Correlation Between MClean Technologies and SSF Home
Can any of the company-specific risk be diversified away by investing in both MClean Technologies and SSF Home 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 MClean Technologies and SSF Home into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between MClean Technologies Bhd and SSF Home Group, you can compare the effects of market volatilities on MClean Technologies and SSF Home 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 MClean Technologies with a short position of SSF Home. Check out your portfolio center. Please also check ongoing floating volatility patterns of MClean Technologies and SSF Home.
Diversification Opportunities for MClean Technologies and SSF Home
0.26 | Correlation Coefficient |
Modest diversification
The 3 months correlation between MClean and SSF is 0.26. Overlapping area represents the amount of risk that can be diversified away by holding MClean Technologies Bhd and SSF Home Group in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SSF Home Group and MClean Technologies 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 MClean Technologies Bhd are associated (or correlated) with SSF Home. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SSF Home Group has no effect on the direction of MClean Technologies i.e., MClean Technologies and SSF Home go up and down completely randomly.
Pair Corralation between MClean Technologies and SSF Home
Assuming the 90 days trading horizon MClean Technologies Bhd is expected to generate 3.07 times more return on investment than SSF Home. However, MClean Technologies is 3.07 times more volatile than SSF Home Group. It trades about 0.06 of its potential returns per unit of risk. SSF Home Group is currently generating about 0.01 per unit of risk. If you would invest 28.00 in MClean Technologies Bhd on September 28, 2024 and sell it today you would earn a total of 3.00 from holding MClean Technologies Bhd or generate 10.71% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
MClean Technologies Bhd vs. SSF Home Group
Performance |
Timeline |
MClean Technologies Bhd |
SSF Home Group |
MClean Technologies and SSF Home Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with MClean Technologies and SSF Home
The main advantage of trading using opposite MClean Technologies and SSF Home positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if MClean Technologies position performs unexpectedly, SSF Home 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 SSF Home will offset losses from the drop in SSF Home's long position.MClean Technologies vs. Sports Toto Berhad | MClean Technologies vs. YX Precious Metals | MClean Technologies vs. Dataprep Holdings Bhd | MClean Technologies vs. JF Technology BHD |
SSF Home vs. JF Technology BHD | SSF Home vs. YX Precious Metals | SSF Home vs. Media Prima Bhd | SSF Home vs. Homeritz 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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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