Correlation Between Spotify Technology and DS Smith
Can any of the company-specific risk be diversified away by investing in both Spotify Technology and DS Smith 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 Spotify Technology and DS Smith into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Spotify Technology SA and DS Smith PLC, you can compare the effects of market volatilities on Spotify Technology and DS Smith 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 Spotify Technology with a short position of DS Smith. Check out your portfolio center. Please also check ongoing floating volatility patterns of Spotify Technology and DS Smith.
Diversification Opportunities for Spotify Technology and DS Smith
0.8 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Spotify and SMDS is 0.8. Overlapping area represents the amount of risk that can be diversified away by holding Spotify Technology SA and DS Smith PLC in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on DS Smith PLC and Spotify Technology 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 Spotify Technology SA are associated (or correlated) with DS Smith. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of DS Smith PLC has no effect on the direction of Spotify Technology i.e., Spotify Technology and DS Smith go up and down completely randomly.
Pair Corralation between Spotify Technology and DS Smith
Assuming the 90 days trading horizon Spotify Technology SA is expected to generate 1.33 times more return on investment than DS Smith. However, Spotify Technology is 1.33 times more volatile than DS Smith PLC. It trades about 0.15 of its potential returns per unit of risk. DS Smith PLC is currently generating about 0.07 per unit of risk. If you would invest 8,838 in Spotify Technology SA on October 11, 2024 and sell it today you would earn a total of 36,792 from holding Spotify Technology SA or generate 416.29% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 98.19% |
| Values | Daily Returns |
Spotify Technology SA vs. DS Smith PLC
Performance |
| Timeline |
| Spotify Technology |
| DS Smith PLC |
Spotify Technology and DS Smith Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Spotify Technology and DS Smith
The main advantage of trading using opposite Spotify Technology and DS Smith positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Spotify Technology position performs unexpectedly, DS Smith 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 DS Smith will offset losses from the drop in DS Smith's long position.| Spotify Technology vs. JD Sports Fashion | Spotify Technology vs. One Media iP | Spotify Technology vs. Bisichi Mining PLC | Spotify Technology vs. Hecla Mining Co |
| DS Smith vs. Coeur Mining | DS Smith vs. Spotify Technology SA | DS Smith vs. Europa Metals | DS Smith vs. Axway Software SA |
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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