Correlation Between City Union and Gokul Refoils
Can any of the company-specific risk be diversified away by investing in both City Union and Gokul Refoils 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 City Union and Gokul Refoils into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between City Union Bank and Gokul Refoils and, you can compare the effects of market volatilities on City Union and Gokul Refoils 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 City Union with a short position of Gokul Refoils. Check out your portfolio center. Please also check ongoing floating volatility patterns of City Union and Gokul Refoils.
Diversification Opportunities for City Union and Gokul Refoils
0.56 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between City and Gokul is 0.56. Overlapping area represents the amount of risk that can be diversified away by holding City Union Bank and Gokul Refoils and in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Gokul Refoils and City Union 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 City Union Bank are associated (or correlated) with Gokul Refoils. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Gokul Refoils has no effect on the direction of City Union i.e., City Union and Gokul Refoils go up and down completely randomly.
Pair Corralation between City Union and Gokul Refoils
Assuming the 90 days trading horizon City Union is expected to generate 1.82 times less return on investment than Gokul Refoils. But when comparing it to its historical volatility, City Union Bank is 1.67 times less risky than Gokul Refoils. It trades about 0.07 of its potential returns per unit of risk. Gokul Refoils and is currently generating about 0.08 of returns per unit of risk over similar time horizon. If you would invest 5,008 in Gokul Refoils and on September 4, 2024 and sell it today you would earn a total of 761.00 from holding Gokul Refoils and or generate 15.2% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 98.41% |
| Values | Daily Returns |
City Union Bank vs. Gokul Refoils and
Performance |
| Timeline |
| City Union Bank |
| Gokul Refoils |
City Union and Gokul Refoils Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with City Union and Gokul Refoils
The main advantage of trading using opposite City Union and Gokul Refoils positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if City Union position performs unexpectedly, Gokul Refoils 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 Gokul Refoils will offset losses from the drop in Gokul Refoils' long position.| City Union vs. Gokul Refoils and | City Union vs. Metalyst Forgings Limited | City Union vs. Nahar Industrial Enterprises | City Union vs. Manaksia Coated Metals |
| Gokul Refoils vs. Compucom Software Limited | Gokul Refoils vs. Paramount Communications Limited | Gokul Refoils vs. Home First Finance | Gokul Refoils vs. Life Insurance |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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