Correlation Between Aluminumof China and CITY OFFICE
Can any of the company-specific risk be diversified away by investing in both Aluminumof China and CITY OFFICE 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 Aluminumof China and CITY OFFICE into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Aluminum of and CITY OFFICE REIT, you can compare the effects of market volatilities on Aluminumof China and CITY OFFICE 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 Aluminumof China with a short position of CITY OFFICE. Check out your portfolio center. Please also check ongoing floating volatility patterns of Aluminumof China and CITY OFFICE.
Diversification Opportunities for Aluminumof China and CITY OFFICE
-0.02 | Correlation Coefficient |
Good diversification
The 3 months correlation between Aluminumof and CITY is -0.02. Overlapping area represents the amount of risk that can be diversified away by holding Aluminum of and CITY OFFICE REIT in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on CITY OFFICE REIT and Aluminumof China 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 Aluminum of are associated (or correlated) with CITY OFFICE. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of CITY OFFICE REIT has no effect on the direction of Aluminumof China i.e., Aluminumof China and CITY OFFICE go up and down completely randomly.
Pair Corralation between Aluminumof China and CITY OFFICE
Assuming the 90 days horizon Aluminum of is expected to generate 1.04 times more return on investment than CITY OFFICE. However, Aluminumof China is 1.04 times more volatile than CITY OFFICE REIT. It trades about 0.07 of its potential returns per unit of risk. CITY OFFICE REIT is currently generating about 0.04 per unit of risk. If you would invest 28.00 in Aluminum of on September 1, 2024 and sell it today you would earn a total of 28.00 from holding Aluminum of or generate 100.0% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Aluminum of vs. CITY OFFICE REIT
Performance |
| Timeline |
| Aluminumof China |
| CITY OFFICE REIT |
Aluminumof China and CITY OFFICE Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Aluminumof China and CITY OFFICE
The main advantage of trading using opposite Aluminumof China and CITY OFFICE positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Aluminumof China position performs unexpectedly, CITY OFFICE 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 CITY OFFICE will offset losses from the drop in CITY OFFICE's long position.| Aluminumof China vs. PLAYTIKA HOLDING DL 01 | Aluminumof China vs. COSMOSTEEL HLDGS | Aluminumof China vs. Daido Steel Co | Aluminumof China vs. BLUESCOPE STEEL |
| CITY OFFICE vs. QINGCI GAMES INC | CITY OFFICE vs. ANGLER GAMING PLC | CITY OFFICE vs. GAMESTOP | CITY OFFICE vs. Games Workshop Group |
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 Analyst Advice module to analyst recommendations and target price estimates broken down by several categories.
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