Correlation Between BIG Blockchain and CleanSpark
Can any of the company-specific risk be diversified away by investing in both BIG Blockchain and CleanSpark at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining BIG Blockchain and CleanSpark into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between BIG Blockchain Intelligence and CleanSpark, you can compare the effects of market volatilities on BIG Blockchain and CleanSpark and check how they will diversify away market risk if combined in the same portfolio for a given time horizon. You can also utilize pair trading strategies of matching a long position in BIG Blockchain with a short position of CleanSpark. Check out your portfolio center. Please also check ongoing floating volatility patterns of BIG Blockchain and CleanSpark.
Diversification Opportunities for BIG Blockchain and CleanSpark
0.78 | Correlation Coefficient |
Poor diversification
The 3 months correlation between BIG and CleanSpark is 0.78. Overlapping area represents the amount of risk that can be diversified away by holding BIG Blockchain Intelligence and CleanSpark in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on CleanSpark and BIG Blockchain is a relative statistical measure of the degree to which these equity instruments tend to move together. The correlation coefficient measures the extent to which returns on BIG Blockchain Intelligence are associated (or correlated) with CleanSpark. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of CleanSpark has no effect on the direction of BIG Blockchain i.e., BIG Blockchain and CleanSpark go up and down completely randomly.
Pair Corralation between BIG Blockchain and CleanSpark
Assuming the 90 days horizon BIG Blockchain is expected to generate 3.55 times less return on investment than CleanSpark. But when comparing it to its historical volatility, BIG Blockchain Intelligence is 1.64 times less risky than CleanSpark. It trades about 0.08 of its potential returns per unit of risk. CleanSpark is currently generating about 0.18 of returns per unit of risk over similar time horizon. If you would invest 1,061 in CleanSpark on September 1, 2024 and sell it today you would earn a total of 374.00 from holding CleanSpark or generate 35.25% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
BIG Blockchain Intelligence vs. CleanSpark
Performance |
| Timeline |
| BIG Blockchain Intel |
| CleanSpark |
BIG Blockchain and CleanSpark Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with BIG Blockchain and CleanSpark
The main advantage of trading using opposite BIG Blockchain and CleanSpark positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if BIG Blockchain position performs unexpectedly, CleanSpark can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in CleanSpark will offset losses from the drop in CleanSpark's long position.| BIG Blockchain vs. DeFi Technologies | BIG Blockchain vs. Argo Blockchain PLC | BIG Blockchain vs. DigiMax Global | BIG Blockchain vs. Galaxy Digital Holdings |
| CleanSpark vs. Hut 8 Corp | CleanSpark vs. HIVE Blockchain Technologies | CleanSpark vs. Bit Digital | CleanSpark vs. Terawulf |
Check out your portfolio center.Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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