Correlation Between Netflix and Thyssenkrupp
Can any of the company-specific risk be diversified away by investing in both Netflix and Thyssenkrupp 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 Netflix and Thyssenkrupp into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Netflix and Thyssenkrupp AG ON, you can compare the effects of market volatilities on Netflix and Thyssenkrupp 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 Netflix with a short position of Thyssenkrupp. Check out your portfolio center. Please also check ongoing floating volatility patterns of Netflix and Thyssenkrupp.
Diversification Opportunities for Netflix and Thyssenkrupp
0.84 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Netflix and Thyssenkrupp is 0.84. Overlapping area represents the amount of risk that can be diversified away by holding Netflix and Thyssenkrupp AG ON in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Thyssenkrupp AG ON and Netflix 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 Netflix are associated (or correlated) with Thyssenkrupp. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Thyssenkrupp AG ON has no effect on the direction of Netflix i.e., Netflix and Thyssenkrupp go up and down completely randomly.
Pair Corralation between Netflix and Thyssenkrupp
Given the investment horizon of 90 days Netflix is expected to generate 1.04 times less return on investment than Thyssenkrupp. But when comparing it to its historical volatility, Netflix is 2.29 times less risky than Thyssenkrupp. It trades about 0.59 of its potential returns per unit of risk. Thyssenkrupp AG ON is currently generating about 0.27 of returns per unit of risk over similar time horizon. If you would invest 319.00 in Thyssenkrupp AG ON on September 5, 2024 and sell it today you would earn a total of 68.00 from holding Thyssenkrupp AG ON or generate 21.32% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 91.3% |
| Values | Daily Returns |
Netflix vs. Thyssenkrupp AG ON
Performance |
| Timeline |
| Netflix |
| Thyssenkrupp AG ON |
Netflix and Thyssenkrupp Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Netflix and Thyssenkrupp
The main advantage of trading using opposite Netflix and Thyssenkrupp positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Netflix position performs unexpectedly, Thyssenkrupp 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 Thyssenkrupp will offset losses from the drop in Thyssenkrupp's long position.| Netflix vs. Paramount Global Class | Netflix vs. Roku Inc | Netflix vs. Warner Bros Discovery | Netflix vs. AMC Entertainment Holdings |
| Thyssenkrupp vs. Samsung Electronics Co | Thyssenkrupp vs. Samsung Electronics Co | Thyssenkrupp vs. Hyundai Motor | Thyssenkrupp vs. Toyota Motor Corp |
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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