Correlation Between Caterpillar and Global Energy
Can any of the company-specific risk be diversified away by investing in both Caterpillar and Global Energy 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 Caterpillar and Global Energy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Caterpillar and Global Energy Metals, you can compare the effects of market volatilities on Caterpillar and Global Energy 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 Caterpillar with a short position of Global Energy. Check out your portfolio center. Please also check ongoing floating volatility patterns of Caterpillar and Global Energy.
Diversification Opportunities for Caterpillar and Global Energy
-0.67 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Caterpillar and Global is -0.67. Overlapping area represents the amount of risk that can be diversified away by holding Caterpillar and Global Energy Metals in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Global Energy Metals and Caterpillar 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 Caterpillar are associated (or correlated) with Global Energy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Global Energy Metals has no effect on the direction of Caterpillar i.e., Caterpillar and Global Energy go up and down completely randomly.
Pair Corralation between Caterpillar and Global Energy
Considering the 90-day investment horizon Caterpillar is expected to generate 1.41 times less return on investment than Global Energy. But when comparing it to its historical volatility, Caterpillar is 5.35 times less risky than Global Energy. It trades about 0.16 of its potential returns per unit of risk. Global Energy Metals is currently generating about 0.04 of returns per unit of risk over similar time horizon. If you would invest 1.28 in Global Energy Metals on September 1, 2024 and sell it today you would lose (0.05) from holding Global Energy Metals or give up 3.91% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Weak |
| Accuracy | 95.45% |
| Values | Daily Returns |
Caterpillar vs. Global Energy Metals
Performance |
| Timeline |
| Caterpillar |
| Global Energy Metals |
Caterpillar and Global Energy Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Caterpillar and Global Energy
The main advantage of trading using opposite Caterpillar and Global Energy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Caterpillar position performs unexpectedly, Global Energy 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 Global Energy will offset losses from the drop in Global Energy's long position.| Caterpillar vs. AGCO Corporation | Caterpillar vs. Nikola Corp | Caterpillar vs. PACCAR Inc | Caterpillar vs. Deere Company |
| Global Energy vs. ATT Inc | Global Energy vs. Merck Company | Global Energy vs. Walt Disney | Global Energy vs. Caterpillar |
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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