk and propose a class of kernel-based tests to detect extreme downside risk spillover between financial markets, where risk is measured by the left tail of the distribution or equivalently by the Value at Risk (VaR). The proposed tests have a convenient asymptotic standard normal distribution under the null hypothesis of no Granger causality in risk. They check a large number of lags and thus can detect risk spillover that occurs with a time lag or that has weak spillover at each lag but carries over a very long distributional lag. Usually, tests using a large number of lags may have low power against alternatives of practical importance, due to the loss of a large number of degrees of freedom. Such power loss is fortunately alleviated for our tests because our kernel approach naturally discounts higher order lags, which is consistent with the stylized fact that today’s financial markets are often more influenced by the recent events than the remote past events. A simulation study shows that the proposed tests have reasonable size and power against a variety of empirically plausible alternatives in finite samples, including the spillover from the dynamics in mean, variance, skewness and kurtosis respectively. In particular, nonuniform weighting delivers better power than uniform weighting and a Granger-type regression procedure. The proposed tests are useful in investigating large comovements between financial markets such as financial contagions. An application to the Eurodollar and Japanese Yen highlights the merits of our approach.

Estimating ‘Value at Risk’ of crude oil price and its spillover effect using the GED-GARCH approach

Estimation has been carried out using GARCH-type models, based on the Generalized Error Distribution (GED), for both the extreme downside and upside Value-at-Risks (VaR) of returns in the WTI and Brent crude oil spot markets. Furthermore, according to a new concept of Granger causality in risk, a kernel-based test is proposed to detect extreme risk spillover effect between the two oil markets. Results of an empirical study indicate that the GED-GARCH-based VaR approach appears more effective than the well-recognized HSAF (i.e. historical simulation with ARMA forecasts). Moreover, this approach is also more realistic and comprehensive than the standard normal distribution-based VaR model that is commonly used. Results reveal that there is significant two-way risk spillover effect between WTI and Brent markets. Supplementary study indicates that at the 99% confidence level, when negative market news arises that brings about a slump in oil price return, historical information on risk in the WTI market helps to forecast the Brent market. Conversely, it is not the case when positive news occurs and returns rise. Historical information on risk in the two markets can facilitate forecasts of future extreme market risks for each other. These results are valuable for anyone who needs evaluation and forecasts of the risk situation in international crude oil markets.

Spillover effect of US dollar exchange rate on oil prices

The US dollar is frequently used as the invoicing currency of international crude oil trading. Hence, the fluctuation in US dollar exchange rate is believed to underlie the volatility of crude oil price and especially its forecasting accuracy. Using econometric techniques including cointegration, VAR model, ARCH type models and a newly proposed approach to test Granger causality in risk, three spillover effects are explored, i.e., mean spillover, volatility spillover and risk spillover. Using rigorous appraisal, analysis is made of the influence of US dollar exchange rate on the international crude oil price from the perspective of market trading and several findings have been obtained. Firstly, a significant long-term equilibrium cointegrating relationship can be identified between the two markets. This suggests a crucial reason for the fluctuation in crude oil price. But interestingly, the reverse does not work. Specifically, the influence of a standard deviation disturbance of US dollar exchange rate on oil price is increased quite slowly, and reaches its highest point, 1.0088 US dollars per barrel, after 1 year or so with a slightly and steadily diminishing process afterward. This implies that the US dollar depreciation for the years under investigation was a key factor in driving up the international crude oil price. Secondly, there is apparent volatility and clustering for the two market prices, whereas their volatility spillover effect is insignificant, which reveals that their price volatility take relatively independent paths and the instant fluctuation in US dollar exchange rate will not cause significant change in the oil market. Finally, their risk spillover effect appears quite limited, hence price risk influence of US dollar exchange rate on the oil market is not necessarily emphasized too much. Put it another way, compared with the powerful oil market, the impact of US dollar exchange rate is confirmed to be relatively partial. These results indicate that the influence of US dollar exchange rate on the international crude oil market proves quite significant in the long term; however, its short-term and instant influence turns out to be quite limited, which is noteworthy to be taken into account for oil market researchers, market trading analysts and traders.