Correlation Between MGIC INVESTMENT and QBE Insurance
Can any of the company-specific risk be diversified away by investing in both MGIC INVESTMENT and QBE Insurance 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 MGIC INVESTMENT and QBE Insurance into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between MGIC INVESTMENT and QBE Insurance Group, you can compare the effects of market volatilities on MGIC INVESTMENT and QBE Insurance 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 MGIC INVESTMENT with a short position of QBE Insurance. Check out your portfolio center. Please also check ongoing floating volatility patterns of MGIC INVESTMENT and QBE Insurance.
Diversification Opportunities for MGIC INVESTMENT and QBE Insurance
-0.11 | Correlation Coefficient |
Good diversification
The 3 months correlation between MGIC and QBE is -0.11. Overlapping area represents the amount of risk that can be diversified away by holding MGIC INVESTMENT and QBE Insurance Group in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on QBE Insurance Group and MGIC INVESTMENT 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 MGIC INVESTMENT are associated (or correlated) with QBE Insurance. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of QBE Insurance Group has no effect on the direction of MGIC INVESTMENT i.e., MGIC INVESTMENT and QBE Insurance go up and down completely randomly.
Pair Corralation between MGIC INVESTMENT and QBE Insurance
Assuming the 90 days trading horizon MGIC INVESTMENT is expected to generate 7.54 times less return on investment than QBE Insurance. But when comparing it to its historical volatility, MGIC INVESTMENT is 1.18 times less risky than QBE Insurance. It trades about 0.02 of its potential returns per unit of risk. QBE Insurance Group is currently generating about 0.15 of returns per unit of risk over similar time horizon. If you would invest 1,117 in QBE Insurance Group on December 28, 2024 and sell it today you would earn a total of 173.00 from holding QBE Insurance Group or generate 15.49% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
MGIC INVESTMENT vs. QBE Insurance Group
Performance |
Timeline |
MGIC INVESTMENT |
QBE Insurance Group |
MGIC INVESTMENT and QBE Insurance Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with MGIC INVESTMENT and QBE Insurance
The main advantage of trading using opposite MGIC INVESTMENT and QBE Insurance positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if MGIC INVESTMENT position performs unexpectedly, QBE Insurance 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 QBE Insurance will offset losses from the drop in QBE Insurance's long position.MGIC INVESTMENT vs. Apple Inc | MGIC INVESTMENT vs. Apple Inc | MGIC INVESTMENT vs. Apple Inc | MGIC INVESTMENT vs. Apple Inc |
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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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