An Analysis of Cryptocurrencies Conditional Cross Correlations

“Small things matter most”: The spillover effects in the cryptocurrency market and gold as a silver bullet

“…They reported variation in the correlation of extreme returns under different market conditions (bull and bear markets). On a wider note, the current literature on cryptocurrency has been highly entrenched in the financial risk management (see, for instance, Aslanidis et al, 2019 , Katsiampa et al, 2019 , Charfeddine and Maouchi, 2019 , Canh et al, 2019 , Bouri et al, 2018 and Baek et al (2015)). These studies employed the traditional quantitative approaches to investigate systematic risks as well as the efficiency in cryptocurrency markets.…”

A Dynamic Linguistic Decision Making Approach for a Cryptocurrency Investment Scenario

“…From time to time, the investor has to decide if he or she ought to hold or changes his or her investment decision according to the market behavior. Considering that cryptocurrencies are unrelated to main traditional assets like stock and bond indices, or gold [11], [12], the investor must rely only on the information provided by the cryptocurrency market, and his or her own risk appraisal.…”

“…They included some macroeconomic data as explanatory variables, in addition to lagged price and volume figures. However, as several authors have shown [11], [12], cryptocurrencies are detached from the main traditional assets and real economy proxies. Recently, Atsalakis et al [13] used a PATSOS neuro-fuzzy controller forecasting system, in order to predict price changes in four cryptocurrencies.…”

“…It has been found that the standard deviation of cryptocurrency returns is ten times greater than that of traditional assets (stocks and bonds) [12]. In addition, other authors have reported strong persistence in return volatility [9], [4].…”

Data Analytics for the Cryptocurrencies Behavior

“…There have been some successes in the matter of correctly analysing and study the economical behaviour of the cryptocurrencies, such as an accurate forecasting on the price trend by the use of Gradient Boost Decision Trees [11] or a dissection of the bubbles in the Bitcoin history [12].…”