Correlation Between SOFTWARE MANSION and Magna Polonia
Can any of the company-specific risk be diversified away by investing in both SOFTWARE MANSION and Magna Polonia 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 SOFTWARE MANSION and Magna Polonia into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between SOFTWARE MANSION SPOLKA and Magna Polonia SA, you can compare the effects of market volatilities on SOFTWARE MANSION and Magna Polonia 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 SOFTWARE MANSION with a short position of Magna Polonia. Check out your portfolio center. Please also check ongoing floating volatility patterns of SOFTWARE MANSION and Magna Polonia.
Diversification Opportunities for SOFTWARE MANSION and Magna Polonia
0.26 | Correlation Coefficient |
Modest diversification
The 3 months correlation between SOFTWARE and Magna is 0.26. Overlapping area represents the amount of risk that can be diversified away by holding SOFTWARE MANSION SPOLKA and Magna Polonia SA in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Magna Polonia SA and SOFTWARE MANSION 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 SOFTWARE MANSION SPOLKA are associated (or correlated) with Magna Polonia. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Magna Polonia SA has no effect on the direction of SOFTWARE MANSION i.e., SOFTWARE MANSION and Magna Polonia go up and down completely randomly.
Pair Corralation between SOFTWARE MANSION and Magna Polonia
Assuming the 90 days trading horizon SOFTWARE MANSION SPOLKA is expected to generate 1.86 times more return on investment than Magna Polonia. However, SOFTWARE MANSION is 1.86 times more volatile than Magna Polonia SA. It trades about 0.14 of its potential returns per unit of risk. Magna Polonia SA is currently generating about 0.09 per unit of risk. If you would invest 3,030 in SOFTWARE MANSION SPOLKA on December 23, 2024 and sell it today you would earn a total of 770.00 from holding SOFTWARE MANSION SPOLKA or generate 25.41% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 98.33% |
Values | Daily Returns |
SOFTWARE MANSION SPOLKA vs. Magna Polonia SA
Performance |
Timeline |
SOFTWARE MANSION SPOLKA |
Magna Polonia SA |
SOFTWARE MANSION and Magna Polonia Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with SOFTWARE MANSION and Magna Polonia
The main advantage of trading using opposite SOFTWARE MANSION and Magna Polonia positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if SOFTWARE MANSION position performs unexpectedly, Magna Polonia 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 Magna Polonia will offset losses from the drop in Magna Polonia's long position.SOFTWARE MANSION vs. Banco Santander SA | SOFTWARE MANSION vs. UniCredit SpA | SOFTWARE MANSION vs. CEZ as | SOFTWARE MANSION vs. Polski Koncern Naftowy |
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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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