Correlation Between ConnectOne Bancorp and 63253QAB0
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By analyzing existing cross correlation between ConnectOne Bancorp and NAB 4944 12 JAN 28, you can compare the effects of market volatilities on ConnectOne Bancorp and 63253QAB0 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 ConnectOne Bancorp with a short position of 63253QAB0. Check out your portfolio center. Please also check ongoing floating volatility patterns of ConnectOne Bancorp and 63253QAB0.
Diversification Opportunities for ConnectOne Bancorp and 63253QAB0
-0.65 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between ConnectOne and 63253QAB0 is -0.65. Overlapping area represents the amount of risk that can be diversified away by holding ConnectOne Bancorp and NAB 4944 12 JAN 28 in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on NAB 4944 12 and ConnectOne Bancorp 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 ConnectOne Bancorp are associated (or correlated) with 63253QAB0. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of NAB 4944 12 has no effect on the direction of ConnectOne Bancorp i.e., ConnectOne Bancorp and 63253QAB0 go up and down completely randomly.
Pair Corralation between ConnectOne Bancorp and 63253QAB0
Assuming the 90 days horizon ConnectOne Bancorp is expected to generate 2.51 times less return on investment than 63253QAB0. But when comparing it to its historical volatility, ConnectOne Bancorp is 4.08 times less risky than 63253QAB0. It trades about 0.06 of its potential returns per unit of risk. NAB 4944 12 JAN 28 is currently generating about 0.04 of returns per unit of risk over similar time horizon. If you would invest 10,122 in NAB 4944 12 JAN 28 on September 25, 2024 and sell it today you would earn a total of 66.00 from holding NAB 4944 12 JAN 28 or generate 0.65% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 70.0% |
Values | Daily Returns |
ConnectOne Bancorp vs. NAB 4944 12 JAN 28
Performance |
Timeline |
ConnectOne Bancorp |
NAB 4944 12 |
ConnectOne Bancorp and 63253QAB0 Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with ConnectOne Bancorp and 63253QAB0
The main advantage of trading using opposite ConnectOne Bancorp and 63253QAB0 positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if ConnectOne Bancorp position performs unexpectedly, 63253QAB0 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 63253QAB0 will offset losses from the drop in 63253QAB0's long position.The idea behind ConnectOne Bancorp and NAB 4944 12 JAN 28 pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.63253QAB0 vs. Coty Inc | 63253QAB0 vs. Victorias Secret Co | 63253QAB0 vs. Lindblad Expeditions Holdings | 63253QAB0 vs. JD Sports Fashion |
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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