Correlation Between Nusa Palapa and Imago Mulia
Can any of the company-specific risk be diversified away by investing in both Nusa Palapa and Imago Mulia 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 Nusa Palapa and Imago Mulia into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Nusa Palapa Gemilang and Imago Mulia Persada, you can compare the effects of market volatilities on Nusa Palapa and Imago Mulia 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 Nusa Palapa with a short position of Imago Mulia. Check out your portfolio center. Please also check ongoing floating volatility patterns of Nusa Palapa and Imago Mulia.
Diversification Opportunities for Nusa Palapa and Imago Mulia
-0.17 | Correlation Coefficient |
Good diversification
The 3 months correlation between Nusa and Imago is -0.17. Overlapping area represents the amount of risk that can be diversified away by holding Nusa Palapa Gemilang and Imago Mulia Persada in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Imago Mulia Persada and Nusa Palapa 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 Nusa Palapa Gemilang are associated (or correlated) with Imago Mulia. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Imago Mulia Persada has no effect on the direction of Nusa Palapa i.e., Nusa Palapa and Imago Mulia go up and down completely randomly.
Pair Corralation between Nusa Palapa and Imago Mulia
Assuming the 90 days trading horizon Nusa Palapa Gemilang is expected to under-perform the Imago Mulia. But the stock apears to be less risky and, when comparing its historical volatility, Nusa Palapa Gemilang is 1.11 times less risky than Imago Mulia. The stock trades about -0.03 of its potential returns per unit of risk. The Imago Mulia Persada is currently generating about 0.06 of returns per unit of risk over similar time horizon. If you would invest 4,706 in Imago Mulia Persada on September 2, 2024 and sell it today you would earn a total of 3,594 from holding Imago Mulia Persada or generate 76.37% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Nusa Palapa Gemilang vs. Imago Mulia Persada
Performance |
Timeline |
Nusa Palapa Gemilang |
Imago Mulia Persada |
Nusa Palapa and Imago Mulia Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Nusa Palapa and Imago Mulia
The main advantage of trading using opposite Nusa Palapa and Imago Mulia positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Nusa Palapa position performs unexpectedly, Imago Mulia 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 Imago Mulia will offset losses from the drop in Imago Mulia's long position.Nusa Palapa vs. Berkah Beton Sadaya | Nusa Palapa vs. Triputra Agro Persada | Nusa Palapa vs. PT Sunter Lakeside | Nusa Palapa vs. Ladangbaja Murni PT |
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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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