Correlation Between Autosports and Hotel Property
Can any of the company-specific risk be diversified away by investing in both Autosports and Hotel Property 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 Autosports and Hotel Property into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Autosports Group and Hotel Property Investments, you can compare the effects of market volatilities on Autosports and Hotel Property 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 Autosports with a short position of Hotel Property. Check out your portfolio center. Please also check ongoing floating volatility patterns of Autosports and Hotel Property.
Diversification Opportunities for Autosports and Hotel Property
-0.08 | Correlation Coefficient |
Good diversification
The 3 months correlation between Autosports and Hotel is -0.08. Overlapping area represents the amount of risk that can be diversified away by holding Autosports Group and Hotel Property Investments in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Hotel Property Inves and Autosports 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 Autosports Group are associated (or correlated) with Hotel Property. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Hotel Property Inves has no effect on the direction of Autosports i.e., Autosports and Hotel Property go up and down completely randomly.
Pair Corralation between Autosports and Hotel Property
Assuming the 90 days trading horizon Autosports Group is expected to under-perform the Hotel Property. In addition to that, Autosports is 1.27 times more volatile than Hotel Property Investments. It trades about -0.01 of its total potential returns per unit of risk. Hotel Property Investments is currently generating about 0.1 per unit of volatility. If you would invest 274.00 in Hotel Property Investments on August 25, 2024 and sell it today you would earn a total of 96.00 from holding Hotel Property Investments or generate 35.04% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Autosports Group vs. Hotel Property Investments
Performance |
Timeline |
Autosports Group |
Hotel Property Inves |
Autosports and Hotel Property Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Autosports and Hotel Property
The main advantage of trading using opposite Autosports and Hotel Property positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Autosports position performs unexpectedly, Hotel Property 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 Hotel Property will offset losses from the drop in Hotel Property's long position.Autosports vs. Aneka Tambang Tbk | Autosports vs. Macquarie Group | Autosports vs. Macquarie Group Ltd | Autosports vs. Challenger |
Hotel Property vs. Mayfield Childcare | Hotel Property vs. Aurelia Metals | Hotel Property vs. EVE Health Group | Hotel Property vs. Oneview Healthcare PLC |
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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