Correlation Between Office Properties and Old Dominion
Can any of the company-specific risk be diversified away by investing in both Office Properties and Old Dominion 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 Office Properties and Old Dominion into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Office Properties Income and Old Dominion Freight, you can compare the effects of market volatilities on Office Properties and Old Dominion 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 Office Properties with a short position of Old Dominion. Check out your portfolio center. Please also check ongoing floating volatility patterns of Office Properties and Old Dominion.
Diversification Opportunities for Office Properties and Old Dominion
-0.42 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Office and Old is -0.42. Overlapping area represents the amount of risk that can be diversified away by holding Office Properties Income and Old Dominion Freight in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Old Dominion Freight and Office Properties 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 Office Properties Income are associated (or correlated) with Old Dominion. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Old Dominion Freight has no effect on the direction of Office Properties i.e., Office Properties and Old Dominion go up and down completely randomly.
Pair Corralation between Office Properties and Old Dominion
Assuming the 90 days horizon Office Properties Income is expected to generate 1.74 times more return on investment than Old Dominion. However, Office Properties is 1.74 times more volatile than Old Dominion Freight. It trades about 0.01 of its potential returns per unit of risk. Old Dominion Freight is currently generating about -0.45 per unit of risk. If you would invest 1,200 in Office Properties Income on October 11, 2024 and sell it today you would lose (2.00) from holding Office Properties Income or give up 0.17% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Office Properties Income vs. Old Dominion Freight
Performance |
Timeline |
Office Properties Income |
Old Dominion Freight |
Office Properties and Old Dominion Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Office Properties and Old Dominion
The main advantage of trading using opposite Office Properties and Old Dominion positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Office Properties position performs unexpectedly, Old Dominion 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 Old Dominion will offset losses from the drop in Old Dominion's long position.Office Properties vs. United States Cellular | Office Properties vs. United States Cellular | Office Properties vs. DBA Sempra 5750 | Office Properties vs. Hancock Whitney |
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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 Stocks Directory module to find actively traded stocks across global markets.
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