Correlation Between Puradelta Lestari and PT Sarana
Can any of the company-specific risk be diversified away by investing in both Puradelta Lestari and PT Sarana 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 Puradelta Lestari and PT Sarana into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Puradelta Lestari PT and PT Sarana Menara, you can compare the effects of market volatilities on Puradelta Lestari and PT Sarana 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 Puradelta Lestari with a short position of PT Sarana. Check out your portfolio center. Please also check ongoing floating volatility patterns of Puradelta Lestari and PT Sarana.
Diversification Opportunities for Puradelta Lestari and PT Sarana
0.88 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Puradelta and TOWR is 0.88. Overlapping area represents the amount of risk that can be diversified away by holding Puradelta Lestari PT and PT Sarana Menara in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on PT Sarana Menara and Puradelta Lestari 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 Puradelta Lestari PT are associated (or correlated) with PT Sarana. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of PT Sarana Menara has no effect on the direction of Puradelta Lestari i.e., Puradelta Lestari and PT Sarana go up and down completely randomly.
Pair Corralation between Puradelta Lestari and PT Sarana
Assuming the 90 days trading horizon Puradelta Lestari PT is expected to generate 0.45 times more return on investment than PT Sarana. However, Puradelta Lestari PT is 2.23 times less risky than PT Sarana. It trades about -0.11 of its potential returns per unit of risk. PT Sarana Menara is currently generating about -0.08 per unit of risk. If you would invest 14,800 in Puradelta Lestari PT on December 22, 2024 and sell it today you would lose (1,300) from holding Puradelta Lestari PT or give up 8.78% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 98.31% |
Values | Daily Returns |
Puradelta Lestari PT vs. PT Sarana Menara
Performance |
Timeline |
Puradelta Lestari |
PT Sarana Menara |
Puradelta Lestari and PT Sarana Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Puradelta Lestari and PT Sarana
The main advantage of trading using opposite Puradelta Lestari and PT Sarana positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Puradelta Lestari position performs unexpectedly, PT Sarana 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 Sarana will offset losses from the drop in PT Sarana's long position.Puradelta Lestari vs. Pakuwon Jati Tbk | Puradelta Lestari vs. Sido Muncul PT | Puradelta Lestari vs. Bekasi Fajar Industrial | Puradelta Lestari vs. Bank Pembangunan Timur |
PT Sarana vs. Tower Bersama Infrastructure | PT Sarana vs. Merdeka Copper Gold | PT Sarana vs. XL Axiata Tbk | PT Sarana vs. Japfa Comfeed Indonesia |
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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