Correlation Between Telkom Indonesia and Global Partner
Can any of the company-specific risk be diversified away by investing in both Telkom Indonesia and Global Partner 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 Telkom Indonesia and Global Partner into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Telkom Indonesia Tbk and Global Partner Acq, you can compare the effects of market volatilities on Telkom Indonesia and Global Partner 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 Telkom Indonesia with a short position of Global Partner. Check out your portfolio center. Please also check ongoing floating volatility patterns of Telkom Indonesia and Global Partner.
Diversification Opportunities for Telkom Indonesia and Global Partner
0.6 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Telkom and Global is 0.6. Overlapping area represents the amount of risk that can be diversified away by holding Telkom Indonesia Tbk and Global Partner Acq in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Global Partner Acq and Telkom Indonesia 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 Telkom Indonesia Tbk are associated (or correlated) with Global Partner. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Global Partner Acq has no effect on the direction of Telkom Indonesia i.e., Telkom Indonesia and Global Partner go up and down completely randomly.
Pair Corralation between Telkom Indonesia and Global Partner
Considering the 90-day investment horizon Telkom Indonesia Tbk is expected to generate 0.72 times more return on investment than Global Partner. However, Telkom Indonesia Tbk is 1.38 times less risky than Global Partner. It trades about -0.02 of its potential returns per unit of risk. Global Partner Acq is currently generating about -0.21 per unit of risk. If you would invest 1,815 in Telkom Indonesia Tbk on September 1, 2024 and sell it today you would lose (107.00) from holding Telkom Indonesia Tbk or give up 5.9% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 19.84% |
Values | Daily Returns |
Telkom Indonesia Tbk vs. Global Partner Acq
Performance |
Timeline |
Telkom Indonesia Tbk |
Global Partner Acq |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
Telkom Indonesia and Global Partner Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Telkom Indonesia and Global Partner
The main advantage of trading using opposite Telkom Indonesia and Global Partner positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Telkom Indonesia position performs unexpectedly, Global Partner 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 Global Partner will offset losses from the drop in Global Partner's long position.Telkom Indonesia vs. T Mobile | Telkom Indonesia vs. Comcast Corp | Telkom Indonesia vs. Lumen Technologies | Telkom Indonesia vs. Charter Communications |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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