Correlation Between Daewoo SBI and Daejoo Electronic
Can any of the company-specific risk be diversified away by investing in both Daewoo SBI and Daejoo Electronic 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 Daewoo SBI and Daejoo Electronic into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Daewoo SBI SPAC and Daejoo Electronic Materials, you can compare the effects of market volatilities on Daewoo SBI and Daejoo Electronic 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 Daewoo SBI with a short position of Daejoo Electronic. Check out your portfolio center. Please also check ongoing floating volatility patterns of Daewoo SBI and Daejoo Electronic.
Diversification Opportunities for Daewoo SBI and Daejoo Electronic
0.13 | Correlation Coefficient |
Average diversification
The 3 months correlation between Daewoo and Daejoo is 0.13. Overlapping area represents the amount of risk that can be diversified away by holding Daewoo SBI SPAC and Daejoo Electronic Materials in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Daejoo Electronic and Daewoo SBI 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 Daewoo SBI SPAC are associated (or correlated) with Daejoo Electronic. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Daejoo Electronic has no effect on the direction of Daewoo SBI i.e., Daewoo SBI and Daejoo Electronic go up and down completely randomly.
Pair Corralation between Daewoo SBI and Daejoo Electronic
Assuming the 90 days trading horizon Daewoo SBI SPAC is expected to under-perform the Daejoo Electronic. But the stock apears to be less risky and, when comparing its historical volatility, Daewoo SBI SPAC is 1.73 times less risky than Daejoo Electronic. The stock trades about -0.03 of its potential returns per unit of risk. The Daejoo Electronic Materials is currently generating about 0.01 of returns per unit of risk over similar time horizon. If you would invest 8,380,012 in Daejoo Electronic Materials on October 6, 2024 and sell it today you would lose (730,012) from holding Daejoo Electronic Materials or give up 8.71% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Daewoo SBI SPAC vs. Daejoo Electronic Materials
Performance |
Timeline |
Daewoo SBI SPAC |
Daejoo Electronic |
Daewoo SBI and Daejoo Electronic Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Daewoo SBI and Daejoo Electronic
The main advantage of trading using opposite Daewoo SBI and Daejoo Electronic positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Daewoo SBI position performs unexpectedly, Daejoo Electronic 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 Daejoo Electronic will offset losses from the drop in Daejoo Electronic's long position.Daewoo SBI vs. ITM Semiconductor Co | Daewoo SBI vs. ABOV Semiconductor Co | Daewoo SBI vs. Seers Technology | Daewoo SBI vs. Eagle Veterinary Technology |
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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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