Correlation Between Ambac Financial and PLAYMATES TOYS
Can any of the company-specific risk be diversified away by investing in both Ambac Financial and PLAYMATES TOYS 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 Ambac Financial and PLAYMATES TOYS into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ambac Financial Group and PLAYMATES TOYS, you can compare the effects of market volatilities on Ambac Financial and PLAYMATES TOYS 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 Ambac Financial with a short position of PLAYMATES TOYS. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ambac Financial and PLAYMATES TOYS.
Diversification Opportunities for Ambac Financial and PLAYMATES TOYS
-0.15 | Correlation Coefficient |
Good diversification
The 3 months correlation between Ambac and PLAYMATES is -0.15. Overlapping area represents the amount of risk that can be diversified away by holding Ambac Financial Group and PLAYMATES TOYS in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on PLAYMATES TOYS and Ambac Financial 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 Ambac Financial Group are associated (or correlated) with PLAYMATES TOYS. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of PLAYMATES TOYS has no effect on the direction of Ambac Financial i.e., Ambac Financial and PLAYMATES TOYS go up and down completely randomly.
Pair Corralation between Ambac Financial and PLAYMATES TOYS
Assuming the 90 days trading horizon Ambac Financial is expected to generate 1.15 times less return on investment than PLAYMATES TOYS. But when comparing it to its historical volatility, Ambac Financial Group is 1.11 times less risky than PLAYMATES TOYS. It trades about 0.07 of its potential returns per unit of risk. PLAYMATES TOYS is currently generating about 0.07 of returns per unit of risk over similar time horizon. If you would invest 6.60 in PLAYMATES TOYS on September 23, 2024 and sell it today you would earn a total of 0.20 from holding PLAYMATES TOYS or generate 3.03% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Ambac Financial Group vs. PLAYMATES TOYS
Performance |
Timeline |
Ambac Financial Group |
PLAYMATES TOYS |
Ambac Financial and PLAYMATES TOYS Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Ambac Financial and PLAYMATES TOYS
The main advantage of trading using opposite Ambac Financial and PLAYMATES TOYS positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ambac Financial position performs unexpectedly, PLAYMATES TOYS 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 PLAYMATES TOYS will offset losses from the drop in PLAYMATES TOYS's long position.Ambac Financial vs. PLAYMATES TOYS | Ambac Financial vs. CHINA TONTINE WINES | Ambac Financial vs. SIMS METAL MGT | Ambac Financial vs. PENN NATL GAMING |
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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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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