Cryptocurrencies have seen explosive growth over the last few years. Now their market capitalization surpasses that of traditional markets such as stocks and commodities; leading to algorithms being created specifically to analyze and forecast volatility.
We analyzed the development of cryptocurrency markets using daily data for three major cryptocurrencies and USDT denominated in USD. Our results show that all three cryptocurrencies, except USDT, exhibit similar patterns of fluctuation.
Time series analysis
Cryptocurrency prices fluctuate frequently, making it hard for traders to predict their future value. To analyze this fluctuation, researchers use time series analysis to detect patterns and forecast trends – this method has proved especially useful in the highly correlated cryptocurrency market.
This study uses daily data from major cryptocurrencies to analyze their price behavior, employing various techniques such as time series analysis, correlation analysis and forecasting. Furthermore, it attempts to uncover any underlying structures influencing their dynamics of price change.
This research shows that digital currencies are highly interrelated. Furthermore, most coins exhibit positive links with Bitcoin, Ethereum and Ripple – suggesting no effective hedges among primary import currencies during times of distress. Furthermore, most cryptocurrencies exhibit systematic bubble risks as well as high degrees of interdependence making their hedging an uphill task for investors and portfolio managers.
Correlation analysis
Correlation analysis is a statistical technique for measuring the strength of linear relationships between two variables. Correlation coefficient values range from -1 for perfect inversions up to one when there is positive correlation, with zero indicating no linearity at all.
Correlation coefficients increase with increasing one variable – for instance, increased homework hours often leads to improved grades or vice versa.
Price and market cap of cryptocurrencies can be greatly influenced by their circulating supply. High supplies can make it harder for demand to exceed supply, which leads to reduced price and market cap of crypto assets. As a result, some investors seek out low correlation investments while others take on more risk to gain greater returns; to mitigate such risk it is wise to maintain a diversified portfolio.
Stochastic analysis
Cryptocurrencies have highly volatile prices that are affected by many different factors, from news to popularity and court decisions – Ripple’s recent victory in its lawsuit against the SEC may have had a notable effect. However, it’s important to distinguish short-term market fluctuations from longer-term trends: while short-term reactions and news may affect cryptocurrency price movements quickly, overall market trends should always take precedence.
Stochastic analysis is a tool used to represent uncertainty in situations using probability distributions. It is an indispensable resource for traders, planners and analysts who require knowledge about how their investments perform under uncertain conditions as well as being able to assess probabilities associated with various outcomes.
WalletInvestor’s long-term LTC forecast is pessimistic, anticipating that LTC will experience a downtrend until 2022 when its value should rebound and reach USD $40 per coin. According to this company’s projections, cryptocurrency should reach this threshold around December of that year.
Forecasting
When trying to predict price trends of virtual currencies, three forms of analysis may be employed: fundamental, technical and forecasting. Fundamental analysis involves considering all aspects of a market while forecasting relies on statistical trends; both approaches have long been utilized by financial professionals worldwide and have proven their worth over time.
This study employed 16 virtual currencies with market capitalizations greater than $1 billion as the sample, much larger than previous research. Data research took place over seven natural years, divided into two periods known as Period 1 and Period 2, wherein key explanatory variables included the OHLC prices of Bitcoin itself, other cryptocurrencies, and Google search volumes related to its search volume.
This research shows that major capitalized cryptocurrencies possess strong pairwise correlations among themselves as well as with market volatility indices, suggesting they play an integral part in risk transmission across markets.
