Correlation Between Saat Aggressive and Simt Sp
Can any of the company-specific risk be diversified away by investing in both Saat Aggressive 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 Saat Aggressive and Simt Sp into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Saat Aggressive Strategy and Simt Sp 500, you can compare the effects of market volatilities on Saat Aggressive 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 Saat Aggressive with a short position of Simt Sp. Check out your portfolio center. Please also check ongoing floating volatility patterns of Saat Aggressive and Simt Sp.
Diversification Opportunities for Saat Aggressive and Simt Sp
0.89 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Saat and Simt is 0.89. Overlapping area represents the amount of risk that can be diversified away by holding Saat Aggressive Strategy 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 Saat Aggressive 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 Saat Aggressive Strategy 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 Saat Aggressive i.e., Saat Aggressive and Simt Sp go up and down completely randomly.
Pair Corralation between Saat Aggressive and Simt Sp
Assuming the 90 days horizon Saat Aggressive is expected to generate 1.7 times less return on investment than Simt Sp. But when comparing it to its historical volatility, Saat Aggressive Strategy is 1.54 times less risky than Simt Sp. It trades about 0.14 of its potential returns per unit of risk. Simt Sp 500 is currently generating about 0.16 of returns per unit of risk over similar time horizon. If you would invest 10,484 in Simt Sp 500 on August 28, 2024 and sell it today you would earn a total of 302.00 from holding Simt Sp 500 or generate 2.88% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 95.45% |
| Values | Daily Returns |
Saat Aggressive Strategy vs. Simt Sp 500
Performance |
| Timeline |
| Saat Aggressive Strategy |
| Simt Sp 500 |
Saat Aggressive and Simt Sp Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Saat Aggressive and Simt Sp
The main advantage of trading using opposite Saat Aggressive and Simt Sp positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Saat Aggressive 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.| Saat Aggressive vs. Saat Market Growth | Saat Aggressive vs. Saat Moderate Strategy | Saat Aggressive vs. Saat Servative Strategy | Saat Aggressive vs. Simt Large Cap |
| Simt Sp vs. Simt Sp 500 | Simt Sp vs. Deutsche Sp 500 | Simt Sp vs. Siit Dynamic Asset | Simt Sp vs. Prudential Qma Stock |
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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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