Correlation Between Columbia Sportswear and Johnson Matthey
Can any of the company-specific risk be diversified away by investing in both Columbia Sportswear and Johnson Matthey 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 Columbia Sportswear and Johnson Matthey into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Columbia Sportswear and Johnson Matthey PLC, you can compare the effects of market volatilities on Columbia Sportswear and Johnson Matthey 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 Columbia Sportswear with a short position of Johnson Matthey. Check out your portfolio center. Please also check ongoing floating volatility patterns of Columbia Sportswear and Johnson Matthey.
Diversification Opportunities for Columbia Sportswear and Johnson Matthey
-0.08 | Correlation Coefficient |
Good diversification
The 3 months correlation between Columbia and Johnson is -0.08. Overlapping area represents the amount of risk that can be diversified away by holding Columbia Sportswear and Johnson Matthey PLC in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Johnson Matthey PLC and Columbia Sportswear 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 Columbia Sportswear are associated (or correlated) with Johnson Matthey. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Johnson Matthey PLC has no effect on the direction of Columbia Sportswear i.e., Columbia Sportswear and Johnson Matthey go up and down completely randomly.
Pair Corralation between Columbia Sportswear and Johnson Matthey
Assuming the 90 days horizon Columbia Sportswear is expected to under-perform the Johnson Matthey. In addition to that, Columbia Sportswear is 1.37 times more volatile than Johnson Matthey PLC. It trades about -0.12 of its total potential returns per unit of risk. Johnson Matthey PLC is currently generating about 0.04 per unit of volatility. If you would invest 1,580 in Johnson Matthey PLC on December 22, 2024 and sell it today you would earn a total of 49.00 from holding Johnson Matthey PLC or generate 3.1% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Columbia Sportswear vs. Johnson Matthey PLC
Performance |
Timeline |
Columbia Sportswear |
Johnson Matthey PLC |
Columbia Sportswear and Johnson Matthey Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Columbia Sportswear and Johnson Matthey
The main advantage of trading using opposite Columbia Sportswear and Johnson Matthey positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Columbia Sportswear position performs unexpectedly, Johnson Matthey 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 Johnson Matthey will offset losses from the drop in Johnson Matthey's long position.Columbia Sportswear vs. PARKEN Sport Entertainment | Columbia Sportswear vs. PROSIEBENSAT1 MEDIADR4 | Columbia Sportswear vs. X FAB Silicon Foundries | Columbia Sportswear vs. CNVISION MEDIA |
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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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