Correlation Between Clean Energy and AMAG Austria
Can any of the company-specific risk be diversified away by investing in both Clean Energy and AMAG Austria 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 AMAG Austria 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 AMAG Austria Metall, you can compare the effects of market volatilities on Clean Energy and AMAG Austria 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 AMAG Austria. Check out your portfolio center. Please also check ongoing floating volatility patterns of Clean Energy and AMAG Austria.
Diversification Opportunities for Clean Energy and AMAG Austria
0.14 | Correlation Coefficient |
Average diversification
The 3 months correlation between Clean and AMAG is 0.14. Overlapping area represents the amount of risk that can be diversified away by holding Clean Energy Fuels and AMAG Austria Metall in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on AMAG Austria Metall 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 AMAG Austria. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of AMAG Austria Metall has no effect on the direction of Clean Energy i.e., Clean Energy and AMAG Austria go up and down completely randomly.
Pair Corralation between Clean Energy and AMAG Austria
Assuming the 90 days horizon Clean Energy Fuels is expected to generate 3.11 times more return on investment than AMAG Austria. However, Clean Energy is 3.11 times more volatile than AMAG Austria Metall. It trades about 0.23 of its potential returns per unit of risk. AMAG Austria Metall is currently generating about 0.03 per unit of risk. If you would invest 256.00 in Clean Energy Fuels on October 14, 2024 and sell it today you would earn a total of 35.00 from holding Clean Energy Fuels or generate 13.67% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Clean Energy Fuels vs. AMAG Austria Metall
Performance |
| Timeline |
| Clean Energy Fuels |
| AMAG Austria Metall |
Clean Energy and AMAG Austria Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Clean Energy and AMAG Austria
The main advantage of trading using opposite Clean Energy and AMAG Austria positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Clean Energy position performs unexpectedly, AMAG Austria 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 AMAG Austria will offset losses from the drop in AMAG Austria's long position.| Clean Energy vs. UPDATE SOFTWARE | Clean Energy vs. Goosehead Insurance | Clean Energy vs. Vishay Intertechnology | Clean Energy vs. INSURANCE AUST GRP |
| AMAG Austria vs. AEON STORES | AMAG Austria vs. CVW CLEANTECH INC | AMAG Austria vs. Clean Energy Fuels | AMAG Austria vs. BJs Wholesale Club |
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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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