Correlation Between Protech Mitra and Dunia Virtual
Can any of the company-specific risk be diversified away by investing in both Protech Mitra and Dunia Virtual 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 Protech Mitra and Dunia Virtual into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Protech Mitra Perkasa and Dunia Virtual Online, you can compare the effects of market volatilities on Protech Mitra and Dunia Virtual 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 Protech Mitra with a short position of Dunia Virtual. Check out your portfolio center. Please also check ongoing floating volatility patterns of Protech Mitra and Dunia Virtual.
Diversification Opportunities for Protech Mitra and Dunia Virtual
-0.8 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Protech and Dunia is -0.8. Overlapping area represents the amount of risk that can be diversified away by holding Protech Mitra Perkasa and Dunia Virtual Online in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dunia Virtual Online and Protech Mitra 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 Protech Mitra Perkasa are associated (or correlated) with Dunia Virtual. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dunia Virtual Online has no effect on the direction of Protech Mitra i.e., Protech Mitra and Dunia Virtual go up and down completely randomly.
Pair Corralation between Protech Mitra and Dunia Virtual
Assuming the 90 days trading horizon Protech Mitra Perkasa is expected to under-perform the Dunia Virtual. But the stock apears to be less risky and, when comparing its historical volatility, Protech Mitra Perkasa is 1.81 times less risky than Dunia Virtual. The stock trades about -0.04 of its potential returns per unit of risk. The Dunia Virtual Online is currently generating about 0.27 of returns per unit of risk over similar time horizon. If you would invest 20,000 in Dunia Virtual Online on December 30, 2024 and sell it today you would earn a total of 25,400 from holding Dunia Virtual Online or generate 127.0% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Protech Mitra Perkasa vs. Dunia Virtual Online
Performance |
Timeline |
Protech Mitra Perkasa |
Dunia Virtual Online |
Protech Mitra and Dunia Virtual Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Protech Mitra and Dunia Virtual
The main advantage of trading using opposite Protech Mitra and Dunia Virtual positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Protech Mitra position performs unexpectedly, Dunia Virtual 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 Dunia Virtual will offset losses from the drop in Dunia Virtual's long position.Protech Mitra vs. Pelayaran Nelly Dwi | Protech Mitra vs. Trans Power Marine | Protech Mitra vs. Sidomulyo Selaras Tbk | Protech Mitra vs. Bali Towerindo Sentra |
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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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