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This paper deals with the analysis of the relationship between cryptocurrencies and gold prices. In particular, we use fractional integration and cointegration techniques to examine the degree of persistence of the series and the possibility of short and long run equilibrium relationships between them. Our results indicate that there is evidence of mean reversion in gold prices and also in some of the cryptocurrencies; however, cointegration is only found in a few cases with a very small degree of cointegration in the long run relationship. Testing the hypothesis of convergence throughout the ratios, again we only found evidence of mean reversion in the cases of Bytecoin, Dash, Ether, Monero and Ether. • The paper analyses the relationship between cryptocurrencies and gold prices. • Fractional integration and cointegration is used to examine the degree of persistence. • Results indicate that there is evidence of mean reversion in gold prices. • Also in some of the cryptocurrencies. • Cointegration is found in a few cases with a very small degree of cointegration. [ABSTRACT FROM AUTHOR]

Abstract To overcome the limitations of the traditional approach which uses linear causality to examine whether the supply-leading and demand-following theories hold. As certain countries will be found not to follow the theory by using the traditional approach, this paper first suggests using all the proxies of financial development and economic growth as well as both multivariate and bivariate linear and nonlinear causality tests to analyze the relationship between financial development and economic growth. The multivariate nonlinear test not only takes into consideration both dependent and joint effects among variables, but is also able to detect a multivariate nonlinear deterministic process that cannot be detected by using any linear causality test. We find five more countries in which the supply-leading hypothesis and/or demand-following hypothesis hold true than with the traditional approach. However, there is still one country, Pakistan, for which no linear or nonlinear causality is found between its financial development and economic growth. To overcome this limitation, this paper suggests including cointegration in the analysis. This leads us to conclude that either supply-leading or demand-following hypotheses or both hold for all countries without any exception. There will be some types of relationships between economic growth and financial development in any country such that either they move together or economic growth causes financial development or financial development causes economic growth without any exception. The finding in our paper is useful for governments, politicians, and other international institutions in their decision making process for the development of the countries and reducing poverty. Highlights • First to use cointegration and (non)linear causality to study financial development and economic growth. • Financial development and economic growth are moving together in some developing countries. • Both demand-following and supply-leading theories hold for all of the countries studied in our paper. • Including nonlinear test allow us to detect causality in five more countries. • Our finding helps in the decision making in the development of the countries and reducing poverty. [ABSTRACT FROM AUTHOR]

In this paper we introduce a new methodology for pair trading. This new method is based on the calculation of the Hurst exponent of a pair. Our approach is inspired by the classical concepts of co-integration and mean reversion but joined under a unique strategy. We will show how Hurst approach presents better results than classical Distance Method and Correlation strategies in different scenarios. Results obtained prove that this new methodology is consistent and suitable by reducing the drawdown of trading over the classical ones getting as a result a better performance. [ABSTRACT FROM AUTHOR]

In this paper, Stock market comovements are examined using cointegration, Granger causality tests and nonlinear approaches in context of mutual information and correlations. Since underlying data sets are affected by non-stationarities and trends, we also apply Adaptive Multifractal Detrended Fluctuation Analysis (AMF-DFA) and Adaptive Multifractal Detrended Cross-Correlation Analysis (AMF-DXA). We find only 170 pair of Stock markets cointegrated, and according to the Granger causality and mutual information, we realize that the strongest relations lies between emerging markets, and between emerging and frontier markets. According to scaling exponent given by AMF-DFA, h ( q = 2 ) > 1 , we find that all underlying data sets belong to non-stationary process. According to Efficient Market Hypothesis (EMH), only 8 markets are classified in uncorrelated processes at 2 σ confidence interval. 6 Stock markets belong to anti-correlated class and dominant part of markets has memory in corresponding daily index prices during January 1995 to February 2014. New-Zealand with H = 0 . 457 ± 0 . 004 and Jordan with H = 0 . 602 ± 0 . 006 are far from EMH. The nature of cross-correlation exponents based on AMF-DXA is almost multifractal for all pair of Stock markets. The empirical relation, H x y ≤ [ H x x + H y y ] ∕ 2 , is confirmed. Mentioned relation for q > 0 is also satisfied while for q < 0 there is a deviation from this relation confirming behavior of markets for small fluctuations is affected by contribution of major pair. For larger fluctuations, the cross-correlation contains information from both local (internal) and global (external) conditions. Width of singularity spectrum for auto-correlation and cross-correlation are Δ α x x ∈ [ 0 . 304 , 0 . 905 ] and Δ α x y ∈ [ 0 . 246 , 1 . 178 ] , respectively. The wide range of singularity spectrum for cross-correlation confirms that the bilateral relation between Stock markets is more complex. The value of σ D C C A indicates that all pairs of stock market studied in this time interval belong to cross-correlated processes. [ABSTRACT FROM AUTHOR]

In order to investigate the evolution of stock market in any period of time, in this paper, combined with sliding window method, Granger causality test and cointegration test, a novel algorithm of constructing directed-weighted financial stock networks via meso-scale. We use the proposed algorithm on the financial stock data of the Shanghai Stock Exchange from January 1st, 2016 to December 31st, 2020 divided at the meso-scale level to construct some directed-weighted financial stock networks with fixed meso-scale and different meso-scale. Analyzing the topology and robustness of these constructed networks indicates that the robustness of financial stock networks with fixed meso-scale (assuming one year) is generally poor. By comparison, in 2018, the financial stocks were closely in contact with each other while the stock market was relatively stable. We also noted that the financial stock networks with different meso-scale show a high level of robustness when being attacked according to descending arrangement of in-degree or out-degree. They are however less robust against attacks according to descending arrangement of degree. Besides, the networks perform best for a meso-scale of 190. Hence, long-term investors are advised to consider a 190-day holding. • A novel algorithm of constructing directed-weighted financial networks is proposed. • The financial stock networks with fixed and different meso-scale are constructed. • The topology characteristics and robustness of the proposed networks are discussed. • The optimal holding time is achieved for long-term investors. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, cointegration relationships among 26 global stock market indices over the periods of sub-prime and European debt crisis and their influence rank are investigated by constructing and analyzing directed and weighted cointegration networks. The obtained results are shown as follows: the crises have changed cointegration relationships among stock market indices, their cointegration relationship increased after the Lehman Brothers collapse, while the degree of cointegration gradually decreased from the sub-prime to European debt crisis. The influence of US, Japan and China market indices are entirely distinguished over different periods. Before European debt crisis US stock market is a ‘global factor’ which leads the developed and emerging markets, while the influence of US stock market decreased evidently during the European debt crisis. Before sub-prime crisis, there is no significant evidence to show that other stock markets co-move with China stock market, while it becomes more integrated with other markets during the sub-prime and European debt crisis. Among developed and emerging stock markets, the developed stock markets lead the world stock markets before European debt crisis, while due to the shock of sub-prime and European debt crisis, their influences decreased and emerging stock markets replaced them to lead global stock markets. [Copyright &y& Elsevier]

Abstract: This paper explores the co-movement of Shanghai stock market and China Yuan (CNY) exchange rates. First, we find that stock price and exchange rate are significantly cross-correlated. Second, employing a cointegration test allowing for a structural break, we find that the Shanghai Composite Index (SCI) is not cointegrated with the exchange rate of CNY/USD. The so-called “cointegration” found in previous studies is just caused by the shock of the recent financial crisis. Third, using linear and nonlinear Granger causality tests, we find no causality between stock prices and exchange rates during the period before the recent financial crisis. After the financial crisis, a unidirectional causality behavior running from exchange rates to stock index is present. [Copyright &y& Elsevier]

Abstract: This paper analyses the behaviour of volatility for several international stock market indexes, namely the SP 500 (USA), the Nikkei (Japan), the PSI 20 (Portugal), the CAC 40 (France), the DAX 30 (Germany), the FTSE 100 (UK), the IBEX 35 (Spain) and the MIB 30 (Italy), in the context of non-stationarity. Our empirical results point to the evidence of the existence of integrated behaviour among several of those stock market indexes of different dimensions. It seems, therefore, that the behaviour of these markets tends to some uniformity, which can be interpreted as the existence of a similar behaviour facing to shocks that may affect the worldwide economy. Whether this is a cause or a consequence of market globalization is an issue that may be stressed in future work. [Copyright &y& Elsevier]

Abstract: In this paper we present new results for the frequency domain principal components estimator of the cointegration space for stationary long memory processes of Morana [Appl. Econ. Lett. 11 (2004) 837], concerning asymptotic properties, identification of the cointegration space and the linkage with the frequency domain least-squares estimator. An application of the approach to stock market volatility data shows that the methodology can effectively be employed for the modelling of long-run relationships, which could not be handled using the standard – cointegration approach. [Copyright &y& Elsevier]

Abstract: This paper uses threshold autoregressive (TAR) and momentum threshold autoregressive (M-TAR) models to address the problem of asymmetry within the Portuguese stock market. These asymmetric error correction models extend the original cointegration models to deal with the problem of low power of unit roots and cointegration tests in the presence of asymmetric adjustment. [Copyright &y& Elsevier]

The present paper investigates persistence and inter-dependence of bitcoin on other popular alternative coins. We employ fractional integration approach in our analysis of persistence, while a more recent fractional cointegration technique in VAR set-up, proposed by Johansen (2008), is used to investigate inter-dependence in pricing of the paired cryptocurrencies. Having partitioned the series into periods before and after the 2017/2018 cryptocurrency price crash, as determined by Bitcoin pricing, we obtain some interesting results. Higher persistence of price shocks is observed after the crash, which is probably due to speculative transactions among cryptocurrency traders, and more evidences of non-mean reversions are revealed, implying chances of further price fall in cryptocurrencies. Cointegration relationships between bitcoin and alternative coins exist in both periods, with weak correlations observed mostly in the post-crash period. Our results further indicate the possibility of market efficiency between pair of cryptocurrency. Generally, we hope the findings will serve as guide to investors in cryptocurrency markets. • Bitcoin is highly priced and highly capitalized. • Prices of other cryptocurrencies are cointegrated with that of Bitcoin. • Cryptocurrency markets are more efficient after the 2017/2018 price crash. • Volatility persistence of cryptocurrency is higher after the 2017/2018 crash. [ABSTRACT FROM AUTHOR]