Correlation Between Finexia Financial and Collins Foods
Can any of the company-specific risk be diversified away by investing in both Finexia Financial and Collins Foods 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 Finexia Financial and Collins Foods into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Finexia Financial Group and Collins Foods, you can compare the effects of market volatilities on Finexia Financial and Collins Foods 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 Finexia Financial with a short position of Collins Foods. Check out your portfolio center. Please also check ongoing floating volatility patterns of Finexia Financial and Collins Foods.
Diversification Opportunities for Finexia Financial and Collins Foods
-0.09 | Correlation Coefficient |
Good diversification
The 3 months correlation between Finexia and Collins is -0.09. Overlapping area represents the amount of risk that can be diversified away by holding Finexia Financial Group and Collins Foods in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Collins Foods and Finexia Financial 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 Finexia Financial Group are associated (or correlated) with Collins Foods. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Collins Foods has no effect on the direction of Finexia Financial i.e., Finexia Financial and Collins Foods go up and down completely randomly.
Pair Corralation between Finexia Financial and Collins Foods
Assuming the 90 days trading horizon Finexia Financial Group is expected to generate 4.15 times more return on investment than Collins Foods. However, Finexia Financial is 4.15 times more volatile than Collins Foods. It trades about 0.27 of its potential returns per unit of risk. Collins Foods is currently generating about 0.07 per unit of risk. If you would invest 26.00 in Finexia Financial Group on August 28, 2024 and sell it today you would earn a total of 5.00 from holding Finexia Financial Group or generate 19.23% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Finexia Financial Group vs. Collins Foods
Performance |
Timeline |
Finexia Financial |
Collins Foods |
Finexia Financial and Collins Foods Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Finexia Financial and Collins Foods
The main advantage of trading using opposite Finexia Financial and Collins Foods positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Finexia Financial position performs unexpectedly, Collins Foods 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 Collins Foods will offset losses from the drop in Collins Foods' long position.Finexia Financial vs. oOhMedia | Finexia Financial vs. Charter Hall Retail | Finexia Financial vs. Dexus Convenience Retail | Finexia Financial vs. Nine Entertainment Co |
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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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