Correlation Between Jakarta Int and Panca Budi
Can any of the company-specific risk be diversified away by investing in both Jakarta Int and Panca Budi 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 Jakarta Int and Panca Budi into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Jakarta Int Hotels and Panca Budi Idaman, you can compare the effects of market volatilities on Jakarta Int and Panca Budi 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 Jakarta Int with a short position of Panca Budi. Check out your portfolio center. Please also check ongoing floating volatility patterns of Jakarta Int and Panca Budi.
Diversification Opportunities for Jakarta Int and Panca Budi
0.73 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Jakarta and Panca is 0.73. Overlapping area represents the amount of risk that can be diversified away by holding Jakarta Int Hotels and Panca Budi Idaman in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Panca Budi Idaman and Jakarta Int 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 Jakarta Int Hotels are associated (or correlated) with Panca Budi. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Panca Budi Idaman has no effect on the direction of Jakarta Int i.e., Jakarta Int and Panca Budi go up and down completely randomly.
Pair Corralation between Jakarta Int and Panca Budi
Assuming the 90 days trading horizon Jakarta Int Hotels is expected to generate 4.43 times more return on investment than Panca Budi. However, Jakarta Int is 4.43 times more volatile than Panca Budi Idaman. It trades about 0.58 of its potential returns per unit of risk. Panca Budi Idaman is currently generating about -0.01 per unit of risk. If you would invest 95,000 in Jakarta Int Hotels on September 3, 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 Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Jakarta Int Hotels vs. Panca Budi Idaman
Performance |
| Timeline |
| Jakarta Int Hotels |
| Panca Budi Idaman |
Jakarta Int and Panca Budi Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Jakarta Int and Panca Budi
The main advantage of trading using opposite Jakarta Int and Panca Budi positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Jakarta Int position performs unexpectedly, Panca Budi 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 Panca Budi will offset losses from the drop in Panca Budi's long position.| Jakarta Int vs. Mitra Pinasthika Mustika | Jakarta Int vs. Asuransi Harta Aman | Jakarta Int vs. Indosterling Technomedia Tbk | Jakarta Int vs. Indosat Tbk |
| Panca Budi vs. Timah Persero Tbk | Panca Budi vs. Semen Indonesia Persero | Panca Budi vs. Mitra Pinasthika Mustika | Panca Budi vs. Jakarta Int Hotels |
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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