Correlation Between Apple and BANK MANDIRI
Can any of the company-specific risk be diversified away by investing in both Apple and BANK MANDIRI 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 Apple and BANK MANDIRI into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Apple Inc and BANK MANDIRI, you can compare the effects of market volatilities on Apple and BANK MANDIRI 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 Apple with a short position of BANK MANDIRI. Check out your portfolio center. Please also check ongoing floating volatility patterns of Apple and BANK MANDIRI.
Diversification Opportunities for Apple and BANK MANDIRI
-0.31 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Apple and BANK is -0.31. Overlapping area represents the amount of risk that can be diversified away by holding Apple Inc and BANK MANDIRI in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on BANK MANDIRI and Apple 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 Apple Inc are associated (or correlated) with BANK MANDIRI. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of BANK MANDIRI has no effect on the direction of Apple i.e., Apple and BANK MANDIRI go up and down completely randomly.
Pair Corralation between Apple and BANK MANDIRI
Assuming the 90 days trading horizon Apple Inc is expected to generate 0.64 times more return on investment than BANK MANDIRI. However, Apple Inc is 1.57 times less risky than BANK MANDIRI. It trades about 0.09 of its potential returns per unit of risk. BANK MANDIRI is currently generating about -0.01 per unit of risk. If you would invest 16,660 in Apple Inc on August 18, 2024 and sell it today you would earn a total of 4,705 from holding Apple Inc or generate 28.24% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 99.48% |
Values | Daily Returns |
Apple Inc vs. BANK MANDIRI
Performance |
Timeline |
Apple Inc |
BANK MANDIRI |
Apple and BANK MANDIRI Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Apple and BANK MANDIRI
The main advantage of trading using opposite Apple and BANK MANDIRI positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Apple position performs unexpectedly, BANK MANDIRI 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 BANK MANDIRI will offset losses from the drop in BANK MANDIRI's long position.The idea behind Apple Inc and BANK MANDIRI pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.BANK MANDIRI vs. Apple Inc | BANK MANDIRI vs. Apple Inc | BANK MANDIRI vs. Microsoft | BANK MANDIRI vs. Superior Plus Corp |
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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