Correlation Between METISA Metalrgica and Electro Ao
Can any of the company-specific risk be diversified away by investing in both METISA Metalrgica and Electro Ao 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 METISA Metalrgica and Electro Ao into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between METISA Metalrgica Timboense and Electro Ao Altona, you can compare the effects of market volatilities on METISA Metalrgica and Electro Ao 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 METISA Metalrgica with a short position of Electro Ao. Check out your portfolio center. Please also check ongoing floating volatility patterns of METISA Metalrgica and Electro Ao.
Diversification Opportunities for METISA Metalrgica and Electro Ao
-0.04 | Correlation Coefficient |
Good diversification
The 3 months correlation between METISA and Electro is -0.04. Overlapping area represents the amount of risk that can be diversified away by holding METISA Metalrgica Timboense and Electro Ao Altona in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Electro Ao Altona and METISA Metalrgica 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 METISA Metalrgica Timboense are associated (or correlated) with Electro Ao. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Electro Ao Altona has no effect on the direction of METISA Metalrgica i.e., METISA Metalrgica and Electro Ao go up and down completely randomly.
Pair Corralation between METISA Metalrgica and Electro Ao
Assuming the 90 days trading horizon METISA Metalrgica is expected to generate 10.74 times less return on investment than Electro Ao. In addition to that, METISA Metalrgica is 1.22 times more volatile than Electro Ao Altona. It trades about 0.01 of its total potential returns per unit of risk. Electro Ao Altona is currently generating about 0.08 per unit of volatility. If you would invest 604.00 in Electro Ao Altona on September 23, 2024 and sell it today you would earn a total of 710.00 from holding Electro Ao Altona or generate 117.55% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
METISA Metalrgica Timboense vs. Electro Ao Altona
Performance |
Timeline |
METISA Metalrgica |
Electro Ao Altona |
METISA Metalrgica and Electro Ao Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with METISA Metalrgica and Electro Ao
The main advantage of trading using opposite METISA Metalrgica and Electro Ao positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if METISA Metalrgica position performs unexpectedly, Electro Ao 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 Electro Ao will offset losses from the drop in Electro Ao's long position.METISA Metalrgica vs. Schulz SA | METISA Metalrgica vs. Fras le SA | METISA Metalrgica vs. PBG SA | METISA Metalrgica vs. Springs Global Participaes |
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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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