Correlation Between IPC MEXICO and OMX Copenhagen

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Can any of the company-specific risk be diversified away by investing in both IPC MEXICO and OMX Copenhagen 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 IPC MEXICO and OMX Copenhagen into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between IPC MEXICO and OMX Copenhagen All, you can compare the effects of market volatilities on IPC MEXICO and OMX Copenhagen 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 IPC MEXICO with a short position of OMX Copenhagen. Check out your portfolio center. Please also check ongoing floating volatility patterns of IPC MEXICO and OMX Copenhagen.

Diversification Opportunities for IPC MEXICO and OMX Copenhagen

0.56
  Correlation Coefficient

Very weak diversification

The 3 months correlation between IPC and OMX is 0.56. Overlapping area represents the amount of risk that can be diversified away by holding IPC MEXICO and OMX Copenhagen All in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on OMX Copenhagen All and IPC MEXICO 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 IPC MEXICO are associated (or correlated) with OMX Copenhagen. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of OMX Copenhagen All has no effect on the direction of IPC MEXICO i.e., IPC MEXICO and OMX Copenhagen go up and down completely randomly.
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Pair Corralation between IPC MEXICO and OMX Copenhagen

Assuming the 90 days trading horizon IPC MEXICO is expected to generate 0.76 times more return on investment than OMX Copenhagen. However, IPC MEXICO is 1.32 times less risky than OMX Copenhagen. It trades about -0.1 of its potential returns per unit of risk. OMX Copenhagen All is currently generating about -0.18 per unit of risk. If you would invest  5,291,350  in IPC MEXICO on August 30, 2024 and sell it today you would lose (307,853) from holding IPC MEXICO or give up 5.82% of portfolio value over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthWeak
Accuracy100.0%
ValuesDaily Returns

IPC MEXICO  vs.  OMX Copenhagen All

 Performance 
       Timeline  

IPC MEXICO and OMX Copenhagen Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with IPC MEXICO and OMX Copenhagen

The main advantage of trading using opposite IPC MEXICO and OMX Copenhagen positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if IPC MEXICO position performs unexpectedly, OMX Copenhagen 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 OMX Copenhagen will offset losses from the drop in OMX Copenhagen's long position.
The idea behind IPC MEXICO and OMX Copenhagen All pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.
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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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