Correlation Between Shinhan Financial and Bosung Power
Can any of the company-specific risk be diversified away by investing in both Shinhan Financial and Bosung Power 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 Shinhan Financial and Bosung Power into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Shinhan Financial Group and Bosung Power Technology, you can compare the effects of market volatilities on Shinhan Financial and Bosung Power 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 Shinhan Financial with a short position of Bosung Power. Check out your portfolio center. Please also check ongoing floating volatility patterns of Shinhan Financial and Bosung Power.
Diversification Opportunities for Shinhan Financial and Bosung Power
0.8 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Shinhan and Bosung is 0.8. Overlapping area represents the amount of risk that can be diversified away by holding Shinhan Financial Group and Bosung Power Technology in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bosung Power Technology and Shinhan Financial 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 Shinhan Financial Group are associated (or correlated) with Bosung Power. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bosung Power Technology has no effect on the direction of Shinhan Financial i.e., Shinhan Financial and Bosung Power go up and down completely randomly.
Pair Corralation between Shinhan Financial and Bosung Power
Assuming the 90 days trading horizon Shinhan Financial Group is expected to generate 0.87 times more return on investment than Bosung Power. However, Shinhan Financial Group is 1.15 times less risky than Bosung Power. It trades about -0.08 of its potential returns per unit of risk. Bosung Power Technology is currently generating about -0.12 per unit of risk. If you would invest 5,620,000 in Shinhan Financial Group on September 27, 2024 and sell it today you would lose (680,000) from holding Shinhan Financial Group or give up 12.1% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Shinhan Financial Group vs. Bosung Power Technology
Performance |
Timeline |
Shinhan Financial |
Bosung Power Technology |
Shinhan Financial and Bosung Power Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Shinhan Financial and Bosung Power
The main advantage of trading using opposite Shinhan Financial and Bosung Power positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Shinhan Financial position performs unexpectedly, Bosung Power 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 Bosung Power will offset losses from the drop in Bosung Power's long position.Shinhan Financial vs. Kukdong Oil Chemicals | Shinhan Financial vs. LG Chemicals | Shinhan Financial vs. ABOV Semiconductor Co | Shinhan Financial vs. SK Chemicals Co |
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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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