Correlation Between AeroSpace Technology and Dong A
Can any of the company-specific risk be diversified away by investing in both AeroSpace Technology and Dong A 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 AeroSpace Technology and Dong A into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between AeroSpace Technology of and Dong A Steel Technology, you can compare the effects of market volatilities on AeroSpace Technology and Dong A 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 AeroSpace Technology with a short position of Dong A. Check out your portfolio center. Please also check ongoing floating volatility patterns of AeroSpace Technology and Dong A.
Diversification Opportunities for AeroSpace Technology and Dong A
0.22 | Correlation Coefficient |
Modest diversification
The 3 months correlation between AeroSpace and Dong is 0.22. Overlapping area represents the amount of risk that can be diversified away by holding AeroSpace Technology of and Dong A Steel Technology in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dong A Steel and AeroSpace Technology 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 AeroSpace Technology of are associated (or correlated) with Dong A. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dong A Steel has no effect on the direction of AeroSpace Technology i.e., AeroSpace Technology and Dong A go up and down completely randomly.
Pair Corralation between AeroSpace Technology and Dong A
Assuming the 90 days trading horizon AeroSpace Technology of is expected to under-perform the Dong A. But the stock apears to be less risky and, when comparing its historical volatility, AeroSpace Technology of is 2.13 times less risky than Dong A. The stock trades about -0.13 of its potential returns per unit of risk. The Dong A Steel Technology is currently generating about -0.01 of returns per unit of risk over similar time horizon. If you would invest 309,815 in Dong A Steel Technology on October 8, 2024 and sell it today you would lose (17,315) from holding Dong A Steel Technology or give up 5.59% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
AeroSpace Technology of vs. Dong A Steel Technology
Performance |
Timeline |
AeroSpace Technology |
Dong A Steel |
AeroSpace Technology and Dong A Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with AeroSpace Technology and Dong A
The main advantage of trading using opposite AeroSpace Technology and Dong A positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if AeroSpace Technology position performs unexpectedly, Dong A 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 Dong A will offset losses from the drop in Dong A's long position.AeroSpace Technology vs. Sajo Seafood | AeroSpace Technology vs. Handok Clean Tech | AeroSpace Technology vs. Hyundai Green Food | AeroSpace Technology vs. Nable Communications |
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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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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