Correlation Between Eli Lilly and Chongqing Machinery
Can any of the company-specific risk be diversified away by investing in both Eli Lilly and Chongqing Machinery 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 Eli Lilly and Chongqing Machinery into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Eli Lilly and and Chongqing Machinery Electric, you can compare the effects of market volatilities on Eli Lilly and Chongqing Machinery 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 Eli Lilly with a short position of Chongqing Machinery. Check out your portfolio center. Please also check ongoing floating volatility patterns of Eli Lilly and Chongqing Machinery.
Diversification Opportunities for Eli Lilly and Chongqing Machinery
0.27 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Eli and Chongqing is 0.27. Overlapping area represents the amount of risk that can be diversified away by holding Eli Lilly and and Chongqing Machinery Electric in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Chongqing Machinery and Eli Lilly 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 Eli Lilly and are associated (or correlated) with Chongqing Machinery. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Chongqing Machinery has no effect on the direction of Eli Lilly i.e., Eli Lilly and Chongqing Machinery go up and down completely randomly.
Pair Corralation between Eli Lilly and Chongqing Machinery
Assuming the 90 days trading horizon Eli Lilly is expected to generate 23.34 times less return on investment than Chongqing Machinery. But when comparing it to its historical volatility, Eli Lilly and is 6.24 times less risky than Chongqing Machinery. It trades about 0.03 of its potential returns per unit of risk. Chongqing Machinery Electric is currently generating about 0.13 of returns per unit of risk over similar time horizon. If you would invest 7.90 in Chongqing Machinery Electric on December 20, 2024 and sell it today you would earn a total of 5.10 from holding Chongqing Machinery Electric or generate 64.56% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Eli Lilly and vs. Chongqing Machinery Electric
Performance |
Timeline |
Eli Lilly |
Chongqing Machinery |
Eli Lilly and Chongqing Machinery Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Eli Lilly and Chongqing Machinery
The main advantage of trading using opposite Eli Lilly and Chongqing Machinery positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Eli Lilly position performs unexpectedly, Chongqing Machinery 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 Chongqing Machinery will offset losses from the drop in Chongqing Machinery's long position.Eli Lilly vs. ETFS Coffee ETC | Eli Lilly vs. MAANSHAN IRON H | Eli Lilly vs. SWISS WATER DECAFFCOFFEE | Eli Lilly vs. CODERE ONLINE LUX |
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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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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