Correlation Between Magic Software and Tel Aviv
Can any of the company-specific risk be diversified away by investing in both Magic Software and Tel Aviv 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 Magic Software and Tel Aviv into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Magic Software Enterprises and Tel Aviv 35, you can compare the effects of market volatilities on Magic Software and Tel Aviv 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 Magic Software with a short position of Tel Aviv. Check out your portfolio center. Please also check ongoing floating volatility patterns of Magic Software and Tel Aviv.
Diversification Opportunities for Magic Software and Tel Aviv
0.42 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Magic and Tel is 0.42. Overlapping area represents the amount of risk that can be diversified away by holding Magic Software Enterprises and Tel Aviv 35 in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Tel Aviv 35 and Magic Software 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 Magic Software Enterprises are associated (or correlated) with Tel Aviv. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Tel Aviv 35 has no effect on the direction of Magic Software i.e., Magic Software and Tel Aviv go up and down completely randomly.
Pair Corralation between Magic Software and Tel Aviv
Assuming the 90 days trading horizon Magic Software Enterprises is expected to generate 3.48 times more return on investment than Tel Aviv. However, Magic Software is 3.48 times more volatile than Tel Aviv 35. It trades about 0.08 of its potential returns per unit of risk. Tel Aviv 35 is currently generating about 0.17 per unit of risk. If you would invest 422,200 in Magic Software Enterprises on September 1, 2024 and sell it today you would earn a total of 15,200 from holding Magic Software Enterprises or generate 3.6% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Magic Software Enterprises vs. Tel Aviv 35
Performance |
| Timeline |
Magic Software and Tel Aviv Volatility Contrast
Predicted Return Density |
| Returns |
Magic Software Enterprises
Pair trading matchups for Magic Software
Tel Aviv 35
Pair trading matchups for Tel Aviv
Pair Trading with Magic Software and Tel Aviv
The main advantage of trading using opposite Magic Software and Tel Aviv positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Magic Software position performs unexpectedly, Tel Aviv 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 Tel Aviv will offset losses from the drop in Tel Aviv's long position.| Magic Software vs. Sapiens International | Magic Software vs. Matrix | Magic Software vs. Tower Semiconductor | Magic Software vs. Nova |
| Tel Aviv vs. YH Dimri Construction | Tel Aviv vs. Electreon Wireless | Tel Aviv vs. B Yair Building | Tel Aviv vs. One Software Technologies |
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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