Correlation Between Daiyang Metal and KakaoBank Corp
Can any of the company-specific risk be diversified away by investing in both Daiyang Metal and KakaoBank Corp 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 Daiyang Metal and KakaoBank Corp into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Daiyang Metal Co and KakaoBank Corp, you can compare the effects of market volatilities on Daiyang Metal and KakaoBank Corp 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 Daiyang Metal with a short position of KakaoBank Corp. Check out your portfolio center. Please also check ongoing floating volatility patterns of Daiyang Metal and KakaoBank Corp.
Diversification Opportunities for Daiyang Metal and KakaoBank Corp
0.11 | Correlation Coefficient |
Average diversification
The 3 months correlation between Daiyang and KakaoBank is 0.11. Overlapping area represents the amount of risk that can be diversified away by holding Daiyang Metal Co and KakaoBank Corp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on KakaoBank Corp and Daiyang Metal 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 Daiyang Metal Co are associated (or correlated) with KakaoBank Corp. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of KakaoBank Corp has no effect on the direction of Daiyang Metal i.e., Daiyang Metal and KakaoBank Corp go up and down completely randomly.
Pair Corralation between Daiyang Metal and KakaoBank Corp
Assuming the 90 days trading horizon Daiyang Metal Co is expected to under-perform the KakaoBank Corp. In addition to that, Daiyang Metal is 1.6 times more volatile than KakaoBank Corp. It trades about -0.17 of its total potential returns per unit of risk. KakaoBank Corp is currently generating about 0.09 per unit of volatility. If you would invest 2,165,000 in KakaoBank Corp on September 1, 2024 and sell it today you would earn a total of 70,000 from holding KakaoBank Corp or generate 3.23% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Daiyang Metal Co vs. KakaoBank Corp
Performance |
| Timeline |
| Daiyang Metal |
| KakaoBank Corp |
Daiyang Metal and KakaoBank Corp Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Daiyang Metal and KakaoBank Corp
The main advantage of trading using opposite Daiyang Metal and KakaoBank Corp positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Daiyang Metal position performs unexpectedly, KakaoBank Corp 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 KakaoBank Corp will offset losses from the drop in KakaoBank Corp's long position.| Daiyang Metal vs. LG Household Healthcare | Daiyang Metal vs. Daejung Chemicals Metals | Daiyang Metal vs. LG Chemicals | Daiyang Metal vs. SK Chemicals Co |
| KakaoBank Corp vs. Shinhan Financial Group | KakaoBank Corp vs. Hana Financial | KakaoBank Corp vs. Woori Financial Group | KakaoBank Corp vs. Industrial Bank |
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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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