Correlation Between Scientific Games and Carnegie Clean
Can any of the company-specific risk be diversified away by investing in both Scientific Games and Carnegie Clean 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 Scientific Games and Carnegie Clean into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Scientific Games and Carnegie Clean Energy, you can compare the effects of market volatilities on Scientific Games and Carnegie Clean 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 Scientific Games with a short position of Carnegie Clean. Check out your portfolio center. Please also check ongoing floating volatility patterns of Scientific Games and Carnegie Clean.
Diversification Opportunities for Scientific Games and Carnegie Clean
0.28 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Scientific and Carnegie is 0.28. Overlapping area represents the amount of risk that can be diversified away by holding Scientific Games and Carnegie Clean Energy in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Carnegie Clean Energy and Scientific Games 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 Scientific Games are associated (or correlated) with Carnegie Clean. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Carnegie Clean Energy has no effect on the direction of Scientific Games i.e., Scientific Games and Carnegie Clean go up and down completely randomly.
Pair Corralation between Scientific Games and Carnegie Clean
Assuming the 90 days horizon Scientific Games is expected to generate 2.4 times less return on investment than Carnegie Clean. But when comparing it to its historical volatility, Scientific Games is 4.29 times less risky than Carnegie Clean. It trades about 0.09 of its potential returns per unit of risk. Carnegie Clean Energy is currently generating about 0.05 of returns per unit of risk over similar time horizon. If you would invest 2.04 in Carnegie Clean Energy on November 5, 2024 and sell it today you would earn a total of 0.06 from holding Carnegie Clean Energy or generate 2.94% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Scientific Games vs. Carnegie Clean Energy
Performance |
| Timeline |
| Scientific Games |
| Carnegie Clean Energy |
Scientific Games and Carnegie Clean Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Scientific Games and Carnegie Clean
The main advantage of trading using opposite Scientific Games and Carnegie Clean positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Scientific Games position performs unexpectedly, Carnegie Clean 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 Carnegie Clean will offset losses from the drop in Carnegie Clean's long position.| Scientific Games vs. IMPERIAL TOBACCO | Scientific Games vs. Universal Health Realty | Scientific Games vs. WESANA HEALTH HOLD | Scientific Games vs. alstria office REIT AG |
| Carnegie Clean vs. Transport International Holdings | Carnegie Clean vs. NTG Nordic Transport | Carnegie Clean vs. Guidewire Software | Carnegie Clean vs. Kingdee International Software |
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 My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.
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