Correlation Between XTL Biopharmaceutica and Netz Hotels
Can any of the company-specific risk be diversified away by investing in both XTL Biopharmaceutica and Netz Hotels 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 XTL Biopharmaceutica and Netz Hotels into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between XTL Biopharmaceuticals and Netz Hotels, you can compare the effects of market volatilities on XTL Biopharmaceutica and Netz Hotels 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 XTL Biopharmaceutica with a short position of Netz Hotels. Check out your portfolio center. Please also check ongoing floating volatility patterns of XTL Biopharmaceutica and Netz Hotels.
Diversification Opportunities for XTL Biopharmaceutica and Netz Hotels
-0.51 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between XTL and Netz is -0.51. Overlapping area represents the amount of risk that can be diversified away by holding XTL Biopharmaceuticals and Netz Hotels in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Netz Hotels and XTL Biopharmaceutica 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 XTL Biopharmaceuticals are associated (or correlated) with Netz Hotels. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Netz Hotels has no effect on the direction of XTL Biopharmaceutica i.e., XTL Biopharmaceutica and Netz Hotels go up and down completely randomly.
Pair Corralation between XTL Biopharmaceutica and Netz Hotels
Assuming the 90 days trading horizon XTL Biopharmaceuticals is expected to generate 1.84 times more return on investment than Netz Hotels. However, XTL Biopharmaceutica is 1.84 times more volatile than Netz Hotels. It trades about 0.06 of its potential returns per unit of risk. Netz Hotels is currently generating about 0.02 per unit of risk. If you would invest 400.00 in XTL Biopharmaceuticals on August 29, 2024 and sell it today you would earn a total of 240.00 from holding XTL Biopharmaceuticals or generate 60.0% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
XTL Biopharmaceuticals vs. Netz Hotels
Performance |
Timeline |
XTL Biopharmaceuticals |
Netz Hotels |
XTL Biopharmaceutica and Netz Hotels Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with XTL Biopharmaceutica and Netz Hotels
The main advantage of trading using opposite XTL Biopharmaceutica and Netz Hotels positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if XTL Biopharmaceutica position performs unexpectedly, Netz Hotels 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 Netz Hotels will offset losses from the drop in Netz Hotels' long position.XTL Biopharmaceutica vs. XTL Biopharmaceuticals Ltd | XTL Biopharmaceutica vs. Intercure | XTL Biopharmaceutica vs. BioLine RX | XTL Biopharmaceutica vs. Foresight Autonomous Holdings |
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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 Portfolio Suggestion module to get suggestions outside of your existing asset allocation including your own model portfolios.
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