Correlation Between Sime Darby and Cosmos Technology
Can any of the company-specific risk be diversified away by investing in both Sime Darby and Cosmos Technology 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 Sime Darby and Cosmos Technology into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Sime Darby Bhd and Cosmos Technology International, you can compare the effects of market volatilities on Sime Darby and Cosmos Technology 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 Sime Darby with a short position of Cosmos Technology. Check out your portfolio center. Please also check ongoing floating volatility patterns of Sime Darby and Cosmos Technology.
Diversification Opportunities for Sime Darby and Cosmos Technology
0.0 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Sime and Cosmos is 0.0. Overlapping area represents the amount of risk that can be diversified away by holding Sime Darby Bhd and Cosmos Technology Internationa in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Cosmos Technology and Sime Darby 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 Sime Darby Bhd are associated (or correlated) with Cosmos Technology. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Cosmos Technology has no effect on the direction of Sime Darby i.e., Sime Darby and Cosmos Technology go up and down completely randomly.
Pair Corralation between Sime Darby and Cosmos Technology
Assuming the 90 days trading horizon Sime Darby is expected to generate 19.02 times less return on investment than Cosmos Technology. But when comparing it to its historical volatility, Sime Darby Bhd is 1.18 times less risky than Cosmos Technology. It trades about 0.02 of its potential returns per unit of risk. Cosmos Technology International is currently generating about 0.33 of returns per unit of risk over similar time horizon. If you would invest 37.00 in Cosmos Technology International on September 29, 2024 and sell it today you would earn a total of 5.00 from holding Cosmos Technology International or generate 13.51% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Flat |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Sime Darby Bhd vs. Cosmos Technology Internationa
Performance |
Timeline |
Sime Darby Bhd |
Cosmos Technology |
Sime Darby and Cosmos Technology Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Sime Darby and Cosmos Technology
The main advantage of trading using opposite Sime Darby and Cosmos Technology positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Sime Darby position performs unexpectedly, Cosmos Technology 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 Cosmos Technology will offset losses from the drop in Cosmos Technology's long position.Sime Darby vs. Cosmos Technology International | Sime Darby vs. Melewar Industrial Group | Sime Darby vs. JF Technology BHD | Sime Darby vs. Uchi Technologies Bhd |
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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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