Correlation Between Kolibri Global and China Southern
Can any of the company-specific risk be diversified away by investing in both Kolibri Global and China Southern 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 Kolibri Global and China Southern into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Kolibri Global Energy and China Southern Airlines, you can compare the effects of market volatilities on Kolibri Global and China Southern 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 Kolibri Global with a short position of China Southern. Check out your portfolio center. Please also check ongoing floating volatility patterns of Kolibri Global and China Southern.
Diversification Opportunities for Kolibri Global and China Southern
0.85 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Kolibri and China is 0.85. Overlapping area represents the amount of risk that can be diversified away by holding Kolibri Global Energy and China Southern Airlines in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on China Southern Airlines and Kolibri Global 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 Kolibri Global Energy are associated (or correlated) with China Southern. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of China Southern Airlines has no effect on the direction of Kolibri Global i.e., Kolibri Global and China Southern go up and down completely randomly.
Pair Corralation between Kolibri Global and China Southern
Given the investment horizon of 90 days Kolibri Global Energy is expected to generate 1.12 times more return on investment than China Southern. However, Kolibri Global is 1.12 times more volatile than China Southern Airlines. It trades about 0.31 of its potential returns per unit of risk. China Southern Airlines is currently generating about -0.18 per unit of risk. If you would invest 466.00 in Kolibri Global Energy on October 11, 2024 and sell it today you would earn a total of 132.00 from holding Kolibri Global Energy or generate 28.33% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Kolibri Global Energy vs. China Southern Airlines
Performance |
Timeline |
Kolibri Global Energy |
China Southern Airlines |
Kolibri Global and China Southern Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Kolibri Global and China Southern
The main advantage of trading using opposite Kolibri Global and China Southern positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Kolibri Global position performs unexpectedly, China Southern 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 China Southern will offset losses from the drop in China Southern's long position.Kolibri Global vs. China Southern Airlines | Kolibri Global vs. The Coca Cola | Kolibri Global vs. Compania Cervecerias Unidas | Kolibri Global vs. National Beverage Corp |
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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 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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