Correlation Between SFL and Q2 Holdings
Can any of the company-specific risk be diversified away by investing in both SFL and Q2 Holdings 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 SFL and Q2 Holdings into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between SFL Corporation and Q2 Holdings, you can compare the effects of market volatilities on SFL and Q2 Holdings 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 SFL with a short position of Q2 Holdings. Check out your portfolio center. Please also check ongoing floating volatility patterns of SFL and Q2 Holdings.
Diversification Opportunities for SFL and Q2 Holdings
0.72 | Correlation Coefficient |
Poor diversification
The 3 months correlation between SFL and QTWO is 0.72. Overlapping area represents the amount of risk that can be diversified away by holding SFL Corp. and Q2 Holdings in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Q2 Holdings and SFL 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 SFL Corporation are associated (or correlated) with Q2 Holdings. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Q2 Holdings has no effect on the direction of SFL i.e., SFL and Q2 Holdings go up and down completely randomly.
Pair Corralation between SFL and Q2 Holdings
Considering the 90-day investment horizon SFL Corporation is expected to generate 0.76 times more return on investment than Q2 Holdings. However, SFL Corporation is 1.32 times less risky than Q2 Holdings. It trades about -0.13 of its potential returns per unit of risk. Q2 Holdings is currently generating about -0.13 per unit of risk. If you would invest 976.00 in SFL Corporation on December 26, 2024 and sell it today you would lose (158.00) from holding SFL Corporation or give up 16.19% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
SFL Corp. vs. Q2 Holdings
Performance |
Timeline |
SFL Corporation |
Q2 Holdings |
SFL and Q2 Holdings Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with SFL and Q2 Holdings
The main advantage of trading using opposite SFL and Q2 Holdings positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if SFL position performs unexpectedly, Q2 Holdings 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 Q2 Holdings will offset losses from the drop in Q2 Holdings' long position.The idea behind SFL Corporation and Q2 Holdings 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.Q2 Holdings vs. PROS Holdings | Q2 Holdings vs. Meridianlink | Q2 Holdings vs. Enfusion | Q2 Holdings vs. Paylocity Holdng |
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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