Correlation Between Sumitomo Rubber and PT Gajah
Can any of the company-specific risk be diversified away by investing in both Sumitomo Rubber and PT Gajah 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 Sumitomo Rubber and PT Gajah into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Sumitomo Rubber Industries and PT Gajah Tunggal, you can compare the effects of market volatilities on Sumitomo Rubber and PT Gajah 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 Sumitomo Rubber with a short position of PT Gajah. Check out your portfolio center. Please also check ongoing floating volatility patterns of Sumitomo Rubber and PT Gajah.
Diversification Opportunities for Sumitomo Rubber and PT Gajah
-0.17 | Correlation Coefficient |
Good diversification
The 3 months correlation between Sumitomo and GH8 is -0.17. Overlapping area represents the amount of risk that can be diversified away by holding Sumitomo Rubber Industries and PT Gajah Tunggal in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on PT Gajah Tunggal and Sumitomo Rubber 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 Sumitomo Rubber Industries are associated (or correlated) with PT Gajah. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of PT Gajah Tunggal has no effect on the direction of Sumitomo Rubber i.e., Sumitomo Rubber and PT Gajah go up and down completely randomly.
Pair Corralation between Sumitomo Rubber and PT Gajah
Assuming the 90 days horizon Sumitomo Rubber Industries is expected to generate 0.18 times more return on investment than PT Gajah. However, Sumitomo Rubber Industries is 5.53 times less risky than PT Gajah. It trades about 0.24 of its potential returns per unit of risk. PT Gajah Tunggal is currently generating about -0.03 per unit of risk. If you would invest 910.00 in Sumitomo Rubber Industries on September 1, 2024 and sell it today you would earn a total of 100.00 from holding Sumitomo Rubber Industries or generate 10.99% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 95.65% |
| Values | Daily Returns |
Sumitomo Rubber Industries vs. PT Gajah Tunggal
Performance |
| Timeline |
| Sumitomo Rubber Indu |
| PT Gajah Tunggal |
Sumitomo Rubber and PT Gajah Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Sumitomo Rubber and PT Gajah
The main advantage of trading using opposite Sumitomo Rubber and PT Gajah positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Sumitomo Rubber position performs unexpectedly, PT Gajah 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 PT Gajah will offset losses from the drop in PT Gajah's long position.| Sumitomo Rubber vs. SEKISUI CHEMICAL | Sumitomo Rubber vs. Sanyo Chemical Industries | Sumitomo Rubber vs. WESTLAKE CHEMICAL | Sumitomo Rubber vs. Lendlease Group |
| PT Gajah vs. SCANSOURCE | PT Gajah vs. RETAIL FOOD GROUP | PT Gajah vs. AUTO TRADER ADR | PT Gajah vs. GungHo Online Entertainment |
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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