Correlation Between Unipol Gruppo and Park Aerospace
Can any of the company-specific risk be diversified away by investing in both Unipol Gruppo and Park Aerospace 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 Unipol Gruppo and Park Aerospace into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Unipol Gruppo Finanziario and Park Aerospace Corp, you can compare the effects of market volatilities on Unipol Gruppo and Park Aerospace 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 Unipol Gruppo with a short position of Park Aerospace. Check out your portfolio center. Please also check ongoing floating volatility patterns of Unipol Gruppo and Park Aerospace.
Diversification Opportunities for Unipol Gruppo and Park Aerospace
0.4 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Unipol and Park is 0.4. Overlapping area represents the amount of risk that can be diversified away by holding Unipol Gruppo Finanziario and Park Aerospace Corp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Park Aerospace Corp and Unipol Gruppo 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 Unipol Gruppo Finanziario are associated (or correlated) with Park Aerospace. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Park Aerospace Corp has no effect on the direction of Unipol Gruppo i.e., Unipol Gruppo and Park Aerospace go up and down completely randomly.
Pair Corralation between Unipol Gruppo and Park Aerospace
Assuming the 90 days trading horizon Unipol Gruppo is expected to generate 3.0 times less return on investment than Park Aerospace. But when comparing it to its historical volatility, Unipol Gruppo Finanziario is 1.58 times less risky than Park Aerospace. It trades about 0.05 of its potential returns per unit of risk. Park Aerospace Corp is currently generating about 0.09 of returns per unit of risk over similar time horizon. If you would invest 1,189 in Park Aerospace Corp on October 15, 2024 and sell it today you would earn a total of 151.00 from holding Park Aerospace Corp or generate 12.7% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Unipol Gruppo Finanziario vs. Park Aerospace Corp
Performance |
Timeline |
Unipol Gruppo Finanziario |
Park Aerospace Corp |
Unipol Gruppo and Park Aerospace Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Unipol Gruppo and Park Aerospace
The main advantage of trading using opposite Unipol Gruppo and Park Aerospace positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Unipol Gruppo position performs unexpectedly, Park Aerospace 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 Park Aerospace will offset losses from the drop in Park Aerospace's long position.Unipol Gruppo vs. Sch Environnement SA | Unipol Gruppo vs. STEEL DYNAMICS | Unipol Gruppo vs. Playmates Toys Limited | Unipol Gruppo vs. JD SPORTS FASH |
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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 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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