Correlation Between Bank Mandiri and Delivra Health
Can any of the company-specific risk be diversified away by investing in both Bank Mandiri and Delivra Health 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 Mandiri and Delivra Health into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bank Mandiri Persero and Delivra Health Brands, you can compare the effects of market volatilities on Bank Mandiri and Delivra Health 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 Mandiri with a short position of Delivra Health. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank Mandiri and Delivra Health.
Diversification Opportunities for Bank Mandiri and Delivra Health
0.79 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Bank and Delivra is 0.79. Overlapping area represents the amount of risk that can be diversified away by holding Bank Mandiri Persero and Delivra Health Brands in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Delivra Health Brands and Bank Mandiri 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 Mandiri Persero are associated (or correlated) with Delivra Health. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Delivra Health Brands has no effect on the direction of Bank Mandiri i.e., Bank Mandiri and Delivra Health go up and down completely randomly.
Pair Corralation between Bank Mandiri and Delivra Health
Assuming the 90 days horizon Bank Mandiri Persero is expected to under-perform the Delivra Health. But the pink sheet apears to be less risky and, when comparing its historical volatility, Bank Mandiri Persero is 4.68 times less risky than Delivra Health. The pink sheet trades about -0.2 of its potential returns per unit of risk. The Delivra Health Brands is currently generating about -0.03 of returns per unit of risk over similar time horizon. If you would invest 1.70 in Delivra Health Brands on September 19, 2024 and sell it today you would lose (0.60) from holding Delivra Health Brands or give up 35.29% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Bank Mandiri Persero vs. Delivra Health Brands
Performance |
Timeline |
Bank Mandiri Persero |
Delivra Health Brands |
Bank Mandiri and Delivra Health Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Bank Mandiri and Delivra Health
The main advantage of trading using opposite Bank Mandiri and Delivra Health positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank Mandiri position performs unexpectedly, Delivra Health 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 Delivra Health will offset losses from the drop in Delivra Health's long position.Bank Mandiri vs. Morningstar Unconstrained Allocation | Bank Mandiri vs. Bondbloxx ETF Trust | Bank Mandiri vs. Spring Valley Acquisition | Bank Mandiri vs. Bondbloxx ETF Trust |
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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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