Correlation Between Cosmos Technology and Systech Bhd
Can any of the company-specific risk be diversified away by investing in both Cosmos Technology and Systech Bhd 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 Cosmos Technology and Systech Bhd into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Cosmos Technology International and Systech Bhd, you can compare the effects of market volatilities on Cosmos Technology and Systech Bhd 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 Cosmos Technology with a short position of Systech Bhd. Check out your portfolio center. Please also check ongoing floating volatility patterns of Cosmos Technology and Systech Bhd.
Diversification Opportunities for Cosmos Technology and Systech Bhd
0.39 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Cosmos and Systech is 0.39. Overlapping area represents the amount of risk that can be diversified away by holding Cosmos Technology Internationa and Systech Bhd in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Systech Bhd and Cosmos Technology 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 Cosmos Technology International are associated (or correlated) with Systech Bhd. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Systech Bhd has no effect on the direction of Cosmos Technology i.e., Cosmos Technology and Systech Bhd go up and down completely randomly.
Pair Corralation between Cosmos Technology and Systech Bhd
Assuming the 90 days trading horizon Cosmos Technology is expected to generate 1.49 times less return on investment than Systech Bhd. But when comparing it to its historical volatility, Cosmos Technology International is 1.91 times less risky than Systech Bhd. It trades about 0.18 of its potential returns per unit of risk. Systech Bhd is currently generating about 0.14 of returns per unit of risk over similar time horizon. If you would invest 26.00 in Systech Bhd on September 13, 2024 and sell it today you would earn a total of 2.00 from holding Systech Bhd or generate 7.69% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Cosmos Technology Internationa vs. Systech Bhd
Performance |
| Timeline |
| Cosmos Technology |
| Systech Bhd |
Cosmos Technology and Systech Bhd Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Cosmos Technology and Systech Bhd
The main advantage of trading using opposite Cosmos Technology and Systech Bhd positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Cosmos Technology position performs unexpectedly, Systech Bhd 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 Systech Bhd will offset losses from the drop in Systech Bhd's long position.| Cosmos Technology vs. K One Technology Bhd | Cosmos Technology vs. Globetronics Tech Bhd | Cosmos Technology vs. Uchi Technologies Bhd | Cosmos Technology vs. Kossan Rubber Industries |
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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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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