Correlation Between Stet California and Sdit Gnma
Can any of the company-specific risk be diversified away by investing in both Stet California and Sdit Gnma 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 Stet California and Sdit Gnma into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Stet California Municipal and Sdit Gnma Fund, you can compare the effects of market volatilities on Stet California and Sdit Gnma 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 Stet California with a short position of Sdit Gnma. Check out your portfolio center. Please also check ongoing floating volatility patterns of Stet California and Sdit Gnma.
Diversification Opportunities for Stet California and Sdit Gnma
0.8 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Stet and Sdit is 0.8. Overlapping area represents the amount of risk that can be diversified away by holding Stet California Municipal and Sdit Gnma Fund in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Sdit Gnma Fund and Stet California 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 Stet California Municipal are associated (or correlated) with Sdit Gnma. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Sdit Gnma Fund has no effect on the direction of Stet California i.e., Stet California and Sdit Gnma go up and down completely randomly.
Pair Corralation between Stet California and Sdit Gnma
Assuming the 90 days horizon Stet California Municipal is expected to generate 0.63 times more return on investment than Sdit Gnma. However, Stet California Municipal is 1.6 times less risky than Sdit Gnma. It trades about 0.15 of its potential returns per unit of risk. Sdit Gnma Fund is currently generating about 0.09 per unit of risk. If you would invest 990.00 in Stet California Municipal on September 1, 2024 and sell it today you would earn a total of 37.00 from holding Stet California Municipal or generate 3.74% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Stet California Municipal vs. Sdit Gnma Fund
Performance |
| Timeline |
| Stet California Municipal |
| Sdit Gnma Fund |
Stet California and Sdit Gnma Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Stet California and Sdit Gnma
The main advantage of trading using opposite Stet California and Sdit Gnma positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Stet California position performs unexpectedly, Sdit Gnma 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 Sdit Gnma will offset losses from the drop in Sdit Gnma's long position.| Stet California vs. Champlain Small | Stet California vs. Ab Small Cap | Stet California vs. Baird Smallmid Cap | Stet California vs. Tax Managed Mid Small |
| Sdit Gnma vs. Simt Multi Asset Accumulation | Sdit Gnma vs. Saat Market Growth | Sdit Gnma vs. Simt Real Return | Sdit Gnma vs. Simt Small Cap |
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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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