Correlation Between AMAG Austria and Dow Jones
Can any of the company-specific risk be diversified away by investing in both AMAG Austria and Dow Jones 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 AMAG Austria and Dow Jones into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between AMAG Austria Metall and Dow Jones Industrial, you can compare the effects of market volatilities on AMAG Austria and Dow Jones 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 AMAG Austria with a short position of Dow Jones. Check out your portfolio center. Please also check ongoing floating volatility patterns of AMAG Austria and Dow Jones.
Diversification Opportunities for AMAG Austria and Dow Jones
-0.22 | Correlation Coefficient |
Very good diversification
The 3 months correlation between AMAG and Dow is -0.22. Overlapping area represents the amount of risk that can be diversified away by holding AMAG Austria Metall and Dow Jones Industrial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dow Jones Industrial and AMAG Austria 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 AMAG Austria Metall are associated (or correlated) with Dow Jones. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dow Jones Industrial has no effect on the direction of AMAG Austria i.e., AMAG Austria and Dow Jones go up and down completely randomly.
Pair Corralation between AMAG Austria and Dow Jones
Assuming the 90 days horizon AMAG Austria Metall is expected to generate 3.17 times more return on investment than Dow Jones. However, AMAG Austria is 3.17 times more volatile than Dow Jones Industrial. It trades about 0.12 of its potential returns per unit of risk. Dow Jones Industrial is currently generating about -0.21 per unit of risk. If you would invest 2,270 in AMAG Austria Metall on September 25, 2024 and sell it today you would earn a total of 120.00 from holding AMAG Austria Metall or generate 5.29% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
AMAG Austria Metall vs. Dow Jones Industrial
Performance |
| Timeline |
AMAG Austria and Dow Jones Volatility Contrast
Predicted Return Density |
| Returns |
AMAG Austria Metall
Pair trading matchups for AMAG Austria
Dow Jones Industrial
Pair trading matchups for Dow Jones
Pair Trading with AMAG Austria and Dow Jones
The main advantage of trading using opposite AMAG Austria and Dow Jones positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if AMAG Austria position performs unexpectedly, Dow Jones 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 Dow Jones will offset losses from the drop in Dow Jones' long position.| AMAG Austria vs. Norsk Hydro ASA | AMAG Austria vs. Norsk Hydro ASA | AMAG Austria vs. Alcoa Corp | AMAG Austria vs. Kaiser Aluminum |
| Dow Jones vs. Sabre Corpo | Dow Jones vs. Cannae Holdings | Dow Jones vs. Pekin Life Insurance | Dow Jones vs. Supercom |
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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