Correlation Between Financial Industries and Catalyst/smh High
Can any of the company-specific risk be diversified away by investing in both Financial Industries and Catalyst/smh High 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 Financial Industries and Catalyst/smh High into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Financial Industries Fund and Catalystsmh High Income, you can compare the effects of market volatilities on Financial Industries and Catalyst/smh High 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 Financial Industries with a short position of Catalyst/smh High. Check out your portfolio center. Please also check ongoing floating volatility patterns of Financial Industries and Catalyst/smh High.
Diversification Opportunities for Financial Industries and Catalyst/smh High
0.73 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Financial and Catalyst/smh is 0.73. Overlapping area represents the amount of risk that can be diversified away by holding Financial Industries Fund and Catalystsmh High Income in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Catalystsmh High Income and Financial Industries 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 Financial Industries Fund are associated (or correlated) with Catalyst/smh High. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Catalystsmh High Income has no effect on the direction of Financial Industries i.e., Financial Industries and Catalyst/smh High go up and down completely randomly.
Pair Corralation between Financial Industries and Catalyst/smh High
Assuming the 90 days horizon Financial Industries is expected to generate 3.57 times less return on investment than Catalyst/smh High. In addition to that, Financial Industries is 1.73 times more volatile than Catalystsmh High Income. It trades about 0.05 of its total potential returns per unit of risk. Catalystsmh High Income is currently generating about 0.3 per unit of volatility. If you would invest 347.00 in Catalystsmh High Income on May 8, 2025 and sell it today you would earn a total of 33.00 from holding Catalystsmh High Income or generate 9.51% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Financial Industries Fund vs. Catalystsmh High Income
Performance |
Timeline |
Financial Industries |
Catalystsmh High Income |
Financial Industries and Catalyst/smh High Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Financial Industries and Catalyst/smh High
The main advantage of trading using opposite Financial Industries and Catalyst/smh High positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Financial Industries position performs unexpectedly, Catalyst/smh High 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 Catalyst/smh High will offset losses from the drop in Catalyst/smh High's long position.Financial Industries vs. Alpine Ultra Short | Financial Industries vs. Aig Government Money | Financial Industries vs. Lord Abbett Intermediate | Financial Industries vs. Gamco Global Telecommunications |
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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 Exposure Probability module to analyze equity upside and downside potential for a given time horizon across multiple markets.
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