Correlation Between Vale Indonesia and Jakarta Int
Can any of the company-specific risk be diversified away by investing in both Vale Indonesia and Jakarta Int 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 Vale Indonesia and Jakarta Int into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Vale Indonesia Tbk and Jakarta Int Hotels, you can compare the effects of market volatilities on Vale Indonesia and Jakarta Int 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 Vale Indonesia with a short position of Jakarta Int. Check out your portfolio center. Please also check ongoing floating volatility patterns of Vale Indonesia and Jakarta Int.
Diversification Opportunities for Vale Indonesia and Jakarta Int
-0.47 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Vale and Jakarta is -0.47. Overlapping area represents the amount of risk that can be diversified away by holding Vale Indonesia Tbk and Jakarta Int Hotels in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Jakarta Int Hotels and Vale Indonesia 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 Vale Indonesia Tbk are associated (or correlated) with Jakarta Int. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Jakarta Int Hotels has no effect on the direction of Vale Indonesia i.e., Vale Indonesia and Jakarta Int go up and down completely randomly.
Pair Corralation between Vale Indonesia and Jakarta Int
Assuming the 90 days trading horizon Vale Indonesia Tbk is expected to under-perform the Jakarta Int. But the stock apears to be less risky and, when comparing its historical volatility, Vale Indonesia Tbk is 6.97 times less risky than Jakarta Int. The stock trades about -0.16 of its potential returns per unit of risk. The Jakarta Int Hotels is currently generating about 0.56 of returns per unit of risk over similar time horizon. If you would invest 95,000 in Jakarta Int Hotels on September 2, 2024 and sell it today you would earn a total of 202,000 from holding Jakarta Int Hotels or generate 212.63% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Vale Indonesia Tbk vs. Jakarta Int Hotels
Performance |
Timeline |
Vale Indonesia Tbk |
Jakarta Int Hotels |
Vale Indonesia and Jakarta Int Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Vale Indonesia and Jakarta Int
The main advantage of trading using opposite Vale Indonesia and Jakarta Int positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Vale Indonesia position performs unexpectedly, Jakarta Int 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 Jakarta Int will offset losses from the drop in Jakarta Int's long position.Vale Indonesia vs. Perusahaan Gas Negara | Vale Indonesia vs. Telkom Indonesia Tbk | Vale Indonesia vs. Mitra Pinasthika Mustika | Vale Indonesia vs. Jakarta Int Hotels |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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