Correlation Between Automobile and Young Poong
Can any of the company-specific risk be diversified away by investing in both Automobile and Young Poong 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 Young Poong into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Automobile Pc and Young Poong Corp, you can compare the effects of market volatilities on Automobile and Young Poong 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 Young Poong. Check out your portfolio center. Please also check ongoing floating volatility patterns of Automobile and Young Poong.
Diversification Opportunities for Automobile and Young Poong
0.01 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Automobile and Young is 0.01. Overlapping area represents the amount of risk that can be diversified away by holding Automobile Pc and Young Poong Corp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Young Poong Corp 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 Young Poong. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Young Poong Corp has no effect on the direction of Automobile i.e., Automobile and Young Poong go up and down completely randomly.
Pair Corralation between Automobile and Young Poong
Assuming the 90 days trading horizon Automobile Pc is expected to under-perform the Young Poong. But the stock apears to be less risky and, when comparing its historical volatility, Automobile Pc is 1.37 times less risky than Young Poong. The stock trades about -0.03 of its potential returns per unit of risk. The Young Poong Corp is currently generating about 0.15 of returns per unit of risk over similar time horizon. If you would invest 38,200,000 in Young Poong Corp on October 28, 2024 and sell it today you would earn a total of 3,150,000 from holding Young Poong Corp or generate 8.25% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Automobile Pc vs. Young Poong Corp
Performance |
| Timeline |
| Automobile Pc |
| Young Poong Corp |
Automobile and Young Poong Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Automobile and Young Poong
The main advantage of trading using opposite Automobile and Young Poong positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Automobile position performs unexpectedly, Young Poong 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 Young Poong will offset losses from the drop in Young Poong's long position.| Automobile vs. Samsung Electronics Co | Automobile vs. Samsung Electronics Co | Automobile vs. KB Financial Group | Automobile vs. Shinhan Financial Group |
| Young Poong vs. Samsung Electronics Co | Young Poong vs. Samsung Electronics Co | Young Poong vs. LG Energy Solution | Young Poong vs. SK Hynix |
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 Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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