Correlation Between SentinelOne and Putnam Floating
Can any of the company-specific risk be diversified away by investing in both SentinelOne and Putnam Floating 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 SentinelOne and Putnam Floating into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between SentinelOne and Putnam Floating Rate, you can compare the effects of market volatilities on SentinelOne and Putnam Floating 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 SentinelOne with a short position of Putnam Floating. Check out your portfolio center. Please also check ongoing floating volatility patterns of SentinelOne and Putnam Floating.
Diversification Opportunities for SentinelOne and Putnam Floating
0.14 | Correlation Coefficient |
Average diversification
The 3 months correlation between SentinelOne and Putnam is 0.14. Overlapping area represents the amount of risk that can be diversified away by holding SentinelOne and Putnam Floating Rate in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Putnam Floating Rate and SentinelOne 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 SentinelOne are associated (or correlated) with Putnam Floating. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Putnam Floating Rate has no effect on the direction of SentinelOne i.e., SentinelOne and Putnam Floating go up and down completely randomly.
Pair Corralation between SentinelOne and Putnam Floating
Taking into account the 90-day investment horizon SentinelOne is expected to generate 20.63 times more return on investment than Putnam Floating. However, SentinelOne is 20.63 times more volatile than Putnam Floating Rate. It trades about 0.05 of its potential returns per unit of risk. Putnam Floating Rate is currently generating about 0.19 per unit of risk. If you would invest 1,524 in SentinelOne on August 29, 2024 and sell it today you would earn a total of 1,284 from holding SentinelOne or generate 84.25% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
SentinelOne vs. Putnam Floating Rate
Performance |
| Timeline |
| SentinelOne |
| Putnam Floating Rate |
SentinelOne and Putnam Floating Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with SentinelOne and Putnam Floating
The main advantage of trading using opposite SentinelOne and Putnam Floating positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if SentinelOne position performs unexpectedly, Putnam Floating 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 Putnam Floating will offset losses from the drop in Putnam Floating's long position.| SentinelOne vs. Crowdstrike Holdings | SentinelOne vs. Okta Inc | SentinelOne vs. Cloudflare | SentinelOne vs. MongoDB |
| Putnam Floating vs. Kinetics Market Opportunities | Putnam Floating vs. Barings Active Short | Putnam Floating vs. Versatile Bond Portfolio | Putnam Floating vs. Mirova Global Green |
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 Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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