Correlation Between Bosung Power and Sungwoo Techron
Can any of the company-specific risk be diversified away by investing in both Bosung Power and Sungwoo Techron 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 Bosung Power and Sungwoo Techron into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bosung Power Technology and Sungwoo Techron CoLtd, you can compare the effects of market volatilities on Bosung Power and Sungwoo Techron 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 Bosung Power with a short position of Sungwoo Techron. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bosung Power and Sungwoo Techron.
Diversification Opportunities for Bosung Power and Sungwoo Techron
0.44 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Bosung and Sungwoo is 0.44. Overlapping area represents the amount of risk that can be diversified away by holding Bosung Power Technology and Sungwoo Techron CoLtd in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Sungwoo Techron CoLtd and Bosung Power 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 Bosung Power Technology are associated (or correlated) with Sungwoo Techron. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Sungwoo Techron CoLtd has no effect on the direction of Bosung Power i.e., Bosung Power and Sungwoo Techron go up and down completely randomly.
Pair Corralation between Bosung Power and Sungwoo Techron
Assuming the 90 days trading horizon Bosung Power Technology is expected to under-perform the Sungwoo Techron. In addition to that, Bosung Power is 1.17 times more volatile than Sungwoo Techron CoLtd. It trades about -0.02 of its total potential returns per unit of risk. Sungwoo Techron CoLtd is currently generating about -0.01 per unit of volatility. If you would invest 392,037 in Sungwoo Techron CoLtd on October 10, 2024 and sell it today you would lose (95,037) from holding Sungwoo Techron CoLtd or give up 24.24% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Bosung Power Technology vs. Sungwoo Techron CoLtd
Performance |
Timeline |
Bosung Power Technology |
Sungwoo Techron CoLtd |
Bosung Power and Sungwoo Techron Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Bosung Power and Sungwoo Techron
The main advantage of trading using opposite Bosung Power and Sungwoo Techron positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bosung Power position performs unexpectedly, Sungwoo Techron 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 Sungwoo Techron will offset losses from the drop in Sungwoo Techron's long position.Bosung Power vs. Woori Financial Group | Bosung Power vs. Jb Financial | Bosung Power vs. Nh Investment And | Bosung Power vs. Hyundai Heavy Industries |
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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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