Correlation Between Doosan Fuel and Phoenix Materials
Can any of the company-specific risk be diversified away by investing in both Doosan Fuel and Phoenix Materials 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 Doosan Fuel and Phoenix Materials into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Doosan Fuel Cell and Phoenix Materials Co, you can compare the effects of market volatilities on Doosan Fuel and Phoenix Materials 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 Doosan Fuel with a short position of Phoenix Materials. Check out your portfolio center. Please also check ongoing floating volatility patterns of Doosan Fuel and Phoenix Materials.
Diversification Opportunities for Doosan Fuel and Phoenix Materials
0.18 | Correlation Coefficient |
Average diversification
The 3 months correlation between Doosan and Phoenix is 0.18. Overlapping area represents the amount of risk that can be diversified away by holding Doosan Fuel Cell and Phoenix Materials Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Phoenix Materials and Doosan Fuel 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 Doosan Fuel Cell are associated (or correlated) with Phoenix Materials. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Phoenix Materials has no effect on the direction of Doosan Fuel i.e., Doosan Fuel and Phoenix Materials go up and down completely randomly.
Pair Corralation between Doosan Fuel and Phoenix Materials
Assuming the 90 days trading horizon Doosan Fuel Cell is expected to under-perform the Phoenix Materials. But the stock apears to be less risky and, when comparing its historical volatility, Doosan Fuel Cell is 2.19 times less risky than Phoenix Materials. The stock trades about -0.03 of its potential returns per unit of risk. The Phoenix Materials Co is currently generating about 0.03 of returns per unit of risk over similar time horizon. If you would invest 65,900 in Phoenix Materials Co on December 2, 2024 and sell it today you would earn a total of 1,900 from holding Phoenix Materials Co or generate 2.88% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Doosan Fuel Cell vs. Phoenix Materials Co
Performance |
Timeline |
Doosan Fuel Cell |
Phoenix Materials |
Doosan Fuel and Phoenix Materials Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Doosan Fuel and Phoenix Materials
The main advantage of trading using opposite Doosan Fuel and Phoenix Materials positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Doosan Fuel position performs unexpectedly, Phoenix Materials 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 Phoenix Materials will offset losses from the drop in Phoenix Materials' long position.Doosan Fuel vs. Eagon Industrial Co | Doosan Fuel vs. Chorokbaem Healthcare Co | Doosan Fuel vs. Songwon Industrial Co | Doosan Fuel vs. Hyunwoo Industrial 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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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