Connectedness between cryptocurrency and technology sectors: International evidence

© 2020 Elsevier Inc. This paper investigates the connectedness between the technology sector and cryptocurrency markets using Diebold and Yilmaz\u27s (2012, 2014) network connectedness measures. The data cover the period from August 1, 2014 to October 31, 2018. Despite the existence of significant interconnectedness between technology sectors worldwide, the results show that contributions from and to the cryptocurrency market are negligible. The cryptocurrency market appears to be less integrated with the technological system and structurally less exposed to systemic risk. To check robustness, application of Fernández-Macho\u27s (2018) wavelet local multiple correlations found an almost exact linear relationship between global technology sectors for periods of quarterly and longer. Additionally, the Granger causality test confirmed the independence results except for in Japan, Turkey and the USA, where possible changes in cryptocurrency prices may be effective in predicting returns. These findings provide insights for cryptocurrency regulators and potential investors around the world

Are There Any Volatility Spill-Over Effects among Cryptocurrencies and Widely Traded Asset Classes?

In the present paper, we investigate connectedness within cryptocurrency markets as well as across the Bitcoin index (hereafter, BPI) and widely traded asset classes such as traditional currencies, stock market indices and commodities, such as gold and Brent oil. A spill over index approach with the spectral representation of variance decomposition networks, is employed to measure connectedness. Results show no significant spillover effects between the nascent market of cryptocurrencies and other financial markets. We suggest that cryptocurrencies are real independent financial instruments that pose no danger to financial system stability. Concerning the connectedness within the cryptocurrency markets, we report a time–frequency–dynamics connectedness nature. Moreover, the decomposition of the total spill over index is mostly dominated by a short frequency component (2–4 days) leading to the conclusion that this nascent market is highly speculative at present. These findings provide insights for regulators and potential international investors

Tail dependence between oil and stocks of major oil-exporting countries using the CoVaR approach

This paper investigates the negative tail risk dependence between oil shocks and stock indices (at aggregated and desegregated levels) for Saudi Arabia (KSA), United Arab Emirates (UAE) and Russia, over the period between 2007 and 2016. DCC-MGARCH approach and CoVaR measure are employed to assess the oil shock exposure. The results show that the tail dependence is significant and depends on the origin of the oil shocks, with intensity that varies across countries and sectors. Keywords: Oil price shocks, Oil-exporting countries, Conditional VaR, JEL Classification: C58, G11, Q

BETTER SAFE HAVENS DURING COVID-19: A COMPARISON BETWEEN ISLAMIC AND SELECTED FINANCIAL ASSETS

This study examines the safe haven properties of six assets (the S&P Technology Index, S&P GSCI Commodity Index, bitcoin, the Dow Jones Islamic Equity Index, the Dow Jones Global Sukuk Index and US Treasury bonds) during contiguous infectious diseases, employing the equity index returns of three regional markets (S&P500, S&P Europe, and S&P Asia-Pacific) over the period 2010 - 2020 Q2. In the research, information-rich methodological tools such as the Markov switching approach and the DCC-GARCH model are used. Our results suggest that Sukuk and bonds act as safe havens for different types of investors during the ongoing COVID-19 crisis. This property is, however, is not confirmed for the S&P Technology Index, Commodity Index, bitcoin or the DJ Islamic Equity Index. Moreover, using the time-varying VAR model and the new measure of pandemic uncertainty proposed by Baker et al. (2020), the results demonstrate that the COVID-19 pandemic has led to uncertainty and heightened volatility spillovers among regional equities and the safe haven assets examined. The key results of the study are robust and useful for portfolio managers and investors

Market-Risk Optimization among the Developed and Emerging Markets with CVaR Measure and Copula Simulation

In this paper, the generalized Pareto distribution (GPD) copula approach is utilized to solve the conditional value-at-risk (CVaR) portfolio problem. Particularly, this approach used (i) copula to model the complete linear and non-linear correlation dependence structure, (ii) Pareto tails to capture the estimates of the parametric Pareto lower tail, the non-parametric kernel-smoothed interior and the parametric Pareto upper tail and (iii) Value-at-Risk (VaR) to quantify risk measure. The simulated sample covers the G7, BRICS (association of Brazil, Russia, India, China and South Africa) and 14 popular emerging stock-market returns for the period between 1997 and 2018. Our results suggest that the efficient frontier with the minimizing CVaR measure and simulated copula returns combined outperforms the risk/return of domestic portfolios, such as the US stock market. This result improves international diversification at the global level. We also show that the Gaussian and t-copula simulated returns give very similar but not identical results. Furthermore, the copula simulation provides more accurate market-risk estimates than historical simulation. Finally, the results support the notion that G7 countries can provide an important opportunity for diversification. These results are important to investors and policymakers

Oil shocks and equity markets: The case of GCC and BRIC economies

This study analyzes the relationship between oil shocks and the equity markets of a group of world major oil producers and consumers encompassing both the GCC and BRICS economies. We employ a novel framework to decompose the oil shocks (demand, supply, and risk shocks) into their daily components. Subsequently, we also employ a network connectedness approach to investigate the static and time-varying connectedness of these shocks with equity markets. Our sample period ranges from January 6, 2005, to July 17, 2020. Empirical results show a medium connectedness between examined equity markets and oil shocks, in terms of returns and volatility, with an unpreceded level during the recent COVID-19 crisis. Furthermore, the volatility of oil-exporting countries contributes more to the volatility connectedness. Demand shock and risk shock are the main contributors to the connectedness

BGRT: une nouvelle base générique de règles d'association triadiques: application à l'autocomplétion de requêtes dans les folksonomies

National audienceThe development of social tagging systems on the Web under the participatory movement often called "Web 2.0", has enabled the emergence of new forms of indexing web content, allowing users to categorize their resources by associating their keywords, called tags. Considered as tripartite hypergraphs of users, tags and resources, the resulting structures, aka folksonomies, are of great interest in information retrieval. In this paper, we exploit these triples (resources, users, tags) to introduce a new definition of a generic basis of triadic association rules, called . We show that the use of generic rules for autocompletion feature highlights the relevance of folksonomies and their real interest in the case of information retrieval. The first results obtained on a real folksonomy are promising and offer many opportunities.Le tagging social s'est récemment imposé dans le paysage du web collaboratif (Web 2.0) comme un support à l'organisation des ressources partagées, permettant aux utilisateurs de catégoriser leurs ressources en leurs associant des mots clefs, appelés tags. La structure ainsi créée, baptisée sous le nom de folksonomie, est assimilée à un hypergraphe triparti d'utilisateurs, de tags et de ressources. Dans ce papier, nous exploitons ces triplets pour introduire une nouvelle définition d'une base générique de règles d'association triadiques, appelée BGRT. Nous montrons que l'utilisation de ces règles génériques pour l'autocomplétion de requêtes permet de mettre en exergue la pertinence des folksonomies et leur intérêt réel pour la recherche d'information. Les premiers résultats obtenus sur une folksonomie réelle s'avèrent prometteurs et ouvrent de nombreuses perspective

Scalable mining of frequent tri-concepts from folksonomies

International audienceMining frequent tri-concepts from folksonomies is an interesting problem with broad applications. Most of the previous tri-concepts mining based algorithms avoided a straightforward handling of the triadic contexts and paid attention to an unfruitful projection of the induced search space into dyadic contexts. As a such projection is very computationally expensive since several tri-concepts are computed redundantly, scalable mining of folksonomies remains a challenging problem. In this paper, we introduce a new algorithm, called Tricons, that directly tackles the triadic form of folksonomies towards a scalable extraction of tri-concepts. The main thrust of the introduced algorithm stands in the application of an appropriate closure operator that splits the search space into equivalence classes for the the localization of tri-minimal generators. These tri-minimal generators make the computation of the tri-concepts less arduous than do the pioneering approches of the literature.The experimental results show that the Tricons enables the scalable frequent tri-concepts mining over two real-life folksonomie

Systemic risk spillovers between crude oil and stock index returns of G7 economies: Conditional value-at-risk and marginal expected shortfall approaches

In this study, we examine systemic risk and dependence between oil and stock market indices of G7 economies between January 2003 and November 2017. Coincidentally, this timeframe covers different distress periods in financial and energy markets. We use several time-constant, time-varying and time-varying Markov-copula models to examine the dependence. Further, we use the delta conditional value-at-risk (Delta CoVaR) of Adrian and Brunnermeier (2016) and marginal expected shortfall (MES) of Acharya et al. (2012) to captures the risk spillover effects and give evidence of systemic risk. From the copula analysis, we find dissimilar dependence structure between returns series of oil and the G7 stock markets. For France, Germany and Japan, the dependence is Markov-switching time-varying, while it is time-varying for the United States and Canada, constant for the United Kingdom and around zero for Italy. Our empirical evidence on systemic risk indicates that oil price dynamics contributes significantly more to the G7 stock market returns during volatile times than during tranquil times. In particular, the Canada stock market appears more sensitive and vulnerable to negative external shocks emerging from the crude oil market than the other markets. Further, the country risk rankings identified using MES and Delta CoVaR may not be identical. In addition, the analysis results suggest that the crude oil market can be a good diversifier for investors in Japan and France and that the investors in the rest of G7 countries must act more carefully. (C) 2020 Elsevier B.V. All rights reserved