Related papers: Cryptocurrencies, Mainstream Asset Classes and Ris…
Methodologies to infer financial networks from the price series of speculative assets vary, however, they generally involve bivariate or multivariate predictive modelling to reveal causal and correlational structures within the time series…
As it is known in the finance risk and macroeconomics literature, risk-sharing in large portfolios may increase the probability of creation of default clusters and of systemic risk. We review recent developments on mathematical and…
This paper identifies the cryptocurrency market crashes and analyses its dynamics using the complex network. We identify three distinct crashes during 2017-20, and the analysis is carried out by dividing the time series into pre-crash,…
This paper shows that Bitcoin is not correlated to a general uncertainty index as measured by the Google Trends data of Castelnuovo and Tran (2017). Instead, Bitcoin is linked to a Google Trends attention measure specific for the…
Granger-Geweke causality (GGC) is a powerful and popular method for identifying directed functional (`causal') connectivity in neuroscience. In a recent paper, Stokes and Purdon [1] raise several concerns about its use. They make two…
While correlation measures are used to discern statistical relationships between observed variables in almost all branches of data-driven scientific inquiry, what we are really interested in is the existence of causal dependence. Designing…
Identifying the causal structure of systems with multiple dynamic elements is critical to several scientific disciplines. The conventional approach is to conduct statistical tests of causality, for example with Granger Causality, between…
This study investigates how media influence and educational resources shape individual engagement with cryptocurrencies. As digital assets become increasingly mainstream, social media platforms, influencers, and financial analysts play a…
Digital currencies and cryptocurrencies have hesitantly started to penetrate the investors, and the next step will be the regulatory risk management framework. We examine the Value-at-Risk and Expected Shortfall properties for the major…
The recent financial crisis have generated renewed interests in fragilities of global financial networks among economists and regulatory authorities. In particular, a potential vulnerability of the financial networks is the "financial…
Cryptocurrency network analysis consists of applying the tools and methods of social network analysis to transactional data issued from cryptocurrencies. The main difference with most online social networks is that users do not exchange…
In recent years, multi-factor strategies have gained increasing popularity in the financial industry, as they allow investors to have a better understanding of the risk drivers underlying their portfolios. Moreover, such strategies promise…
Propagation of balance-sheet or cash-flow insolvency across financial institutions may be modeled as a cascade process on a network representing their mutual exposures. We derive rigorous asymptotic results for the magnitude of contagion in…
The fast-growing cryptocurrency sector presents both challenges and opportunities for businesses and consumers alike. This study investigates the knowledge, expertise, and buying habits of people who shop using cryptocurrencies. Our survey…
Blockchain and its application on cryptocurrency transactions have gathered a lot of attention and popularity since the birth of the pioneer Bitcoin in 2009. More than 1500 cryptocurrencies are currently circulated in the market. The…
Uncovering the risk transmitting path within economic sectors in China is crucial for understanding the stability of the Chinese economic system, especially under the current situation of the China-US trade conflicts. In this paper, we try…
Evaluation of systemic risk in networks of financial institutions in general requires information of inter-institution financial exposures. In the framework of Debt Rank algorithm, we introduce an approximate method of systemic risk…
With the recent prevalence of darkweb/deepweb (D2web) sites specializing in the trade of exploit kits and malware, malicious actors have easy-access to a wide-range of tools that can empower their offensive capability. In this study, we…
This paper performs a large-scale study of dependency chains in the web, to find that around 50% of first-party websites render content that they did not directly load. Although the majority (84.91%) of websites have short dependency chains…
This study identifies the key factors influencing the price movements of major cryptocurrencies, Bitcoin, Binance Coin, Ethereum, Litecoin, Ripple, and Tether, using Bayesian networks (BNs). This study addresses two key challenges:…