Is bitcoin the new digital gold? To answer this question, we investigate the potential benefits of bitcoin during extremely volatile periods. We use the multivariate extreme value theory, which is the appropriate statistical approach to model the tail dependence structure of the return...

We build an agent-based model to study how the interplay between low- and high- frequency trading affects asset price dynamics. Our main goal is to investigate whether high-frequency trading exacerbates market volatility and generates flash crashes. In the model, low-frequency agents adopt...

We investigate the effects of different regulatory policies directed towards high-frequency trading (HFT) through an agent-based model of a limit order book able to generate flash crashes as the result of the interactions between low- and high-frequency (HF) traders. We analyze the impact of the...

Reviewing the definition and measurement of speculative bubbles in context of contagion, this paper analyses the DotCom bubble in American and European equity markets using the dynamic conditional correlation (DCC) model proposed as on one hand as an econometrics explanation and on the other...

Through the application of the VAR-AGARCH model to intra-day data for three cryp-tocurrencies (Bitcoin, Ethereum, and Litecoin), this study examines the return and volatility spillover between these cryptocurrencies during the pre-COVID-19 period and the COVID-19 period. We also estimate the...

Using daily data for eight major cryptocurrencies and bivariate extreme value theory (peaks-over-threshold method), this study examines the extreme dependence between returns and trading volumes in the cryptocurrency market. It is shown that, irrespective of the cryptocurrency under...