Correlation Between OneSavings Bank and Cardiff Property
Can any of the company-specific risk be diversified away by investing in both OneSavings Bank and Cardiff Property 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 OneSavings Bank and Cardiff Property into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between OneSavings Bank PLC and Cardiff Property PLC, you can compare the effects of market volatilities on OneSavings Bank and Cardiff Property 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 OneSavings Bank with a short position of Cardiff Property. Check out your portfolio center. Please also check ongoing floating volatility patterns of OneSavings Bank and Cardiff Property.
Diversification Opportunities for OneSavings Bank and Cardiff Property
0.76 | Correlation Coefficient |
Poor diversification
The 3 months correlation between OneSavings and Cardiff is 0.76. Overlapping area represents the amount of risk that can be diversified away by holding OneSavings Bank PLC and Cardiff Property PLC in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Cardiff Property PLC and OneSavings Bank 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 OneSavings Bank PLC are associated (or correlated) with Cardiff Property. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Cardiff Property PLC has no effect on the direction of OneSavings Bank i.e., OneSavings Bank and Cardiff Property go up and down completely randomly.
Pair Corralation between OneSavings Bank and Cardiff Property
Assuming the 90 days trading horizon OneSavings Bank is expected to generate 2.22 times less return on investment than Cardiff Property. In addition to that, OneSavings Bank is 2.18 times more volatile than Cardiff Property PLC. It trades about 0.03 of its total potential returns per unit of risk. Cardiff Property PLC is currently generating about 0.13 per unit of volatility. If you would invest 230,000 in Cardiff Property PLC on September 29, 2024 and sell it today you would earn a total of 15,000 from holding Cardiff Property PLC or generate 6.52% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
OneSavings Bank PLC vs. Cardiff Property PLC
Performance |
Timeline |
OneSavings Bank PLC |
Cardiff Property PLC |
OneSavings Bank and Cardiff Property Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with OneSavings Bank and Cardiff Property
The main advantage of trading using opposite OneSavings Bank and Cardiff Property positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if OneSavings Bank position performs unexpectedly, Cardiff Property 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 Cardiff Property will offset losses from the drop in Cardiff Property's long position.OneSavings Bank vs. Chocoladefabriken Lindt Spruengli | OneSavings Bank vs. National Atomic Co | OneSavings Bank vs. OTP Bank Nyrt | OneSavings Bank vs. Samsung Electronics Co |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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