Correlation Between RBC Bearings and Church Dwight
Can any of the company-specific risk be diversified away by investing in both RBC Bearings and Church Dwight 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 RBC Bearings and Church Dwight into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between RBC Bearings Incorporated and Church Dwight, you can compare the effects of market volatilities on RBC Bearings and Church Dwight 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 RBC Bearings with a short position of Church Dwight. Check out your portfolio center. Please also check ongoing floating volatility patterns of RBC Bearings and Church Dwight.
Diversification Opportunities for RBC Bearings and Church Dwight
0.72 | Correlation Coefficient |
Poor diversification
The 3 months correlation between RBC and Church is 0.72. Overlapping area represents the amount of risk that can be diversified away by holding RBC Bearings Incorporated and Church Dwight in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Church Dwight and RBC Bearings 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 RBC Bearings Incorporated are associated (or correlated) with Church Dwight. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Church Dwight has no effect on the direction of RBC Bearings i.e., RBC Bearings and Church Dwight go up and down completely randomly.
Pair Corralation between RBC Bearings and Church Dwight
Considering the 90-day investment horizon RBC Bearings Incorporated is expected to generate 1.73 times more return on investment than Church Dwight. However, RBC Bearings is 1.73 times more volatile than Church Dwight. It trades about 0.33 of its potential returns per unit of risk. Church Dwight is currently generating about 0.32 per unit of risk. If you would invest 28,857 in RBC Bearings Incorporated on August 28, 2024 and sell it today you would earn a total of 5,021 from holding RBC Bearings Incorporated or generate 17.4% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
RBC Bearings Incorporated vs. Church Dwight
Performance |
| Timeline |
| RBC Bearings |
| Church Dwight |
RBC Bearings and Church Dwight Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with RBC Bearings and Church Dwight
The main advantage of trading using opposite RBC Bearings and Church Dwight positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if RBC Bearings position performs unexpectedly, Church Dwight 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 Church Dwight will offset losses from the drop in Church Dwight's long position.| RBC Bearings vs. Lincoln Electric Holdings | RBC Bearings vs. Kennametal | RBC Bearings vs. Toro Co | RBC Bearings vs. Snap On |
| Church Dwight vs. Kimberly Clark | Church Dwight vs. Colgate Palmolive | Church Dwight vs. Unilever PLC ADR | Church Dwight vs. Procter Gamble |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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