Correlation Between Baytex Energy and ConocoPhillips
Can any of the company-specific risk be diversified away by investing in both Baytex Energy and ConocoPhillips 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 Baytex Energy and ConocoPhillips into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Baytex Energy Corp and ConocoPhillips, you can compare the effects of market volatilities on Baytex Energy and ConocoPhillips 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 Baytex Energy with a short position of ConocoPhillips. Check out your portfolio center. Please also check ongoing floating volatility patterns of Baytex Energy and ConocoPhillips.
Diversification Opportunities for Baytex Energy and ConocoPhillips
0.53 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Baytex and ConocoPhillips is 0.53. Overlapping area represents the amount of risk that can be diversified away by holding Baytex Energy Corp and ConocoPhillips in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on ConocoPhillips and Baytex Energy 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 Baytex Energy Corp are associated (or correlated) with ConocoPhillips. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of ConocoPhillips has no effect on the direction of Baytex Energy i.e., Baytex Energy and ConocoPhillips go up and down completely randomly.
Pair Corralation between Baytex Energy and ConocoPhillips
Considering the 90-day investment horizon Baytex Energy Corp is expected to under-perform the ConocoPhillips. In addition to that, Baytex Energy is 1.33 times more volatile than ConocoPhillips. It trades about -0.08 of its total potential returns per unit of risk. ConocoPhillips is currently generating about 0.0 per unit of volatility. If you would invest 10,909 in ConocoPhillips on August 31, 2024 and sell it today you would lose (170.00) from holding ConocoPhillips or give up 1.56% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Baytex Energy Corp vs. ConocoPhillips
Performance |
| Timeline |
| Baytex Energy Corp |
| ConocoPhillips |
Baytex Energy and ConocoPhillips Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Baytex Energy and ConocoPhillips
The main advantage of trading using opposite Baytex Energy and ConocoPhillips positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Baytex Energy position performs unexpectedly, ConocoPhillips 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 ConocoPhillips will offset losses from the drop in ConocoPhillips' long position.| Baytex Energy vs. Vermilion Energy | Baytex Energy vs. Obsidian Energy | Baytex Energy vs. Canadian Natural Resources | Baytex Energy vs. Ovintiv |
| ConocoPhillips vs. Diamondback Energy | ConocoPhillips vs. APA Corporation | ConocoPhillips vs. Hess Corporation | ConocoPhillips vs. Coterra Energy |
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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