Correlation Between Sam Yang and Clean Science
Can any of the company-specific risk be diversified away by investing in both Sam Yang and Clean Science 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 Sam Yang and Clean Science into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Sam Yang Foods and Clean Science co, you can compare the effects of market volatilities on Sam Yang and Clean Science 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 Sam Yang with a short position of Clean Science. Check out your portfolio center. Please also check ongoing floating volatility patterns of Sam Yang and Clean Science.
Diversification Opportunities for Sam Yang and Clean Science
-0.11 | Correlation Coefficient |
Good diversification
The 3 months correlation between Sam and Clean is -0.11. Overlapping area represents the amount of risk that can be diversified away by holding Sam Yang Foods and Clean Science co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Clean Science co and Sam Yang 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 Sam Yang Foods are associated (or correlated) with Clean Science. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Clean Science co has no effect on the direction of Sam Yang i.e., Sam Yang and Clean Science go up and down completely randomly.
Pair Corralation between Sam Yang and Clean Science
Assuming the 90 days trading horizon Sam Yang Foods is expected to under-perform the Clean Science. But the stock apears to be less risky and, when comparing its historical volatility, Sam Yang Foods is 1.2 times less risky than Clean Science. The stock trades about -0.07 of its potential returns per unit of risk. The Clean Science co is currently generating about 0.26 of returns per unit of risk over similar time horizon. If you would invest 468,500 in Clean Science co on October 23, 2024 and sell it today you would earn a total of 54,500 from holding Clean Science co or generate 11.63% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Sam Yang Foods vs. Clean Science co
Performance |
Timeline |
Sam Yang Foods |
Clean Science co |
Sam Yang and Clean Science Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Sam Yang and Clean Science
The main advantage of trading using opposite Sam Yang and Clean Science positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Sam Yang position performs unexpectedly, Clean Science 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 Clean Science will offset losses from the drop in Clean Science's long position.Sam Yang vs. Han Kook Steel | Sam Yang vs. Husteel | Sam Yang vs. Hankuk Steel Wire | Sam Yang vs. Jin Air Co |
Clean Science vs. Formetal Co | Clean Science vs. Korea Investment Holdings | Clean Science vs. Innowireless Co | Clean Science vs. Industrial Bank |
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 Risk-Return Analysis module to view associations between returns expected from investment and the risk you assume.
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