Correlation Between Bank Rakyat and Cathedra Bitcoin
Can any of the company-specific risk be diversified away by investing in both Bank Rakyat and Cathedra Bitcoin 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 Bank Rakyat and Cathedra Bitcoin into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bank Rakyat and Cathedra Bitcoin, you can compare the effects of market volatilities on Bank Rakyat and Cathedra Bitcoin 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 Bank Rakyat with a short position of Cathedra Bitcoin. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank Rakyat and Cathedra Bitcoin.
Diversification Opportunities for Bank Rakyat and Cathedra Bitcoin
0.62 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Bank and Cathedra is 0.62. Overlapping area represents the amount of risk that can be diversified away by holding Bank Rakyat and Cathedra Bitcoin in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Cathedra Bitcoin and Bank Rakyat 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 Bank Rakyat are associated (or correlated) with Cathedra Bitcoin. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Cathedra Bitcoin has no effect on the direction of Bank Rakyat i.e., Bank Rakyat and Cathedra Bitcoin go up and down completely randomly.
Pair Corralation between Bank Rakyat and Cathedra Bitcoin
Assuming the 90 days horizon Bank Rakyat is expected to under-perform the Cathedra Bitcoin. But the pink sheet apears to be less risky and, when comparing its historical volatility, Bank Rakyat is 4.16 times less risky than Cathedra Bitcoin. The pink sheet trades about -0.16 of its potential returns per unit of risk. The Cathedra Bitcoin is currently generating about -0.01 of returns per unit of risk over similar time horizon. If you would invest 6.50 in Cathedra Bitcoin on August 31, 2024 and sell it today you would lose (1.19) from holding Cathedra Bitcoin or give up 18.31% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Bank Rakyat vs. Cathedra Bitcoin
Performance |
Timeline |
Bank Rakyat |
Cathedra Bitcoin |
Bank Rakyat and Cathedra Bitcoin Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Bank Rakyat and Cathedra Bitcoin
The main advantage of trading using opposite Bank Rakyat and Cathedra Bitcoin positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank Rakyat position performs unexpectedly, Cathedra Bitcoin 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 Cathedra Bitcoin will offset losses from the drop in Cathedra Bitcoin's long position.Bank Rakyat vs. Bank Mandiri Persero | Bank Rakyat vs. Piraeus Bank SA | Bank Rakyat vs. Eurobank Ergasias Services | Bank Rakyat vs. Kasikornbank Public Co |
Cathedra Bitcoin vs. Arcane Crypto AB | Cathedra Bitcoin vs. Cypherpunk Holdings | Cathedra Bitcoin vs. CreditRiskMonitorCom | Cathedra Bitcoin vs. SPENN Technology AS |
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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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