Correlation Between DB Financial and Shinhan WTI
Can any of the company-specific risk be diversified away by investing in both DB Financial and Shinhan WTI 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 DB Financial and Shinhan WTI into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between DB Financial Investment and Shinhan WTI Futures, you can compare the effects of market volatilities on DB Financial and Shinhan WTI 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 DB Financial with a short position of Shinhan WTI. Check out your portfolio center. Please also check ongoing floating volatility patterns of DB Financial and Shinhan WTI.
Diversification Opportunities for DB Financial and Shinhan WTI
-0.26 | Correlation Coefficient |
Very good diversification
The 3 months correlation between 016610 and Shinhan is -0.26. Overlapping area represents the amount of risk that can be diversified away by holding DB Financial Investment and Shinhan WTI Futures in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Shinhan WTI Futures and DB 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 DB Financial Investment are associated (or correlated) with Shinhan WTI. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Shinhan WTI Futures has no effect on the direction of DB Financial i.e., DB Financial and Shinhan WTI go up and down completely randomly.
Pair Corralation between DB Financial and Shinhan WTI
Assuming the 90 days trading horizon DB Financial Investment is expected to generate 1.33 times more return on investment than Shinhan WTI. However, DB Financial is 1.33 times more volatile than Shinhan WTI Futures. It trades about 0.02 of its potential returns per unit of risk. Shinhan WTI Futures is currently generating about -0.08 per unit of risk. If you would invest 517,000 in DB Financial Investment on September 12, 2024 and sell it today you would earn a total of 3,000 from holding DB Financial Investment or generate 0.58% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
DB Financial Investment vs. Shinhan WTI Futures
Performance |
| Timeline |
| DB Financial Investment |
| Shinhan WTI Futures |
DB Financial and Shinhan WTI Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with DB Financial and Shinhan WTI
The main advantage of trading using opposite DB Financial and Shinhan WTI positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if DB Financial position performs unexpectedly, Shinhan WTI 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 Shinhan WTI will offset losses from the drop in Shinhan WTI's long position.| DB Financial vs. KB Financial Group | DB Financial vs. Shinhan Financial Group | DB Financial vs. Hana Financial | DB Financial vs. Woori Financial Group |
| Shinhan WTI vs. Shinhan Financial Group | Shinhan WTI vs. Cuckoo Homesys Co | Shinhan WTI vs. Jb Financial | Shinhan WTI vs. LG Household Healthcare |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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