Correlation Between Alumindo Light and Tera Data
Can any of the company-specific risk be diversified away by investing in both Alumindo Light and Tera Data 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 Alumindo Light and Tera Data into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Alumindo Light Metal and Tera Data Indonusa, you can compare the effects of market volatilities on Alumindo Light and Tera Data 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 Alumindo Light with a short position of Tera Data. Check out your portfolio center. Please also check ongoing floating volatility patterns of Alumindo Light and Tera Data.
Diversification Opportunities for Alumindo Light and Tera Data
0.38 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Alumindo and Tera is 0.38. Overlapping area represents the amount of risk that can be diversified away by holding Alumindo Light Metal and Tera Data Indonusa in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Tera Data Indonusa and Alumindo Light 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 Alumindo Light Metal are associated (or correlated) with Tera Data. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Tera Data Indonusa has no effect on the direction of Alumindo Light i.e., Alumindo Light and Tera Data go up and down completely randomly.
Pair Corralation between Alumindo Light and Tera Data
Assuming the 90 days trading horizon Alumindo Light Metal is expected to generate 2.17 times more return on investment than Tera Data. However, Alumindo Light is 2.17 times more volatile than Tera Data Indonusa. It trades about 0.11 of its potential returns per unit of risk. Tera Data Indonusa is currently generating about -0.02 per unit of risk. If you would invest 6,500 in Alumindo Light Metal on September 3, 2024 and sell it today you would earn a total of 900.00 from holding Alumindo Light Metal or generate 13.85% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 97.62% |
Values | Daily Returns |
Alumindo Light Metal vs. Tera Data Indonusa
Performance |
Timeline |
Alumindo Light Metal |
Tera Data Indonusa |
Alumindo Light and Tera Data Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Alumindo Light and Tera Data
The main advantage of trading using opposite Alumindo Light and Tera Data positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Alumindo Light position performs unexpectedly, Tera Data 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 Tera Data will offset losses from the drop in Tera Data's long position.Alumindo Light vs. Timah Persero Tbk | Alumindo Light vs. Semen Indonesia Persero | Alumindo Light vs. Mitra Pinasthika Mustika | Alumindo Light vs. Jakarta Int Hotels |
Tera Data vs. PT Dewi Shri | Tera Data vs. Autopedia Sukses Lestari | Tera Data vs. Mitra Pinasthika Mustika | Tera Data vs. Jakarta Int Hotels |
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 Idea Optimizer module to use advanced portfolio builder with pre-computed micro ideas to build optimal portfolio .
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