Correlation Between Invesco KBW and Pacific North
Can any of the company-specific risk be diversified away by investing in both Invesco KBW and Pacific North 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 Invesco KBW and Pacific North into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Invesco KBW Regional and Pacific North of, you can compare the effects of market volatilities on Invesco KBW and Pacific North 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 Invesco KBW with a short position of Pacific North. Check out your portfolio center. Please also check ongoing floating volatility patterns of Invesco KBW and Pacific North.
Diversification Opportunities for Invesco KBW and Pacific North
0.29 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Invesco and Pacific is 0.29. Overlapping area represents the amount of risk that can be diversified away by holding Invesco KBW Regional and Pacific North of in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Pacific North and Invesco KBW 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 Invesco KBW Regional are associated (or correlated) with Pacific North. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Pacific North has no effect on the direction of Invesco KBW i.e., Invesco KBW and Pacific North go up and down completely randomly.
Pair Corralation between Invesco KBW and Pacific North
Given the investment horizon of 90 days Invesco KBW is expected to generate 2.17 times less return on investment than Pacific North. In addition to that, Invesco KBW is 1.56 times more volatile than Pacific North of. It trades about 0.06 of its total potential returns per unit of risk. Pacific North of is currently generating about 0.2 per unit of volatility. If you would invest 2,531 in Pacific North of on July 24, 2025 and sell it today you would earn a total of 685.00 from holding Pacific North of or generate 27.06% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Invesco KBW Regional vs. Pacific North of
Performance |
| Timeline |
| Invesco KBW Regional |
| Pacific North |
Invesco KBW and Pacific North Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Invesco KBW and Pacific North
The main advantage of trading using opposite Invesco KBW and Pacific North positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Invesco KBW position performs unexpectedly, Pacific North 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 Pacific North will offset losses from the drop in Pacific North's long position.| Invesco KBW vs. First Trust Exchange Traded | Invesco KBW vs. The 2023 ETF | Invesco KBW vs. American Century ETF | Invesco KBW vs. Virtus Private Credit |
| Pacific North vs. Emerging Markets Active | Pacific North vs. First Trust Dow | Pacific North vs. First Trust Active | Pacific North vs. iShares AsiaPacific Dividend |
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 Competition Analyzer module to analyze and compare many basic indicators for a group of related or unrelated entities.
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