Correlation Between Siit High and Fisher Investments
Can any of the company-specific risk be diversified away by investing in both Siit High and Fisher Investments 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 Siit High and Fisher Investments into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Siit High Yield and Fisher Large Cap, you can compare the effects of market volatilities on Siit High and Fisher Investments 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 Siit High with a short position of Fisher Investments. Check out your portfolio center. Please also check ongoing floating volatility patterns of Siit High and Fisher Investments.
Diversification Opportunities for Siit High and Fisher Investments
0.67 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Siit and Fisher is 0.67. Overlapping area represents the amount of risk that can be diversified away by holding Siit High Yield and Fisher Large Cap in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Fisher Investments and Siit High 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 Siit High Yield are associated (or correlated) with Fisher Investments. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Fisher Investments has no effect on the direction of Siit High i.e., Siit High and Fisher Investments go up and down completely randomly.
Pair Corralation between Siit High and Fisher Investments
Assuming the 90 days horizon Siit High Yield is expected to generate 0.16 times more return on investment than Fisher Investments. However, Siit High Yield is 6.34 times less risky than Fisher Investments. It trades about -0.31 of its potential returns per unit of risk. Fisher Large Cap is currently generating about -0.26 per unit of risk. If you would invest 720.00 in Siit High Yield on October 11, 2024 and sell it today you would lose (7.00) from holding Siit High Yield or give up 0.97% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Siit High Yield vs. Fisher Large Cap
Performance |
| Timeline |
| Siit High Yield |
| Fisher Investments |
Siit High and Fisher Investments Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Siit High and Fisher Investments
The main advantage of trading using opposite Siit High and Fisher Investments positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Siit High position performs unexpectedly, Fisher Investments 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 Fisher Investments will offset losses from the drop in Fisher Investments' long position.| Siit High vs. Oberweis Emerging Growth | Siit High vs. Mid Cap 15x Strategy | Siit High vs. Nasdaq 100 2x Strategy | Siit High vs. Nasdaq 100 2x Strategy |
| Fisher Investments vs. Ab High Income | Fisher Investments vs. Ab High Income | Fisher Investments vs. Catalystsmh High Income | Fisher Investments vs. Siit High Yield |
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 Insider Screener module to find insiders across different sectors to evaluate their impact on performance.
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