Correlation Between Bosung Power and Sungchang Autotech
Can any of the company-specific risk be diversified away by investing in both Bosung Power and Sungchang Autotech 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 Sungchang Autotech 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 Sungchang Autotech Co, you can compare the effects of market volatilities on Bosung Power and Sungchang Autotech 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 Sungchang Autotech. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bosung Power and Sungchang Autotech.
Diversification Opportunities for Bosung Power and Sungchang Autotech
0.68 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Bosung and Sungchang is 0.68. Overlapping area represents the amount of risk that can be diversified away by holding Bosung Power Technology and Sungchang Autotech Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Sungchang Autotech 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 Sungchang Autotech. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Sungchang Autotech has no effect on the direction of Bosung Power i.e., Bosung Power and Sungchang Autotech go up and down completely randomly.
Pair Corralation between Bosung Power and Sungchang Autotech
Assuming the 90 days trading horizon Bosung Power Technology is expected to generate 1.56 times more return on investment than Sungchang Autotech. However, Bosung Power is 1.56 times more volatile than Sungchang Autotech Co. It trades about 0.0 of its potential returns per unit of risk. Sungchang Autotech Co is currently generating about -0.07 per unit of risk. If you would invest 410,000 in Bosung Power Technology on October 29, 2024 and sell it today you would lose (101,000) from holding Bosung Power Technology or give up 24.63% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Bosung Power Technology vs. Sungchang Autotech Co
Performance |
| Timeline |
| Bosung Power Technology |
| Sungchang Autotech |
Bosung Power and Sungchang Autotech Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Bosung Power and Sungchang Autotech
The main advantage of trading using opposite Bosung Power and Sungchang Autotech positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bosung Power position performs unexpectedly, Sungchang Autotech 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 Sungchang Autotech will offset losses from the drop in Sungchang Autotech's long position.| Bosung Power vs. DRB Industrial Co | Bosung Power vs. Pan Entertainment Co | Bosung Power vs. Industrial Bank | Bosung Power vs. Cube Entertainment |
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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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