Correlation Between Mitra Pinasthika and Bank Cimb
Can any of the company-specific risk be diversified away by investing in both Mitra Pinasthika and Bank Cimb 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 Mitra Pinasthika and Bank Cimb into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Mitra Pinasthika Mustika and Bank Cimb Niaga, you can compare the effects of market volatilities on Mitra Pinasthika and Bank Cimb 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 Mitra Pinasthika with a short position of Bank Cimb. Check out your portfolio center. Please also check ongoing floating volatility patterns of Mitra Pinasthika and Bank Cimb.
Diversification Opportunities for Mitra Pinasthika and Bank Cimb
0.9 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Mitra and Bank is 0.9. Overlapping area represents the amount of risk that can be diversified away by holding Mitra Pinasthika Mustika and Bank Cimb Niaga in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bank Cimb Niaga and Mitra Pinasthika 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 Mitra Pinasthika Mustika are associated (or correlated) with Bank Cimb. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bank Cimb Niaga has no effect on the direction of Mitra Pinasthika i.e., Mitra Pinasthika and Bank Cimb go up and down completely randomly.
Pair Corralation between Mitra Pinasthika and Bank Cimb
Assuming the 90 days trading horizon Mitra Pinasthika Mustika is expected to generate 0.67 times more return on investment than Bank Cimb. However, Mitra Pinasthika Mustika is 1.5 times less risky than Bank Cimb. It trades about 0.08 of its potential returns per unit of risk. Bank Cimb Niaga is currently generating about -0.01 per unit of risk. If you would invest 90,488 in Mitra Pinasthika Mustika on September 3, 2024 and sell it today you would earn a total of 8,512 from holding Mitra Pinasthika Mustika or generate 9.41% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Mitra Pinasthika Mustika vs. Bank Cimb Niaga
Performance |
Timeline |
Mitra Pinasthika Mustika |
Bank Cimb Niaga |
Mitra Pinasthika and Bank Cimb Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Mitra Pinasthika and Bank Cimb
The main advantage of trading using opposite Mitra Pinasthika and Bank Cimb positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Mitra Pinasthika position performs unexpectedly, Bank Cimb 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 Cimb will offset losses from the drop in Bank Cimb's long position.Mitra Pinasthika vs. Saratoga Investama Sedaya | Mitra Pinasthika vs. Puradelta Lestari PT | Mitra Pinasthika vs. Cikarang Listrindo Tbk | Mitra Pinasthika vs. Erajaya Swasembada Tbk |
Bank Cimb vs. Bank Danamon Indonesia | Bank Cimb vs. Bank Maybank Indonesia | Bank Cimb vs. Bank Pan Indonesia | Bank Cimb vs. Indosat Tbk |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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