Correlation Between Procter Gamble and Project Energy
Can any of the company-specific risk be diversified away by investing in both Procter Gamble and Project Energy 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 Project Energy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Procter Gamble and Project Energy Reimagined, you can compare the effects of market volatilities on Procter Gamble and Project Energy 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 Project Energy. Check out your portfolio center. Please also check ongoing floating volatility patterns of Procter Gamble and Project Energy.
Diversification Opportunities for Procter Gamble and Project Energy
-0.65 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Procter and Project is -0.65. Overlapping area represents the amount of risk that can be diversified away by holding Procter Gamble and Project Energy Reimagined in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Project Energy Reimagined 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 Project Energy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Project Energy Reimagined has no effect on the direction of Procter Gamble i.e., Procter Gamble and Project Energy go up and down completely randomly.
Pair Corralation between Procter Gamble and Project Energy
Allowing for the 90-day total investment horizon Procter Gamble is expected to generate 0.07 times more return on investment than Project Energy. However, Procter Gamble is 14.53 times less risky than Project Energy. It trades about 0.07 of its potential returns per unit of risk. Project Energy Reimagined is currently generating about -0.08 per unit of risk. If you would invest 16,250 in Procter Gamble on September 3, 2024 and sell it today you would earn a total of 1,676 from holding Procter Gamble or generate 10.31% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Weak |
| Accuracy | 41.1% |
| Values | Daily Returns |
Procter Gamble vs. Project Energy Reimagined
Performance |
| Timeline |
| Procter Gamble |
| Project Energy Reimagined |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
Procter Gamble and Project Energy Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Procter Gamble and Project Energy
The main advantage of trading using opposite Procter Gamble and Project Energy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Procter Gamble position performs unexpectedly, Project Energy 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 Project Energy will offset losses from the drop in Project Energy's long position.| Procter Gamble vs. Highway Holdings Limited | Procter Gamble vs. QCR Holdings | Procter Gamble vs. Partner Communications | Procter Gamble vs. Acumen Pharmaceuticals |
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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