Correlation Between Sungchang Autotech and Nam Hwa
Can any of the company-specific risk be diversified away by investing in both Sungchang Autotech and Nam Hwa 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 Sungchang Autotech and Nam Hwa into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Sungchang Autotech Co and Nam Hwa Construction, you can compare the effects of market volatilities on Sungchang Autotech and Nam Hwa 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 Sungchang Autotech with a short position of Nam Hwa. Check out your portfolio center. Please also check ongoing floating volatility patterns of Sungchang Autotech and Nam Hwa.
Diversification Opportunities for Sungchang Autotech and Nam Hwa
-0.2 | Correlation Coefficient |
Good diversification
The 3 months correlation between Sungchang and Nam is -0.2. Overlapping area represents the amount of risk that can be diversified away by holding Sungchang Autotech Co and Nam Hwa Construction in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Nam Hwa Construction and Sungchang Autotech 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 Sungchang Autotech Co are associated (or correlated) with Nam Hwa. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Nam Hwa Construction has no effect on the direction of Sungchang Autotech i.e., Sungchang Autotech and Nam Hwa go up and down completely randomly.
Pair Corralation between Sungchang Autotech and Nam Hwa
Assuming the 90 days trading horizon Sungchang Autotech Co is expected to under-perform the Nam Hwa. But the stock apears to be less risky and, when comparing its historical volatility, Sungchang Autotech Co is 1.3 times less risky than Nam Hwa. The stock trades about -0.07 of its potential returns per unit of risk. The Nam Hwa Construction is currently generating about 0.06 of returns per unit of risk over similar time horizon. If you would invest 402,000 in Nam Hwa Construction on September 22, 2024 and sell it today you would earn a total of 33,000 from holding Nam Hwa Construction or generate 8.21% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Sungchang Autotech Co vs. Nam Hwa Construction
Performance |
Timeline |
Sungchang Autotech |
Nam Hwa Construction |
Sungchang Autotech and Nam Hwa Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Sungchang Autotech and Nam Hwa
The main advantage of trading using opposite Sungchang Autotech and Nam Hwa positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Sungchang Autotech position performs unexpectedly, Nam Hwa 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 Nam Hwa will offset losses from the drop in Nam Hwa's long position.Sungchang Autotech vs. Woori Technology Investment | Sungchang Autotech vs. Samsung Card Co | Sungchang Autotech vs. Korea Real Estate | Sungchang Autotech vs. CHOROKBAEM PANY 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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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