Several Fundamental Properties of Dcca Cross-Correlation Coefficient

Pereira

2019

JRFM

The rapid development of cryptocurrencies has drawn attention to this particular market, with investors trying to understand its behaviour and researchers trying to explain it. The evolution of cryptocurrencies’ prices showed a kind of bubble and a crash at the end of 2017. Based on this event, and on the fact that Bitcoin is the most recognized cryptocurrency, we propose to evaluate the contagion effect between Bitcoin and other major cryptocurrencies. Using the Detrended Cross-Correlation Analysis correlation coefficient (ΔρDCCA) and comparing the period after and before the crash, we found evidence of a contagion effect, with this particular market being more integrated now than in the past—something that should be taken into account by current and potential investors.

Section: Data and Methodsologymentioning

confidence: 99%

Contagion Effect in Cryptocurrency Market

Pereira

2019

JRFM

“…This is an efficient coefficient according to [45,46], and besides its use in different research areas (see the work of [47][48][49]), such as other Econophysics methodologies, it has applications in finance. For this purpose, see the work in [50][51][52][53][54], among many others.…”

Section: Methodsmentioning

confidence: 99%

An Econophysics Study of the S&P Global Clean Energy Index

Loures

2020

Sustainability

The study of how financial markets behave continues to be interesting. The existence of more and more data and the development of statistical techniques are some reasons for the increase in research in finance. However, the difficulty in understanding some markets’ behavior is a continuous challenge. In this context, a new research area called Econophysics has emerged, which is constantly increasing in size. We propose in this work to use methodologies related to Econophysics to analyze one stock index composed of firms producing clean energy (S&P Global Clean Energy Index) and compare it with the New York Stock Exchange (NYSE) as a stock market benchmark and with the price of crude oil. In a context where environmental issues are on the agenda, this is an important area of research, because it could help investors to make their decisions. Our results show that the clean energy index seems to have higher time serial dependence than the others, and is less exposed to oil price than the NYSE.

“…This is also an efficient measure even when time series suffer from non-stationarity. For more details about this and other properties of the coefficient, see the work of [52][53][54][55].…”

Section: Data and Methodsologymentioning

confidence: 99%

The Exposure of European Union Productive Sectors to Oil Price Changes

Pereira

2020

Sustainability

Oil is one of the most important products in the world, being used for fuel production but also as an input in several industries. After the oil shocks of the 1970s, which caused great turbulence, the interest in the analysis of this particular product grew. The analysis of the comovements between oil and other assets became a hot topic. In this study, we propose an analysis of how oil price correlates with several industry indexes. The detrended cross-correlation analysis coefficient (ρDCCA) is used, with data from 1992 to 2019, and we analyze not only the correlation between oil and several Euro Stoxx indexes during the whole sample, but also how that correlation evolved for the different decades (1990s, 2000s and 2010s). Naturally, oil and gas are the sectors that correlate the most with crude oil, with correlation coefficients reaching levels higher than 0.6 in some cases. However, the results also indicate that all sectors are now more exposed to oil price variations than in the past, with the financial sector as one of the sectors with the greatest increase in correlation.Sustainability 2020, 12, 1620 2 of 16 importance for the economy as a whole, but also because price shocks are common, having an impact on the economy. Moreover, and because oil is not only a very important raw material but also a non-renewable resource, the study of its behavior, in this case the comovements of its price with stock markets, could go towards a better understanding of how financial stock markets can be related with sustainability (see, for example, [12,13] for some discussion on this topic).In this study we propose an analysis of how oil price correlates with several of the Euro Stoxx industry indexes. The objective is to understand how the correlation differs among 10 different sectorial indexes: oil and gas, basic materials, industrials, consumer goods, health care, consumer services, telecommunications, utilities, financials and technology. Despite the large body of literature analyzing comovements between oil price and other assets, we found some need of work analyzing the possible dynamics of the relationship between crude oil prices and sectoral indexes in the EU. This kind of analysis could contribute to energy policies to reduce European countries' dependence on oil.Despite the existence of several approaches to the study of correlations between oil and different sectors, we propose a different approach. Basing our study on the detrended cross-correlation analysis coefficient (ρDCCA), and with data from 1992 to 2019, we analyse not only the correlation between oil and the chosen indexes during the whole sample, but we also make an analysis for each decade, i.e., the 1990s, 2000s and 2010s. With this, and based on the difference in the correlation between different periods (∆ρDCCA), it is possible to analyze the evolution of correlations over time and understand if those indexes' exposure to possible oil shocks increased or not, something of great importance for all the agents mentioned above.Our main findings point ...