Correlation Between PetroChina Company and Exxon Mobil
Can any of the company-specific risk be diversified away by investing in both PetroChina Company and Exxon Mobil 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 PetroChina Company and Exxon Mobil into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between PetroChina Company Limited and Exxon Mobil, you can compare the effects of market volatilities on PetroChina Company and Exxon Mobil 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 PetroChina Company with a short position of Exxon Mobil. Check out your portfolio center. Please also check ongoing floating volatility patterns of PetroChina Company and Exxon Mobil.
Diversification Opportunities for PetroChina Company and Exxon Mobil
0.43 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between PetroChina and Exxon is 0.43. Overlapping area represents the amount of risk that can be diversified away by holding PetroChina Company Limited and Exxon Mobil in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Exxon Mobil and PetroChina Company 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 PetroChina Company Limited are associated (or correlated) with Exxon Mobil. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Exxon Mobil has no effect on the direction of PetroChina Company i.e., PetroChina Company and Exxon Mobil go up and down completely randomly.
Pair Corralation between PetroChina Company and Exxon Mobil
Assuming the 90 days horizon PetroChina Company Limited is expected to under-perform the Exxon Mobil. In addition to that, PetroChina Company is 1.03 times more volatile than Exxon Mobil. It trades about -0.12 of its total potential returns per unit of risk. Exxon Mobil is currently generating about 0.12 per unit of volatility. If you would invest 10,743 in Exxon Mobil on September 1, 2024 and sell it today you would earn a total of 407.00 from holding Exxon Mobil or generate 3.79% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
PetroChina Company Limited vs. Exxon Mobil
Performance |
| Timeline |
| PetroChina Limited |
| Exxon Mobil |
PetroChina Company and Exxon Mobil Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with PetroChina Company and Exxon Mobil
The main advantage of trading using opposite PetroChina Company and Exxon Mobil positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if PetroChina Company position performs unexpectedly, Exxon Mobil 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 Exxon Mobil will offset losses from the drop in Exxon Mobil's long position.| PetroChina Company vs. Apple Inc | PetroChina Company vs. Apple Inc | PetroChina Company vs. Apple Inc | PetroChina Company vs. Apple Inc |
| Exxon Mobil vs. Apple Inc | Exxon Mobil vs. Apple Inc | Exxon Mobil vs. Apple Inc | Exxon Mobil vs. Apple 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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