Correlation Between Kuala Lumpur and Sime Darby
Can any of the company-specific risk be diversified away by investing in both Kuala Lumpur and Sime Darby 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 Kuala Lumpur and Sime Darby into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Kuala Lumpur Kepong and Sime Darby Bhd, you can compare the effects of market volatilities on Kuala Lumpur and Sime Darby 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 Kuala Lumpur with a short position of Sime Darby. Check out your portfolio center. Please also check ongoing floating volatility patterns of Kuala Lumpur and Sime Darby.
Diversification Opportunities for Kuala Lumpur and Sime Darby
-0.35 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Kuala and Sime is -0.35. Overlapping area represents the amount of risk that can be diversified away by holding Kuala Lumpur Kepong and Sime Darby Bhd in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Sime Darby Bhd and Kuala Lumpur 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 Kuala Lumpur Kepong are associated (or correlated) with Sime Darby. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Sime Darby Bhd has no effect on the direction of Kuala Lumpur i.e., Kuala Lumpur and Sime Darby go up and down completely randomly.
Pair Corralation between Kuala Lumpur and Sime Darby
Assuming the 90 days trading horizon Kuala Lumpur Kepong is expected to generate 0.42 times more return on investment than Sime Darby. However, Kuala Lumpur Kepong is 2.36 times less risky than Sime Darby. It trades about -0.24 of its potential returns per unit of risk. Sime Darby Bhd is currently generating about -0.41 per unit of risk. If you would invest 2,166 in Kuala Lumpur Kepong on October 16, 2024 and sell it today you would lose (56.00) from holding Kuala Lumpur Kepong or give up 2.59% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Kuala Lumpur Kepong vs. Sime Darby Bhd
Performance |
Timeline |
Kuala Lumpur Kepong |
Sime Darby Bhd |
Kuala Lumpur and Sime Darby Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Kuala Lumpur and Sime Darby
The main advantage of trading using opposite Kuala Lumpur and Sime Darby positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Kuala Lumpur position performs unexpectedly, Sime Darby 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 Sime Darby will offset losses from the drop in Sime Darby's long position.Kuala Lumpur vs. Alliance Financial Group | Kuala Lumpur vs. British American Tobacco | Kuala Lumpur vs. Binasat Communications Bhd | Kuala Lumpur vs. YX Precious Metals |
Sime Darby vs. Central Industrial Corp | Sime Darby vs. Cosmos Technology International | Sime Darby vs. CPE Technology Berhad | Sime Darby vs. Mercury Industries Bhd |
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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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