Correlation Between Damsan JSC and Ducgiang Chemicals
Can any of the company-specific risk be diversified away by investing in both Damsan JSC and Ducgiang Chemicals 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 Damsan JSC and Ducgiang Chemicals into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Damsan JSC and Ducgiang Chemicals Detergent, you can compare the effects of market volatilities on Damsan JSC and Ducgiang Chemicals 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 Damsan JSC with a short position of Ducgiang Chemicals. Check out your portfolio center. Please also check ongoing floating volatility patterns of Damsan JSC and Ducgiang Chemicals.
Diversification Opportunities for Damsan JSC and Ducgiang Chemicals
-0.17 | Correlation Coefficient |
Good diversification
The 3 months correlation between Damsan and Ducgiang is -0.17. Overlapping area represents the amount of risk that can be diversified away by holding Damsan JSC and Ducgiang Chemicals Detergent in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Ducgiang Chemicals and Damsan JSC 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 Damsan JSC are associated (or correlated) with Ducgiang Chemicals. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Ducgiang Chemicals has no effect on the direction of Damsan JSC i.e., Damsan JSC and Ducgiang Chemicals go up and down completely randomly.
Pair Corralation between Damsan JSC and Ducgiang Chemicals
Assuming the 90 days trading horizon Damsan JSC is expected to generate 1.56 times more return on investment than Ducgiang Chemicals. However, Damsan JSC is 1.56 times more volatile than Ducgiang Chemicals Detergent. It trades about 0.03 of its potential returns per unit of risk. Ducgiang Chemicals Detergent is currently generating about 0.03 per unit of risk. If you would invest 922,000 in Damsan JSC on December 2, 2024 and sell it today you would earn a total of 25,000 from holding Damsan JSC or generate 2.71% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Damsan JSC vs. Ducgiang Chemicals Detergent
Performance |
Timeline |
Damsan JSC |
Ducgiang Chemicals |
Damsan JSC and Ducgiang Chemicals Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Damsan JSC and Ducgiang Chemicals
The main advantage of trading using opposite Damsan JSC and Ducgiang Chemicals positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Damsan JSC position performs unexpectedly, Ducgiang Chemicals 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 Ducgiang Chemicals will offset losses from the drop in Ducgiang Chemicals' long position.Damsan JSC vs. Elcom Technology Communications | Damsan JSC vs. Ducgiang Chemicals Detergent | Damsan JSC vs. Innovative Technology Development | Damsan JSC vs. PostTelecommunication Equipment |
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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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