Correlation Between BigBearai Holdings and Applied Blockchain
Can any of the company-specific risk be diversified away by investing in both BigBearai Holdings and Applied Blockchain 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 BigBearai Holdings and Applied Blockchain into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between BigBearai Holdings and Applied Blockchain, you can compare the effects of market volatilities on BigBearai Holdings and Applied Blockchain 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 BigBearai Holdings with a short position of Applied Blockchain. Check out your portfolio center. Please also check ongoing floating volatility patterns of BigBearai Holdings and Applied Blockchain.
Diversification Opportunities for BigBearai Holdings and Applied Blockchain
0.68 | Correlation Coefficient |
Poor diversification
The 3 months correlation between BigBearai and Applied is 0.68. Overlapping area represents the amount of risk that can be diversified away by holding BigBearai Holdings and Applied Blockchain in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Applied Blockchain and BigBearai Holdings 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 BigBearai Holdings are associated (or correlated) with Applied Blockchain. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Applied Blockchain has no effect on the direction of BigBearai Holdings i.e., BigBearai Holdings and Applied Blockchain go up and down completely randomly.
Pair Corralation between BigBearai Holdings and Applied Blockchain
Given the investment horizon of 90 days BigBearai Holdings is expected to generate 1.27 times more return on investment than Applied Blockchain. However, BigBearai Holdings is 1.27 times more volatile than Applied Blockchain. It trades about 0.16 of its potential returns per unit of risk. Applied Blockchain is currently generating about 0.14 per unit of risk. If you would invest 160.00 in BigBearai Holdings on September 17, 2024 and sell it today you would earn a total of 139.00 from holding BigBearai Holdings or generate 86.88% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
BigBearai Holdings vs. Applied Blockchain
Performance |
Timeline |
BigBearai Holdings |
Applied Blockchain |
BigBearai Holdings and Applied Blockchain Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with BigBearai Holdings and Applied Blockchain
The main advantage of trading using opposite BigBearai Holdings and Applied Blockchain positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if BigBearai Holdings position performs unexpectedly, Applied Blockchain 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 Applied Blockchain will offset losses from the drop in Applied Blockchain's long position.BigBearai Holdings vs. Innodata | BigBearai Holdings vs. CLPS Inc | BigBearai Holdings vs. ARB IOT Group | BigBearai Holdings vs. FiscalNote Holdings |
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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 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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