Correlation Between Geely Automobile and PT Bank
Can any of the company-specific risk be diversified away by investing in both Geely Automobile and PT Bank 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 Geely Automobile and PT Bank into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Geely Automobile Holdings and PT Bank Central, you can compare the effects of market volatilities on Geely Automobile and PT Bank 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 Geely Automobile with a short position of PT Bank. Check out your portfolio center. Please also check ongoing floating volatility patterns of Geely Automobile and PT Bank.
Diversification Opportunities for Geely Automobile and PT Bank
0.13 | Correlation Coefficient |
Average diversification
The 3 months correlation between Geely and BZG2 is 0.13. Overlapping area represents the amount of risk that can be diversified away by holding Geely Automobile Holdings and PT Bank Central in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on PT Bank Central and Geely Automobile 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 Geely Automobile Holdings are associated (or correlated) with PT Bank. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of PT Bank Central has no effect on the direction of Geely Automobile i.e., Geely Automobile and PT Bank go up and down completely randomly.
Pair Corralation between Geely Automobile and PT Bank
Assuming the 90 days horizon Geely Automobile Holdings is expected to generate 1.13 times more return on investment than PT Bank. However, Geely Automobile is 1.13 times more volatile than PT Bank Central. It trades about 0.2 of its potential returns per unit of risk. PT Bank Central is currently generating about 0.02 per unit of risk. If you would invest 99.00 in Geely Automobile Holdings on August 29, 2024 and sell it today you would earn a total of 59.00 from holding Geely Automobile Holdings or generate 59.6% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 98.46% |
| Values | Daily Returns |
Geely Automobile Holdings vs. PT Bank Central
Performance |
| Timeline |
| Geely Automobile Holdings |
| PT Bank Central |
Geely Automobile and PT Bank Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Geely Automobile and PT Bank
The main advantage of trading using opposite Geely Automobile and PT Bank positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Geely Automobile position performs unexpectedly, PT Bank 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 PT Bank will offset losses from the drop in PT Bank's long position.| Geely Automobile vs. STORE ELECTRONIC | Geely Automobile vs. BYD ELECTRONIC | Geely Automobile vs. Arrow Electronics | Geely Automobile vs. PennantPark Investment |
| PT Bank vs. BURLINGTON STORES | PT Bank vs. MeVis Medical Solutions | PT Bank vs. BJs Wholesale Club | PT Bank vs. QURATE RETAIL INC |
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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