Correlation Between Procter Gamble and JBG SMITH
Can any of the company-specific risk be diversified away by investing in both Procter Gamble and JBG SMITH 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 Procter Gamble and JBG SMITH into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Procter Gamble and JBG SMITH Properties, you can compare the effects of market volatilities on Procter Gamble and JBG SMITH 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 Procter Gamble with a short position of JBG SMITH. Check out your portfolio center. Please also check ongoing floating volatility patterns of Procter Gamble and JBG SMITH.
Diversification Opportunities for Procter Gamble and JBG SMITH
-0.01 | Correlation Coefficient |
Good diversification
The 3 months correlation between Procter and JBG is -0.01. Overlapping area represents the amount of risk that can be diversified away by holding Procter Gamble and JBG SMITH Properties in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on JBG SMITH Properties and Procter Gamble 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 Procter Gamble are associated (or correlated) with JBG SMITH. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of JBG SMITH Properties has no effect on the direction of Procter Gamble i.e., Procter Gamble and JBG SMITH go up and down completely randomly.
Pair Corralation between Procter Gamble and JBG SMITH
Allowing for the 90-day total investment horizon Procter Gamble is expected to generate 0.44 times more return on investment than JBG SMITH. However, Procter Gamble is 2.3 times less risky than JBG SMITH. It trades about 0.04 of its potential returns per unit of risk. JBG SMITH Properties is currently generating about 0.0 per unit of risk. If you would invest 14,468 in Procter Gamble on September 28, 2024 and sell it today you would earn a total of 2,548 from holding Procter Gamble or generate 17.61% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Procter Gamble vs. JBG SMITH Properties
Performance |
Timeline |
Procter Gamble |
JBG SMITH Properties |
Procter Gamble and JBG SMITH Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Procter Gamble and JBG SMITH
The main advantage of trading using opposite Procter Gamble and JBG SMITH positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Procter Gamble position performs unexpectedly, JBG SMITH 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 JBG SMITH will offset losses from the drop in JBG SMITH's long position.Procter Gamble vs. Unilever PLC ADR | Procter Gamble vs. Estee Lauder Companies | Procter Gamble vs. ELF Beauty | Procter Gamble vs. Coty Inc |
JBG SMITH vs. Cousins Properties Incorporated | JBG SMITH vs. Highwoods Properties | JBG SMITH vs. Douglas Emmett | JBG SMITH vs. Equity Commonwealth |
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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