Correlation Between BP Plc and PetroChina Company
Can any of the company-specific risk be diversified away by investing in both BP Plc and PetroChina Company 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 BP Plc and PetroChina Company into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between BP plc and PetroChina Company Limited, you can compare the effects of market volatilities on BP Plc and PetroChina Company 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 BP Plc with a short position of PetroChina Company. Check out your portfolio center. Please also check ongoing floating volatility patterns of BP Plc and PetroChina Company.
Diversification Opportunities for BP Plc and PetroChina Company
0.61 | Correlation Coefficient |
Poor diversification
The 3 months correlation between BPE5 and PetroChina is 0.61. Overlapping area represents the amount of risk that can be diversified away by holding BP plc and PetroChina Company Limited in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on PetroChina Limited and BP Plc 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 BP plc are associated (or correlated) with PetroChina Company. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of PetroChina Limited has no effect on the direction of BP Plc i.e., BP Plc and PetroChina Company go up and down completely randomly.
Pair Corralation between BP Plc and PetroChina Company
Assuming the 90 days trading horizon BP plc is expected to generate 0.99 times more return on investment than PetroChina Company. However, BP plc is 1.01 times less risky than PetroChina Company. It trades about 0.17 of its potential returns per unit of risk. PetroChina Company Limited is currently generating about -0.07 per unit of risk. If you would invest 480.00 in BP plc on December 1, 2024 and sell it today you would earn a total of 55.00 from holding BP plc or generate 11.46% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
BP plc vs. PetroChina Company Limited
Performance |
| Timeline |
| BP plc |
| PetroChina Limited |
BP Plc and PetroChina Company Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with BP Plc and PetroChina Company
The main advantage of trading using opposite BP Plc and PetroChina Company positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if BP Plc position performs unexpectedly, PetroChina Company 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 PetroChina Company will offset losses from the drop in PetroChina Company's long position.| BP Plc vs. Q2M Managementberatung AG | BP Plc vs. Data Modul AG | BP Plc vs. Linedata Services SA | BP Plc vs. Information Services International Dentsu |
| PetroChina Company vs. CENTURIA OFFICE REIT | PetroChina Company vs. AEON METALS LTD | PetroChina Company vs. ADRIATIC METALS LS 013355 | PetroChina Company vs. Cleanaway Waste Management |
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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