Correlation Between SOFTWARE MANSION and Gaming Factory
Can any of the company-specific risk be diversified away by investing in both SOFTWARE MANSION and Gaming Factory 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 Gaming Factory 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 Gaming Factory SA, you can compare the effects of market volatilities on SOFTWARE MANSION and Gaming Factory 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 Gaming Factory. Check out your portfolio center. Please also check ongoing floating volatility patterns of SOFTWARE MANSION and Gaming Factory.
Diversification Opportunities for SOFTWARE MANSION and Gaming Factory
0.54 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between SOFTWARE and Gaming is 0.54. Overlapping area represents the amount of risk that can be diversified away by holding SOFTWARE MANSION SPOLKA and Gaming Factory SA in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Gaming Factory 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 Gaming Factory. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Gaming Factory SA has no effect on the direction of SOFTWARE MANSION i.e., SOFTWARE MANSION and Gaming Factory go up and down completely randomly.
Pair Corralation between SOFTWARE MANSION and Gaming Factory
Assuming the 90 days trading horizon SOFTWARE MANSION SPOLKA is expected to generate 0.62 times more return on investment than Gaming Factory. However, SOFTWARE MANSION SPOLKA is 1.62 times less risky than Gaming Factory. It trades about -0.05 of its potential returns per unit of risk. Gaming Factory SA is currently generating about -0.07 per unit of risk. If you would invest 3,400 in SOFTWARE MANSION SPOLKA on September 9, 2024 and sell it today you would lose (280.00) from holding SOFTWARE MANSION SPOLKA or give up 8.24% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 93.75% |
Values | Daily Returns |
SOFTWARE MANSION SPOLKA vs. Gaming Factory SA
Performance |
Timeline |
SOFTWARE MANSION SPOLKA |
Gaming Factory SA |
SOFTWARE MANSION and Gaming Factory Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with SOFTWARE MANSION and Gaming Factory
The main advantage of trading using opposite SOFTWARE MANSION and Gaming Factory positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if SOFTWARE MANSION position performs unexpectedly, Gaming Factory 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 Gaming Factory will offset losses from the drop in Gaming Factory'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 Portfolio Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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