Correlation Between Systech Bhd and KL Technology
Can any of the company-specific risk be diversified away by investing in both Systech Bhd and KL 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 Systech Bhd and KL Technology into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Systech Bhd and KL Technology, you can compare the effects of market volatilities on Systech Bhd and KL 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 Systech Bhd with a short position of KL Technology. Check out your portfolio center. Please also check ongoing floating volatility patterns of Systech Bhd and KL Technology.
Diversification Opportunities for Systech Bhd and KL Technology
0.45 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Systech and KLTE is 0.45. Overlapping area represents the amount of risk that can be diversified away by holding Systech Bhd and KL Technology in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on KL Technology and Systech Bhd 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 Systech Bhd are associated (or correlated) with KL Technology. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of KL Technology has no effect on the direction of Systech Bhd i.e., Systech Bhd and KL Technology go up and down completely randomly.
Pair Corralation between Systech Bhd and KL Technology
Assuming the 90 days trading horizon Systech Bhd is expected to generate 2.5 times more return on investment than KL Technology. However, Systech Bhd is 2.5 times more volatile than KL Technology. It trades about 0.05 of its potential returns per unit of risk. KL Technology is currently generating about 0.11 per unit of risk. If you would invest 31.00 in Systech Bhd on September 25, 2024 and sell it today you would earn a total of 2.00 from holding Systech Bhd or generate 6.45% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Systech Bhd vs. KL Technology
Performance |
Timeline |
Systech Bhd and KL Technology Volatility Contrast
Predicted Return Density |
Returns |
Systech Bhd
Pair trading matchups for Systech Bhd
KL Technology
Pair trading matchups for KL Technology
Pair Trading with Systech Bhd and KL Technology
The main advantage of trading using opposite Systech Bhd and KL Technology positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Systech Bhd position performs unexpectedly, KL 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 KL Technology will offset losses from the drop in KL Technology's long position.Systech Bhd vs. Impiana Hotels Bhd | Systech Bhd vs. Nova Wellness Group | Systech Bhd vs. YTL Hospitality REIT | Systech Bhd vs. Sungei Bagan Rubber |
KL Technology vs. Public Packages Holdings | KL Technology vs. Greatech Technology Bhd | KL Technology vs. Choo Bee Metal | KL Technology vs. Cosmos Technology International |
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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