Correlation Between Ford and UBS Property
Can any of the company-specific risk be diversified away by investing in both Ford and UBS 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 Ford and UBS Property into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ford Motor and UBS Property, you can compare the effects of market volatilities on Ford and UBS 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 Ford with a short position of UBS Property. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ford and UBS Property.
Diversification Opportunities for Ford and UBS Property
-0.49 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Ford and UBS is -0.49. Overlapping area represents the amount of risk that can be diversified away by holding Ford Motor and UBS Property in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on UBS Property and Ford 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 Ford Motor are associated (or correlated) with UBS Property. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of UBS Property has no effect on the direction of Ford i.e., Ford and UBS Property go up and down completely randomly.
Pair Corralation between Ford and UBS Property
Taking into account the 90-day investment horizon Ford Motor is expected to under-perform the UBS Property. In addition to that, Ford is 2.28 times more volatile than UBS Property. It trades about -0.34 of its total potential returns per unit of risk. UBS Property is currently generating about 0.07 per unit of volatility. If you would invest 6,980 in UBS Property on September 27, 2024 and sell it today you would earn a total of 60.00 from holding UBS Property or generate 0.86% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 95.45% |
Values | Daily Returns |
Ford Motor vs. UBS Property
Performance |
Timeline |
Ford Motor |
UBS Property |
Ford and UBS Property Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Ford and UBS Property
The main advantage of trading using opposite Ford and UBS Property positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ford position performs unexpectedly, UBS 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 UBS Property will offset losses from the drop in UBS Property's long position.The idea behind Ford Motor and UBS Property 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.UBS Property vs. Procimmo Real Estate | UBS Property vs. Baloise Holding AG | UBS Property vs. Banque Cantonale du | UBS Property vs. Invesco EQQQ NASDAQ 100 |
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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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