Correlation Between PT Hatten and Sanurhasta Mitra
Can any of the company-specific risk be diversified away by investing in both PT Hatten and Sanurhasta Mitra 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 Hatten and Sanurhasta Mitra into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between PT Hatten Bali and Sanurhasta Mitra PT, you can compare the effects of market volatilities on PT Hatten and Sanurhasta Mitra 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 Hatten with a short position of Sanurhasta Mitra. Check out your portfolio center. Please also check ongoing floating volatility patterns of PT Hatten and Sanurhasta Mitra.
Diversification Opportunities for PT Hatten and Sanurhasta Mitra
-0.54 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between WINE and Sanurhasta is -0.54. Overlapping area represents the amount of risk that can be diversified away by holding PT Hatten Bali and Sanurhasta Mitra PT in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Sanurhasta Mitra and PT Hatten 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 Hatten Bali are associated (or correlated) with Sanurhasta Mitra. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Sanurhasta Mitra has no effect on the direction of PT Hatten i.e., PT Hatten and Sanurhasta Mitra go up and down completely randomly.
Pair Corralation between PT Hatten and Sanurhasta Mitra
Assuming the 90 days trading horizon PT Hatten Bali is expected to under-perform the Sanurhasta Mitra. But the stock apears to be less risky and, when comparing its historical volatility, PT Hatten Bali is 2.48 times less risky than Sanurhasta Mitra. The stock trades about -0.05 of its potential returns per unit of risk. The Sanurhasta Mitra PT is currently generating about 0.21 of returns per unit of risk over similar time horizon. If you would invest 5,500 in Sanurhasta Mitra PT on December 22, 2024 and sell it today you would earn a total of 9,300 from holding Sanurhasta Mitra PT or generate 169.09% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 98.31% |
Values | Daily Returns |
PT Hatten Bali vs. Sanurhasta Mitra PT
Performance |
Timeline |
PT Hatten Bali |
Sanurhasta Mitra |
PT Hatten and Sanurhasta Mitra Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with PT Hatten and Sanurhasta Mitra
The main advantage of trading using opposite PT Hatten and Sanurhasta Mitra positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if PT Hatten position performs unexpectedly, Sanurhasta Mitra 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 Sanurhasta Mitra will offset losses from the drop in Sanurhasta Mitra's long position.PT Hatten vs. PT Jobubu Jarum | PT Hatten vs. PT Dewi Shri | PT Hatten vs. PT Data Sinergitama | PT Hatten vs. PAM Mineral Tbk |
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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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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