Correlation Between Pt Pradiksi and PT Jhonlin
Can any of the company-specific risk be diversified away by investing in both Pt Pradiksi and PT Jhonlin 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 Pt Pradiksi and PT Jhonlin into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Pt Pradiksi Gunatama and PT Jhonlin Agro, you can compare the effects of market volatilities on Pt Pradiksi and PT Jhonlin 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 Pt Pradiksi with a short position of PT Jhonlin. Check out your portfolio center. Please also check ongoing floating volatility patterns of Pt Pradiksi and PT Jhonlin.
Diversification Opportunities for Pt Pradiksi and PT Jhonlin
-0.42 | Correlation Coefficient |
Very good diversification
The 3 months correlation between PGUN and JARR is -0.42. Overlapping area represents the amount of risk that can be diversified away by holding Pt Pradiksi Gunatama and PT Jhonlin Agro in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on PT Jhonlin Agro and Pt Pradiksi 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 Pt Pradiksi Gunatama are associated (or correlated) with PT Jhonlin. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of PT Jhonlin Agro has no effect on the direction of Pt Pradiksi i.e., Pt Pradiksi and PT Jhonlin go up and down completely randomly.
Pair Corralation between Pt Pradiksi and PT Jhonlin
Assuming the 90 days trading horizon Pt Pradiksi Gunatama is expected to under-perform the PT Jhonlin. But the stock apears to be less risky and, when comparing its historical volatility, Pt Pradiksi Gunatama is 11.34 times less risky than PT Jhonlin. The stock trades about -0.08 of its potential returns per unit of risk. The PT Jhonlin Agro is currently generating about 0.08 of returns per unit of risk over similar time horizon. If you would invest 27,600 in PT Jhonlin Agro on September 13, 2024 and sell it today you would earn a total of 6,400 from holding PT Jhonlin Agro or generate 23.19% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 98.41% |
Values | Daily Returns |
Pt Pradiksi Gunatama vs. PT Jhonlin Agro
Performance |
Timeline |
Pt Pradiksi Gunatama |
PT Jhonlin Agro |
Pt Pradiksi and PT Jhonlin Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Pt Pradiksi and PT Jhonlin
The main advantage of trading using opposite Pt Pradiksi and PT Jhonlin positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Pt Pradiksi position performs unexpectedly, PT Jhonlin 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 Jhonlin will offset losses from the drop in PT Jhonlin's long position.Pt Pradiksi vs. Mahkota Group Tbk | Pt Pradiksi vs. Palma Serasih PT | Pt Pradiksi vs. Cisadane Sawit Raya | Pt Pradiksi vs. Diamond Food Indonesia |
PT Jhonlin vs. Mahkota Group Tbk | PT Jhonlin vs. Palma Serasih PT | PT Jhonlin vs. Cisadane Sawit Raya | PT Jhonlin vs. Diamond Food 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 Valuation module to check real value of public entities based on technical and fundamental data.
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