Correlation Between Bukaka Teknik and Link Net
Can any of the company-specific risk be diversified away by investing in both Bukaka Teknik and Link Net 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 Bukaka Teknik and Link Net into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bukaka Teknik Utama and Link Net Tbk, you can compare the effects of market volatilities on Bukaka Teknik and Link Net 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 Bukaka Teknik with a short position of Link Net. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bukaka Teknik and Link Net.
Diversification Opportunities for Bukaka Teknik and Link Net
-0.14 | Correlation Coefficient |
Good diversification
The 3 months correlation between Bukaka and Link is -0.14. Overlapping area represents the amount of risk that can be diversified away by holding Bukaka Teknik Utama and Link Net Tbk in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Link Net Tbk and Bukaka Teknik 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 Bukaka Teknik Utama are associated (or correlated) with Link Net. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Link Net Tbk has no effect on the direction of Bukaka Teknik i.e., Bukaka Teknik and Link Net go up and down completely randomly.
Pair Corralation between Bukaka Teknik and Link Net
Assuming the 90 days trading horizon Bukaka Teknik Utama is expected to under-perform the Link Net. But the stock apears to be less risky and, when comparing its historical volatility, Bukaka Teknik Utama is 5.09 times less risky than Link Net. The stock trades about -0.1 of its potential returns per unit of risk. The Link Net Tbk is currently generating about 0.45 of returns per unit of risk over similar time horizon. If you would invest 121,000 in Link Net Tbk on November 3, 2024 and sell it today you would earn a total of 129,000 from holding Link Net Tbk or generate 106.61% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Bukaka Teknik Utama vs. Link Net Tbk
Performance |
| Timeline |
| Bukaka Teknik Utama |
| Link Net Tbk |
Bukaka Teknik and Link Net Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Bukaka Teknik and Link Net
The main advantage of trading using opposite Bukaka Teknik and Link Net positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bukaka Teknik position performs unexpectedly, Link Net 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 Link Net will offset losses from the drop in Link Net's long position.| Bukaka Teknik vs. Indo Kordsa Tbk | Bukaka Teknik vs. Wilmar Cahaya Indonesia | Bukaka Teknik vs. Citra Marga Nusaphala | Bukaka Teknik vs. Darya Varia Laboratoria Tbk |
| Link Net vs. Mitra Keluarga Karyasehat | Link Net vs. Surya Citra Media | Link Net vs. Matahari Department Store | Link Net vs. Puradelta Lestari PT |
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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