Correlation Between Sumitomo Rubber and PACCAR
Can any of the company-specific risk be diversified away by investing in both Sumitomo Rubber and PACCAR 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 Sumitomo Rubber and PACCAR into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Sumitomo Rubber Industries and PACCAR Inc, you can compare the effects of market volatilities on Sumitomo Rubber and PACCAR 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 Sumitomo Rubber with a short position of PACCAR. Check out your portfolio center. Please also check ongoing floating volatility patterns of Sumitomo Rubber and PACCAR.
Diversification Opportunities for Sumitomo Rubber and PACCAR
0.64 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Sumitomo and PACCAR is 0.64. Overlapping area represents the amount of risk that can be diversified away by holding Sumitomo Rubber Industries and PACCAR Inc in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on PACCAR Inc and Sumitomo Rubber 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 Sumitomo Rubber Industries are associated (or correlated) with PACCAR. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of PACCAR Inc has no effect on the direction of Sumitomo Rubber i.e., Sumitomo Rubber and PACCAR go up and down completely randomly.
Pair Corralation between Sumitomo Rubber and PACCAR
Assuming the 90 days horizon Sumitomo Rubber Industries is expected to generate 3.78 times more return on investment than PACCAR. However, Sumitomo Rubber is 3.78 times more volatile than PACCAR Inc. It trades about 0.06 of its potential returns per unit of risk. PACCAR Inc is currently generating about 0.08 per unit of risk. If you would invest 339.00 in Sumitomo Rubber Industries on September 27, 2024 and sell it today you would earn a total of 731.00 from holding Sumitomo Rubber Industries or generate 215.63% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Sumitomo Rubber Industries vs. PACCAR Inc
Performance |
Timeline |
Sumitomo Rubber Indu |
PACCAR Inc |
Sumitomo Rubber and PACCAR Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Sumitomo Rubber and PACCAR
The main advantage of trading using opposite Sumitomo Rubber and PACCAR positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Sumitomo Rubber position performs unexpectedly, PACCAR 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 PACCAR will offset losses from the drop in PACCAR's long position.Sumitomo Rubber vs. The Goodyear Tire | Sumitomo Rubber vs. Zeon Corporation | Sumitomo Rubber vs. Essentra plc | Sumitomo Rubber vs. Polyplex Public |
PACCAR vs. Sinotruk Limited | PACCAR vs. Wabash National | PACCAR vs. Hyster Yale Materials Handling | PACCAR vs. Qingling Motors Co |
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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