Correlation Between Reynolds Consumer and Silgan Holdings
Can any of the company-specific risk be diversified away by investing in both Reynolds Consumer and Silgan Holdings 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 Reynolds Consumer and Silgan Holdings into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Reynolds Consumer Products and Silgan Holdings, you can compare the effects of market volatilities on Reynolds Consumer and Silgan Holdings 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 Reynolds Consumer with a short position of Silgan Holdings. Check out your portfolio center. Please also check ongoing floating volatility patterns of Reynolds Consumer and Silgan Holdings.
Diversification Opportunities for Reynolds Consumer and Silgan Holdings
0.36 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Reynolds and Silgan is 0.36. Overlapping area represents the amount of risk that can be diversified away by holding Reynolds Consumer Products and Silgan Holdings in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Silgan Holdings and Reynolds Consumer 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 Reynolds Consumer Products are associated (or correlated) with Silgan Holdings. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Silgan Holdings has no effect on the direction of Reynolds Consumer i.e., Reynolds Consumer and Silgan Holdings go up and down completely randomly.
Pair Corralation between Reynolds Consumer and Silgan Holdings
Given the investment horizon of 90 days Reynolds Consumer Products is expected to under-perform the Silgan Holdings. In addition to that, Reynolds Consumer is 1.16 times more volatile than Silgan Holdings. It trades about -0.1 of its total potential returns per unit of risk. Silgan Holdings is currently generating about 0.01 per unit of volatility. If you would invest 5,152 in Silgan Holdings on December 29, 2024 and sell it today you would lose (3.00) from holding Silgan Holdings or give up 0.06% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Reynolds Consumer Products vs. Silgan Holdings
Performance |
Timeline |
Reynolds Consumer |
Silgan Holdings |
Reynolds Consumer and Silgan Holdings Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Reynolds Consumer and Silgan Holdings
The main advantage of trading using opposite Reynolds Consumer and Silgan Holdings positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Reynolds Consumer position performs unexpectedly, Silgan Holdings 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 Silgan Holdings will offset losses from the drop in Silgan Holdings' long position.Reynolds Consumer vs. Greif Bros | Reynolds Consumer vs. Karat Packaging | Reynolds Consumer vs. Silgan Holdings | Reynolds Consumer vs. O I Glass |
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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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