Correlation Between Bank Central and Unilever Indonesia
Can any of the company-specific risk be diversified away by investing in both Bank Central and Unilever Indonesia 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 Central and Unilever Indonesia into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bank Central Asia and Unilever Indonesia Tbk, you can compare the effects of market volatilities on Bank Central and Unilever Indonesia 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 Central with a short position of Unilever Indonesia. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank Central and Unilever Indonesia.
Diversification Opportunities for Bank Central and Unilever Indonesia
-0.47 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Bank and Unilever is -0.47. Overlapping area represents the amount of risk that can be diversified away by holding Bank Central Asia and Unilever Indonesia Tbk in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Unilever Indonesia Tbk and Bank Central 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 Central Asia are associated (or correlated) with Unilever Indonesia. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Unilever Indonesia Tbk has no effect on the direction of Bank Central i.e., Bank Central and Unilever Indonesia go up and down completely randomly.
Pair Corralation between Bank Central and Unilever Indonesia
Assuming the 90 days trading horizon Bank Central Asia is expected to generate 0.52 times more return on investment than Unilever Indonesia. However, Bank Central Asia is 1.92 times less risky than Unilever Indonesia. It trades about 0.1 of its potential returns per unit of risk. Unilever Indonesia Tbk is currently generating about 0.05 per unit of risk. If you would invest 947,500 in Bank Central Asia on February 7, 2024 and sell it today you would earn a total of 25,000 from holding Bank Central Asia or generate 2.64% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Bank Central Asia vs. Unilever Indonesia Tbk
Performance |
Timeline |
Bank Central Asia |
Unilever Indonesia Tbk |
Bank Central and Unilever Indonesia Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Bank Central and Unilever Indonesia
The main advantage of trading using opposite Bank Central and Unilever Indonesia positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank Central position performs unexpectedly, Unilever Indonesia 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 Unilever Indonesia will offset losses from the drop in Unilever Indonesia's long position.Bank Central vs. Bank Rakyat Indonesia | Bank Central vs. Bank Mandiri Persero | Bank Central vs. Bank Negara Indonesia | Bank Central vs. Astra International Tbk |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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