An Approach to Security for Unstructured Big Data

Security of Big Data is a huge concern. In a broad sense, Big Data contains two types of data: structured and unstructured. Providing security to unstructured data is more difficult than providing security to structured data. In this paper, we have developed an approach to provide adequate security to unstructured data by considering types of data and their sensitivity levels. We have reviewed the different analytics methods of Big Data to build nodes of different types of data. Each type of data has been classified to provide adequate security and enhance the overhead of the security system. To provide security to a data node, and a security suite has been designed by incorporating different security algorithms. Those security algorithms collectively form a security suite which has been interfaced with the data node. Information on data sensitivity has been collected through a survey. We have shown through several experiments on multiple computer systems with varied configurations that data classification with respect to sensitivity levels enhances the performance of the system. The experimental results show how and in what amount the designed security suite reduces overhead and increases security simultaneously.     

Global financial crisis and dependence risk analysis of sector portfolios: a vine copula approach

We use regular vine (r-vine), canonical vine (c-vine) and drawable vine (d-vine) copulas to examine the dependence risk characteristics of three 20-stock portfolios from the retail, manufacturing and gold-mining equity sectors of the Australian market in periods before, during and after the 2008–2009 global financial crisis (GFC). Our results indicate that the retail portfolio is less risky than the manufacturing counterpart in the crisis period, while the gold-mining portfolio is less risky than both the retail and manufacturing sector portfolios. Both the retail and gold stocks display a higher propensity to yield positively skewed returns in the crisis periods, contrary to the manufacturing stocks. The r-vine is found to best capture the multivariate dependence structure of the stocks in the retail and gold-mining portfolios, while the d-vine does it for the manufacturing stock portfolio. These findings could be used to develop dependence risk- and investment risk-adjusted strategies for investment, rebalancing and hedging which more adequately account for the downside risk in various market conditions.     

Commodities and financial variables: Analyzing relationships in a changing regime environment

This paper examines the dynamic interrelationships among four highly internationally traded commodities, oil, copper, gold and silver and three commodity-relevant financial variables including short-run interest rate, exchange rate and the world equity index. We explore these interrelationships using weekly time series in a regime switching environment. The results clearly show that the interrelationships are not only regime-dependent but there is also predictive information on those relationships across the two regimes classified by the level of uncertainties. The findings are likely to be of interest to both investors and policy makers. Contrary to other related studies, the results point to mixed evidence of directional relationships between these widely traded individual commodities and macro-financial variables, depending on the regimes.     

Dynamic Relationships among GCC Stock Markets and Nymex Oil Futures

Daily relationships among stock markets of the Gulf Cooperation Council (GCC) members, excluding Qatar, form two equilibrium relationships with varying predictive power. The Saudi market leads, followed by Bahrain and United Arab Emirates. Kuwait, which is dominated by momentum traders, and Oman have the weakest links with the other GCC markets. Only the Saudi index can predict—and be predicted by—New York Mercantile Exchange oil futures prices. Therefore these markets are candidates for diversified regional portfolios at the country level. The trading day effect is weak for all GCC markets and oil futures prices but remains consistent with findings for the U.S. stock market. (JEL C22 , F3 , Q49 )     

A Multiple and Partial Wavelet Analysis of the Oil Price,Inflation, Exchange Rate,and Economic Growth Nexus in Saudi Arabia

This article provides a fresh insight into the dynamic nexus between oil prices, the Saudi/US dollar exchange rate, inflation, and output growth rate in Saudi Arabia’ economy, using novel Morlet’ wavelet methods. Specifically, it implements various tools of methodology: the continuous wavelet power spectrum, the cross-wavelet power spectrum, the wavelet coherency, the multiple and the partial wavelet coherence to the annual sample period 1969–2014. Our results unveil that the relationships among the variables evolve through time and frequency. From the time-domain view, we show strong but non-homogenous linkages between the four variables. From the frequency-domain view, we uncover significant wavelet coherences and strong lead-lag relationships. From an economic view, the wavelet analysis shows that Saudi economy is still exposed to several global risk factors, which are mainly related to the oil market volatility, and the pegging of the local currency to the US dollar. Such risk factors strongly and negatively affect the real economic growth, exert more pressure on inflation, and substantially limit the freedom to pursue an independent monetary policy.     

Dynamics of CDS spread indexes of US financial sectors

This article examines the Credit Default Swap (CDS) spread index for three sectors, banking, financial services and insurance, in the short and long run. In the long run, the results show that the index of the insurance sector which sells the long term CDS contracts has the highest adjustment, while the banking sector is not error correcting. In the short run, although the insurance sector CDS spread index has general predictive power of all sector CDS spreads, the evidence suggests that the banking sector particularly leads the financial services and this in turn leads the insurance sector, implying a leading sector CDS pricing role for the banking spreads in the short run. The short run sensitivity Generalized Impulse Response Function (GIRF) and Generalized Variance Decomposition (GVDC) analyses also demonstrate that the sectors’ credit risk responds more to credit events in the banking sector than in the other two sectors other than their own over a 50 day horizon. However, the lowest cross sector CDS shock impacts in the short run come from the insurance sector. These results are useful for regulators wishing to embark on new regulations of these financial institutions such as Basel III.     

Tail dependence risk exposure and diversification potential of Islamic and conventional banks

This paper undertakes a rolling window comparative analysis of risks for portfolios consisting of GCC Islamic and conventional bank indices. We draw our empirical results by employing canonical, drawable and regular vine copula models, as well as by implementing a portfolio optimization method with a conditional Value-at-Risk constraint. We find evidence of higher riskiness in the group of Islamic banks relative to the group of conventional banks across each of the financial rolling window scenarios under consideration. Specifically, a greater negative (nonlinear) tail asymmetric dependence is observed in the pairs of Islamic banks’ relationships. The results also show that the optimal portfolio model supports a clear preference towards the group of conventional banks in regard to risk minimization and diversification benefits.     

Cooperative Carbon Alliances: Defining an Agenda for Global Industrial Decarbonisation

There have been several recent proposals for cooperative climate alliances, from the OECD, the IMF, the World Trade Organization (WTO), the German Government, and others. The “Climate Club” concept comprises many different possible regimes and intents. They range from so-called transformational clubs (which incentivise membership and penalise non-members), to looser joint agreements on ambition level for climate action, such as the UN’s Net-Zero Coalition. Given this option, there is not yet any agreement on how to design such a “club”, or its aims, rules, or scope of membership.

     

Dynamic Global Linkages of the BRICS Stock Markets with the United States and Europe Under External Crisis Shocks: Implications for Portfolio Risk Forecasting

Crisis shocks often lead to changes in the interdependence across stock markets and thus affect risk assessment and management. This paper investigates the extent to which the global financial crisis of 2008–09, which was triggered by the US subprime crisis in 2007, and the European debt crisis that started at the end of 2009, affects the interdependence of the leading emerging markets of the BRICS countries with those of the United States and Europe. Our empirical analysis makes use of the FIAPARCH model combined with the Dynamic Equicorrelation (DECO‐FIAPARCH), which allows for the estimation of market linkage for a large group of countries as a whole, while controlling for asymmetric volatility and long memory. The results reveal the presence of important changes in the time‐varying linkages of the BRICS stock markets with the US and European ones. In particular, the average linkages have significantly been higher between 2007 and the first half of 2012 than the remaining part of the sample, and there is also evidence of a structural change around the Lehman Brothers collapse. We also show the effects of these stylised facts on portfolio risk assessment and forecasting.     

Sovereign bond market dependencies and crisis transmission around the eurozone debt crisis: a dynamic copula approach

We examine the dependency between the European government bond markets around the recent sovereign debt crisis. A dynamic copula approach is used to model the time-varying dependence structure of those government bond markets, evaluate the nature and strength of their dependencies over time, and gauge the transmission of the crisis shocks. Our results can be summarized as follows: i) the eurozone sovereign bond markets under consideration have a significant and positive dependence with the Greek and the EMU benchmark sovereign bond markets; ii) the dynamic-BB7 copula function best describes the dependence structure between these sovereign bond markets and provides evidence of asymmetric tail dependence; iii) the conditional probability of crisis transmission from Greece to other eurozone countries is higher than the other way around; and iv) Greece is the most vulnerable country when the eurozone entered into the sovereign debt crisis.