Correlation Between HANA Micron and SKONEC Entertainment
Can any of the company-specific risk be diversified away by investing in both HANA Micron and SKONEC Entertainment 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 HANA Micron and SKONEC Entertainment into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between HANA Micron and SKONEC Entertainment Co, you can compare the effects of market volatilities on HANA Micron and SKONEC Entertainment 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 HANA Micron with a short position of SKONEC Entertainment. Check out your portfolio center. Please also check ongoing floating volatility patterns of HANA Micron and SKONEC Entertainment.
Diversification Opportunities for HANA Micron and SKONEC Entertainment
0.79 | Correlation Coefficient |
Poor diversification
The 3 months correlation between HANA and SKONEC is 0.79. Overlapping area represents the amount of risk that can be diversified away by holding HANA Micron and SKONEC Entertainment Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SKONEC Entertainment and HANA Micron 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 HANA Micron are associated (or correlated) with SKONEC Entertainment. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SKONEC Entertainment has no effect on the direction of HANA Micron i.e., HANA Micron and SKONEC Entertainment go up and down completely randomly.
Pair Corralation between HANA Micron and SKONEC Entertainment
Assuming the 90 days trading horizon HANA Micron is expected to under-perform the SKONEC Entertainment. But the stock apears to be less risky and, when comparing its historical volatility, HANA Micron is 1.11 times less risky than SKONEC Entertainment. The stock trades about -0.1 of its potential returns per unit of risk. The SKONEC Entertainment Co is currently generating about -0.07 of returns per unit of risk over similar time horizon. If you would invest 721,000 in SKONEC Entertainment Co on September 13, 2024 and sell it today you would lose (428,500) from holding SKONEC Entertainment Co or give up 59.43% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
HANA Micron vs. SKONEC Entertainment Co
Performance |
Timeline |
HANA Micron |
SKONEC Entertainment |
HANA Micron and SKONEC Entertainment Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with HANA Micron and SKONEC Entertainment
The main advantage of trading using opposite HANA Micron and SKONEC Entertainment positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if HANA Micron position performs unexpectedly, SKONEC Entertainment 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 SKONEC Entertainment will offset losses from the drop in SKONEC Entertainment's long position.HANA Micron vs. SKONEC Entertainment Co | HANA Micron vs. MEDIANA CoLtd | HANA Micron vs. T3 Entertainment Co | HANA Micron vs. Genie Music |
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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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