Correlation Between Automobile and Hanmi Semiconductor
Can any of the company-specific risk be diversified away by investing in both Automobile and Hanmi Semiconductor 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 Automobile and Hanmi Semiconductor into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Automobile Pc and Hanmi Semiconductor Co, you can compare the effects of market volatilities on Automobile and Hanmi Semiconductor 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 Automobile with a short position of Hanmi Semiconductor. Check out your portfolio center. Please also check ongoing floating volatility patterns of Automobile and Hanmi Semiconductor.
Diversification Opportunities for Automobile and Hanmi Semiconductor
0.4 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Automobile and Hanmi is 0.4. Overlapping area represents the amount of risk that can be diversified away by holding Automobile Pc and Hanmi Semiconductor Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Hanmi Semiconductor and Automobile 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 Automobile Pc are associated (or correlated) with Hanmi Semiconductor. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Hanmi Semiconductor has no effect on the direction of Automobile i.e., Automobile and Hanmi Semiconductor go up and down completely randomly.
Pair Corralation between Automobile and Hanmi Semiconductor
Assuming the 90 days trading horizon Automobile Pc is expected to under-perform the Hanmi Semiconductor. But the stock apears to be less risky and, when comparing its historical volatility, Automobile Pc is 1.38 times less risky than Hanmi Semiconductor. The stock trades about -0.04 of its potential returns per unit of risk. The Hanmi Semiconductor Co is currently generating about 0.12 of returns per unit of risk over similar time horizon. If you would invest 1,304,196 in Hanmi Semiconductor Co on October 11, 2024 and sell it today you would earn a total of 10,275,804 from holding Hanmi Semiconductor Co or generate 787.9% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Automobile Pc vs. Hanmi Semiconductor Co
Performance |
Timeline |
Automobile Pc |
Hanmi Semiconductor |
Automobile and Hanmi Semiconductor Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Automobile and Hanmi Semiconductor
The main advantage of trading using opposite Automobile and Hanmi Semiconductor positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Automobile position performs unexpectedly, Hanmi Semiconductor 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 Hanmi Semiconductor will offset losses from the drop in Hanmi Semiconductor's long position.Automobile vs. Kbi Metal Co | Automobile vs. Daejung Chemicals Metals | Automobile vs. Sungmoon Electronics Co | Automobile vs. KyungIn Electronics Co |
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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 Volatility Analysis module to get historical volatility and risk analysis based on latest market data.
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