Correlation Between Cabana Target and Regents Park
Can any of the company-specific risk be diversified away by investing in both Cabana Target and Regents Park 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 Cabana Target and Regents Park into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Cabana Target Drawdown and Regents Park Hedged, you can compare the effects of market volatilities on Cabana Target and Regents Park 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 Cabana Target with a short position of Regents Park. Check out your portfolio center. Please also check ongoing floating volatility patterns of Cabana Target and Regents Park.
Diversification Opportunities for Cabana Target and Regents Park
0.92 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Cabana and Regents is 0.92. Overlapping area represents the amount of risk that can be diversified away by holding Cabana Target Drawdown and Regents Park Hedged in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Regents Park Hedged and Cabana Target 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 Cabana Target Drawdown are associated (or correlated) with Regents Park. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Regents Park Hedged has no effect on the direction of Cabana Target i.e., Cabana Target and Regents Park go up and down completely randomly.
Pair Corralation between Cabana Target and Regents Park
Given the investment horizon of 90 days Cabana Target Drawdown is expected to generate 0.81 times more return on investment than Regents Park. However, Cabana Target Drawdown is 1.23 times less risky than Regents Park. It trades about 0.22 of its potential returns per unit of risk. Regents Park Hedged is currently generating about 0.14 per unit of risk. If you would invest 2,525 in Cabana Target Drawdown on August 30, 2024 and sell it today you would earn a total of 67.00 from holding Cabana Target Drawdown or generate 2.65% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Cabana Target Drawdown vs. Regents Park Hedged
Performance |
| Timeline |
| Cabana Target Drawdown |
| Regents Park Hedged |
Cabana Target and Regents Park Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Cabana Target and Regents Park
The main advantage of trading using opposite Cabana Target and Regents Park positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Cabana Target position performs unexpectedly, Regents Park 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 Regents Park will offset losses from the drop in Regents Park's long position.| Cabana Target vs. Tech Central | Cabana Target vs. Global X PropTech | Cabana Target vs. TransAct Technologies Incorporated | Cabana Target vs. 1st Source |
| Regents Park vs. Cabana Target Leading | Regents Park vs. Cabana Target Drawdown | Regents Park vs. FT Cboe Vest |
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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