Correlation Between Stet California and Simt Sp
Can any of the company-specific risk be diversified away by investing in both Stet California and Simt Sp 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 Simt Sp 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 Simt Sp 500, you can compare the effects of market volatilities on Stet California and Simt Sp 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 Simt Sp. Check out your portfolio center. Please also check ongoing floating volatility patterns of Stet California and Simt Sp.
Diversification Opportunities for Stet California and Simt Sp
-0.42 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Stet and Simt is -0.42. Overlapping area represents the amount of risk that can be diversified away by holding Stet California Municipal and Simt Sp 500 in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Simt Sp 500 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 Simt Sp. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Simt Sp 500 has no effect on the direction of Stet California i.e., Stet California and Simt Sp go up and down completely randomly.
Pair Corralation between Stet California and Simt Sp
Assuming the 90 days horizon Stet California is expected to generate 7.21 times less return on investment than Simt Sp. But when comparing it to its historical volatility, Stet California Municipal is 4.18 times less risky than Simt Sp. It trades about 0.07 of its potential returns per unit of risk. Simt Sp 500 is currently generating about 0.12 of returns per unit of risk over similar time horizon. If you would invest 7,782 in Simt Sp 500 on August 31, 2024 and sell it today you would earn a total of 2,995 from holding Simt Sp 500 or generate 38.49% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 99.73% |
| Values | Daily Returns |
Stet California Municipal vs. Simt Sp 500
Performance |
| Timeline |
| Stet California Municipal |
| Simt Sp 500 |
Stet California and Simt Sp Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Stet California and Simt Sp
The main advantage of trading using opposite Stet California and Simt Sp positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Stet California position performs unexpectedly, Simt Sp 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 Simt Sp will offset losses from the drop in Simt Sp's long position.| Stet California vs. Tiaa Cref Lifestyle Moderate | Stet California vs. Fidelity Managed Retirement | Stet California vs. Pro Blend Moderate Term | Stet California vs. Lifestyle Ii Moderate |
| Simt Sp vs. Simt Small Cap | Simt Sp vs. Simt Small Cap | Simt Sp vs. Simt Large Cap | Simt Sp vs. Sit International Equity |
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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