Correlation Between HIVE Blockchain and Indo Tambangraya
Can any of the company-specific risk be diversified away by investing in both HIVE Blockchain and Indo Tambangraya 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 HIVE Blockchain and Indo Tambangraya into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between HIVE Blockchain Technologies and Indo Tambangraya Megah, you can compare the effects of market volatilities on HIVE Blockchain and Indo Tambangraya 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 HIVE Blockchain with a short position of Indo Tambangraya. Check out your portfolio center. Please also check ongoing floating volatility patterns of HIVE Blockchain and Indo Tambangraya.
Diversification Opportunities for HIVE Blockchain and Indo Tambangraya
0.65 | Correlation Coefficient |
Poor diversification
The 3 months correlation between HIVE and Indo is 0.65. Overlapping area represents the amount of risk that can be diversified away by holding HIVE Blockchain Technologies and Indo Tambangraya Megah in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Indo Tambangraya Megah and HIVE 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 HIVE Blockchain Technologies are associated (or correlated) with Indo Tambangraya. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Indo Tambangraya Megah has no effect on the direction of HIVE Blockchain i.e., HIVE Blockchain and Indo Tambangraya go up and down completely randomly.
Pair Corralation between HIVE Blockchain and Indo Tambangraya
Given the investment horizon of 90 days HIVE Blockchain Technologies is expected to under-perform the Indo Tambangraya. In addition to that, HIVE Blockchain is 1.4 times more volatile than Indo Tambangraya Megah. It trades about -0.18 of its total potential returns per unit of risk. Indo Tambangraya Megah is currently generating about -0.06 per unit of volatility. If you would invest 335.00 in Indo Tambangraya Megah on December 28, 2024 and sell it today you would lose (50.00) from holding Indo Tambangraya Megah or give up 14.93% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 95.24% |
Values | Daily Returns |
HIVE Blockchain Technologies vs. Indo Tambangraya Megah
Performance |
Timeline |
HIVE Blockchain Tech |
Indo Tambangraya Megah |
HIVE Blockchain and Indo Tambangraya Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with HIVE Blockchain and Indo Tambangraya
The main advantage of trading using opposite HIVE Blockchain and Indo Tambangraya positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if HIVE Blockchain position performs unexpectedly, Indo Tambangraya 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 Indo Tambangraya will offset losses from the drop in Indo Tambangraya's long position.HIVE Blockchain vs. Bitfarms | HIVE Blockchain vs. CleanSpark | HIVE Blockchain vs. Marathon Digital Holdings | HIVE Blockchain vs. Riot Blockchain |
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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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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