Correlation Between Procter Gamble and Pacer Swan
Can any of the company-specific risk be diversified away by investing in both Procter Gamble and Pacer Swan 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 Pacer Swan into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Procter Gamble and Pacer Swan SOS, you can compare the effects of market volatilities on Procter Gamble and Pacer Swan 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 Pacer Swan. Check out your portfolio center. Please also check ongoing floating volatility patterns of Procter Gamble and Pacer Swan.
Diversification Opportunities for Procter Gamble and Pacer Swan
-0.32 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Procter and Pacer is -0.32. Overlapping area represents the amount of risk that can be diversified away by holding Procter Gamble and Pacer Swan SOS in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Pacer Swan SOS 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 Pacer Swan. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Pacer Swan SOS has no effect on the direction of Procter Gamble i.e., Procter Gamble and Pacer Swan go up and down completely randomly.
Pair Corralation between Procter Gamble and Pacer Swan
Allowing for the 90-day total investment horizon Procter Gamble is expected to generate 2.41 times more return on investment than Pacer Swan. However, Procter Gamble is 2.41 times more volatile than Pacer Swan SOS. It trades about 0.05 of its potential returns per unit of risk. Pacer Swan SOS is currently generating about 0.12 per unit of risk. If you would invest 14,361 in Procter Gamble on August 30, 2024 and sell it today you would earn a total of 3,575 from holding Procter Gamble or generate 24.89% 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. Pacer Swan SOS
Performance |
| Timeline |
| Procter Gamble |
| Pacer Swan SOS |
Procter Gamble and Pacer Swan Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Procter Gamble and Pacer Swan
The main advantage of trading using opposite Procter Gamble and Pacer Swan positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Procter Gamble position performs unexpectedly, Pacer Swan 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 Pacer Swan will offset losses from the drop in Pacer Swan's long position.| Procter Gamble vs. The Clorox | Procter Gamble vs. Colgate Palmolive | Procter Gamble vs. Church Dwight | Procter Gamble vs. Kimberly Clark |
| Pacer Swan vs. Pacer Swan SOS | Pacer Swan vs. Pacer Swan SOS | Pacer Swan vs. Pacer Funds Trust | Pacer Swan vs. Pacer Swan SOS |
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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