Correlation Between Koryo Credit and Daehan Steel
Can any of the company-specific risk be diversified away by investing in both Koryo Credit and Daehan Steel 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 Koryo Credit and Daehan Steel into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Koryo Credit Information and Daehan Steel, you can compare the effects of market volatilities on Koryo Credit and Daehan Steel 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 Koryo Credit with a short position of Daehan Steel. Check out your portfolio center. Please also check ongoing floating volatility patterns of Koryo Credit and Daehan Steel.
Diversification Opportunities for Koryo Credit and Daehan Steel
0.28 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Koryo and Daehan is 0.28. Overlapping area represents the amount of risk that can be diversified away by holding Koryo Credit Information and Daehan Steel in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Daehan Steel and Koryo Credit 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 Koryo Credit Information are associated (or correlated) with Daehan Steel. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Daehan Steel has no effect on the direction of Koryo Credit i.e., Koryo Credit and Daehan Steel go up and down completely randomly.
Pair Corralation between Koryo Credit and Daehan Steel
Assuming the 90 days trading horizon Koryo Credit is expected to generate 37.97 times less return on investment than Daehan Steel. But when comparing it to its historical volatility, Koryo Credit Information is 1.97 times less risky than Daehan Steel. It trades about 0.01 of its potential returns per unit of risk. Daehan Steel is currently generating about 0.22 of returns per unit of risk over similar time horizon. If you would invest 1,305,000 in Daehan Steel on September 21, 2024 and sell it today you would earn a total of 357,000 from holding Daehan Steel or generate 27.36% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Koryo Credit Information vs. Daehan Steel
Performance |
Timeline |
Koryo Credit Information |
Daehan Steel |
Koryo Credit and Daehan Steel Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Koryo Credit and Daehan Steel
The main advantage of trading using opposite Koryo Credit and Daehan Steel positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Koryo Credit position performs unexpectedly, Daehan Steel 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 Daehan Steel will offset losses from the drop in Daehan Steel's long position.Koryo Credit vs. CKH Food Health | Koryo Credit vs. BGF Retail Co | Koryo Credit vs. Shinsegae Food | Koryo Credit vs. Korean Reinsurance Co |
Daehan Steel vs. InfoBank | Daehan Steel vs. Korea Computer | Daehan Steel vs. Lotte Data Communication | Daehan Steel vs. Koryo Credit Information |
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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