Correlation Between NorthWestern and Siriuspoint
Can any of the company-specific risk be diversified away by investing in both NorthWestern and Siriuspoint 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 NorthWestern and Siriuspoint into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between NorthWestern and Siriuspoint, you can compare the effects of market volatilities on NorthWestern and Siriuspoint 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 NorthWestern with a short position of Siriuspoint. Check out your portfolio center. Please also check ongoing floating volatility patterns of NorthWestern and Siriuspoint.
Diversification Opportunities for NorthWestern and Siriuspoint
0.19 | Correlation Coefficient |
Average diversification
The 3 months correlation between NorthWestern and Siriuspoint is 0.19. Overlapping area represents the amount of risk that can be diversified away by holding NorthWestern and Siriuspoint in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Siriuspoint and NorthWestern 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 NorthWestern are associated (or correlated) with Siriuspoint. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Siriuspoint has no effect on the direction of NorthWestern i.e., NorthWestern and Siriuspoint go up and down completely randomly.
Pair Corralation between NorthWestern and Siriuspoint
Considering the 90-day investment horizon NorthWestern is expected to generate 5.94 times less return on investment than Siriuspoint. But when comparing it to its historical volatility, NorthWestern is 1.84 times less risky than Siriuspoint. It trades about 0.07 of its potential returns per unit of risk. Siriuspoint is currently generating about 0.23 of returns per unit of risk over similar time horizon. If you would invest 1,351 in Siriuspoint on August 30, 2024 and sell it today you would earn a total of 194.00 from holding Siriuspoint or generate 14.36% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
NorthWestern vs. Siriuspoint
Performance |
| Timeline |
| NorthWestern |
| Siriuspoint |
NorthWestern and Siriuspoint Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with NorthWestern and Siriuspoint
The main advantage of trading using opposite NorthWestern and Siriuspoint positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NorthWestern position performs unexpectedly, Siriuspoint 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 Siriuspoint will offset losses from the drop in Siriuspoint's long position.| NorthWestern vs. Allete Inc | NorthWestern vs. Black Hills | NorthWestern vs. Otter Tail | NorthWestern vs. Avista |
| Siriuspoint vs. Maiden Holdings | Siriuspoint vs. Reinsurance Group of | Siriuspoint vs. Oxbridge Re Holdings | Siriuspoint vs. Greenlight Capital Re |
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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