Vector error correction models to measure connectedness of Bitcoin exchange markets

Bitcoins are traded on various exchange platforms and, therefore, prices may differ across trading venues. We aim to investigate return connectedness across eight of the major exchanges of Bitcoin, both from a static and a dynamic viewpoint. To this end, we employ an extension of the order-invariant forecast error variance decomposition proposed by Diebold and Yilmaz (2012) to a generalized vector error correction framework. Our results suggest that there is strong connectedness among the exchanges, as expected, although some of them behave dissimilarly. We identify Bitfinex and Coinbase as leading exchanges during the considered period, while Kraken as a follower exchange. We also obtain that connectedness across exchanges is strongly dynamic, as it evolves over time

Effective transfer entropy to measure information flows in credit markets

In this paper we propose to study the dynamics of financial contagion between the credit default swap (CDS) and the sovereign bond markets through effective transfer entropy, a model-free methodology which enables to overcome the required hypotheses of classical price discovery measures in the statistical and econometric literature, without being restricted to linear dynamics. By means of effective transfer entropy we correct for small sample biases which affect the traditional Shannon transfer entropy, as well as we are able to conduct inference on the estimated directional information flows. In our empirical application, we analyze the CDS and bond market data for eight countries of the European Union, and aim to discover which of the two assets is faster at incorporating the information on the credit risk of the underlying sovereign. Our results show a clear and statistically significant prominence of the bond market for pricing the sovereign credit risk, especially during the crisis period. During the post-crisis period, instead, a few countries behave dissimilarly from the others, in particular Spain and the Netherlands

Vector error correction models to measure connectedness of Bitcoin exchange markets

Bitcoins are traded on various exchange platforms and, therefore, prices may differ across trading venues. We aim to investigate return connectedness across eight of the major exchanges of Bitcoin, both from a static and a dynamic viewpoint. To this end, we employ an extension of the order-invariant forecast error variance decomposition proposed by Diebold and Yilmaz (2012) to a generalized vector error correction framework. Our results suggest that there is strong connectedness among the exchanges, as expected, although some of them behave dissimilarly. We identify Bitfinex and Coinbase as leading exchanges during the considered period, while Kraken as a follower exchange. We also obtain that connectedness across exchanges is strongly dynamic, as it evolves over time

High frequency price change spillovers in bitcoin markets

The study of connectedness is key to assess spillover effects and identify lead-lag relationships among market exchanges trading the same asset. By means of an extension of Diebold and Yilmaz (2012) econometric connectedness measures, we examined the relationships of five major Bitcoin exchange platforms during two periods of main interest: The 2017 surge in prices and the 2018 decline. We concluded that Bitfinex and Gemini are leading exchanges in terms of return spillover transmission during the analyzed time-frame, while Bittrexs act as a follower. We also found that connectedness of overall returns fell substantially right before the Bitcoin price hype, whereas it leveled out during the period the down market period. We confirmed that the results are robust with regards to the modeling strategies

Libra or Librae? Basket based stablecoins to mitigate foreign exchange volatility spillovers

The paper aims to assess, from an empirical viewpoint, the advantages of a stablecoin whose value is derived from a basket of underlying currencies, against a stablecoin which is pegged to the value of one major currency, such as the dollar. To this aim, we first find the optimal weights of the currencies that can comprise our basket. We then employ volatility spillover decomposition methods to understand which foreign currency mostly drives the others. We then look at how the stability of either stablecoin is affected by currency shocks by means of spillover networks built on VAR models. Our empirical findings show that our basket based stablecoin is less volatile than all single currencies. This result is fundamental for policy making, and especially for emerging markets with a high level of remittances: a Librae (basket based stablecoin) can preserve their value during turbolent times better than a Libra (single currency based stablecoin)

Technical analysis on the Bitcoin market: Trading opportunities or investors\u2019 pitfall?

In this paper we aimed to examine the profitability of technical trading rules in the Bitcoin market by using trend-following and mean-reverting strategies. We applied our strategies on the Bitcoin price series sampled both at 5-min intervals and on a daily basis, during the period 1 January 2012 to 20 August 2019. Our findings suggest that, overall, trading on daily data is more profitable than going intraday. Furthermore, we concluded that the Buy and Hold strategy outperforms the examined alternatives on an intraday basis, while Simple Moving Averages yield the best performances when dealing with daily data

Assessing harmfulness and vulnerability in global bipartite networks of terrorist-target relationships

In this paper we leverage a massive attack-focused terrorist database and we design a dynamic bipartite network analysis to examine the structural evolution of terrorists-targets relationships. We introduce two novel measures to jointly assess harmfulness and vulnerability of terrorist and target groups, both at local and global level. Statistical validation using null models provides evidence that the information contained in these measures is new and not included in other variables, thus emphasizing the usefulness of these topological indicators. Finally, a policy-support experiment designed as network dismantling-like drill is proposed to assess the effects of potential attack preventive strategies