Correlation Between Meta Platforms and Spotify Technology
Can any of the company-specific risk be diversified away by investing in both Meta Platforms and Spotify Technology 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 Meta Platforms and Spotify Technology into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Meta Platforms and Spotify Technology SA, you can compare the effects of market volatilities on Meta Platforms and Spotify Technology 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 Meta Platforms with a short position of Spotify Technology. Check out your portfolio center. Please also check ongoing floating volatility patterns of Meta Platforms and Spotify Technology.
Diversification Opportunities for Meta Platforms and Spotify Technology
0.48 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Meta and Spotify is 0.48. Overlapping area represents the amount of risk that can be diversified away by holding Meta Platforms and Spotify Technology SA in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Spotify Technology and Meta Platforms 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 Meta Platforms are associated (or correlated) with Spotify Technology. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Spotify Technology has no effect on the direction of Meta Platforms i.e., Meta Platforms and Spotify Technology go up and down completely randomly.
Pair Corralation between Meta Platforms and Spotify Technology
Given the investment horizon of 90 days Meta Platforms is expected to generate 3.13 times less return on investment than Spotify Technology. But when comparing it to its historical volatility, Meta Platforms is 1.39 times less risky than Spotify Technology. It trades about 0.13 of its potential returns per unit of risk. Spotify Technology SA is currently generating about 0.29 of returns per unit of risk over similar time horizon. If you would invest 32,860 in Spotify Technology SA on September 2, 2024 and sell it today you would earn a total of 14,836 from holding Spotify Technology SA or generate 45.15% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Meta Platforms vs. Spotify Technology SA
Performance |
Timeline |
Meta Platforms |
Spotify Technology |
Meta Platforms and Spotify Technology Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Meta Platforms and Spotify Technology
The main advantage of trading using opposite Meta Platforms and Spotify Technology positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Meta Platforms position performs unexpectedly, Spotify Technology 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 Spotify Technology will offset losses from the drop in Spotify Technology's long position.Meta Platforms vs. MediaAlpha | Meta Platforms vs. Asset Entities Class | Meta Platforms vs. Shutterstock | Meta Platforms vs. Match Group |
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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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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