Correlation Between SK TELECOM and Microbot Medical
Can any of the company-specific risk be diversified away by investing in both SK TELECOM and Microbot Medical 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 SK TELECOM and Microbot Medical into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between SK TELECOM TDADR and Microbot Medical, you can compare the effects of market volatilities on SK TELECOM and Microbot Medical 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 SK TELECOM with a short position of Microbot Medical. Check out your portfolio center. Please also check ongoing floating volatility patterns of SK TELECOM and Microbot Medical.
Diversification Opportunities for SK TELECOM and Microbot Medical
0.14 | Correlation Coefficient |
Average diversification
The 3 months correlation between KMBA and Microbot is 0.14. Overlapping area represents the amount of risk that can be diversified away by holding SK TELECOM TDADR and Microbot Medical in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Microbot Medical and SK TELECOM 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 SK TELECOM TDADR are associated (or correlated) with Microbot Medical. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Microbot Medical has no effect on the direction of SK TELECOM i.e., SK TELECOM and Microbot Medical go up and down completely randomly.
Pair Corralation between SK TELECOM and Microbot Medical
Assuming the 90 days trading horizon SK TELECOM TDADR is expected to generate 0.25 times more return on investment than Microbot Medical. However, SK TELECOM TDADR is 4.06 times less risky than Microbot Medical. It trades about 0.04 of its potential returns per unit of risk. Microbot Medical is currently generating about -0.01 per unit of risk. If you would invest 1,900 in SK TELECOM TDADR on September 2, 2024 and sell it today you would earn a total of 360.00 from holding SK TELECOM TDADR or generate 18.95% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
SK TELECOM TDADR vs. Microbot Medical
Performance |
| Timeline |
| SK TELECOM TDADR |
| Microbot Medical |
SK TELECOM and Microbot Medical Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with SK TELECOM and Microbot Medical
The main advantage of trading using opposite SK TELECOM and Microbot Medical positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if SK TELECOM position performs unexpectedly, Microbot Medical 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 Microbot Medical will offset losses from the drop in Microbot Medical's long position.| SK TELECOM vs. LG Display Co | SK TELECOM vs. United Airlines Holdings | SK TELECOM vs. Cleanaway Waste Management | SK TELECOM vs. PT Global Mediacom |
| Microbot Medical vs. Apple Inc | Microbot Medical vs. Apple Inc | Microbot Medical vs. Apple Inc | Microbot Medical vs. Apple Inc |
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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