Correlation Between Clean Energy and BURLINGTON STORES
Can any of the company-specific risk be diversified away by investing in both Clean Energy and BURLINGTON STORES 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 Clean Energy and BURLINGTON STORES into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Clean Energy Fuels and BURLINGTON STORES, you can compare the effects of market volatilities on Clean Energy and BURLINGTON STORES 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 Clean Energy with a short position of BURLINGTON STORES. Check out your portfolio center. Please also check ongoing floating volatility patterns of Clean Energy and BURLINGTON STORES.
Diversification Opportunities for Clean Energy and BURLINGTON STORES
0.28 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Clean and BURLINGTON is 0.28. Overlapping area represents the amount of risk that can be diversified away by holding Clean Energy Fuels and BURLINGTON STORES in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on BURLINGTON STORES and Clean 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 Clean Energy Fuels are associated (or correlated) with BURLINGTON STORES. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of BURLINGTON STORES has no effect on the direction of Clean Energy i.e., Clean Energy and BURLINGTON STORES go up and down completely randomly.
Pair Corralation between Clean Energy and BURLINGTON STORES
Assuming the 90 days horizon Clean Energy is expected to generate 1.14 times less return on investment than BURLINGTON STORES. In addition to that, Clean Energy is 2.06 times more volatile than BURLINGTON STORES. It trades about 0.06 of its total potential returns per unit of risk. BURLINGTON STORES is currently generating about 0.14 per unit of volatility. If you would invest 17,200 in BURLINGTON STORES on September 3, 2024 and sell it today you would earn a total of 10,000 from holding BURLINGTON STORES or generate 58.14% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Clean Energy Fuels vs. BURLINGTON STORES
Performance |
| Timeline |
| Clean Energy Fuels |
| BURLINGTON STORES |
Clean Energy and BURLINGTON STORES Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Clean Energy and BURLINGTON STORES
The main advantage of trading using opposite Clean Energy and BURLINGTON STORES positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Clean Energy position performs unexpectedly, BURLINGTON STORES 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 BURLINGTON STORES will offset losses from the drop in BURLINGTON STORES's long position.| Clean Energy vs. Marathon Petroleum Corp | Clean Energy vs. Neste Oyj | Clean Energy vs. ENEOS Holdings | Clean Energy vs. PTT OILRETBUS FOR BA10 |
| BURLINGTON STORES vs. ULTRA CLEAN HLDGS | BURLINGTON STORES vs. Clean Energy Fuels | BURLINGTON STORES vs. COSTCO WHOLESALE CDR | BURLINGTON STORES vs. PICKN PAY STORES |
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 Volatility Analysis module to get historical volatility and risk analysis based on latest market data.
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