Correlation Between OMX Copenhagen and Karachi 100

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Can any of the company-specific risk be diversified away by investing in both OMX Copenhagen and Karachi 100 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 OMX Copenhagen and Karachi 100 into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between OMX Copenhagen All and Karachi 100, you can compare the effects of market volatilities on OMX Copenhagen and Karachi 100 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 OMX Copenhagen with a short position of Karachi 100. Check out your portfolio center. Please also check ongoing floating volatility patterns of OMX Copenhagen and Karachi 100.

Diversification Opportunities for OMX Copenhagen and Karachi 100

0.41
  Correlation Coefficient

Very weak diversification

The 3 months correlation between OMX and Karachi is 0.41. Overlapping area represents the amount of risk that can be diversified away by holding OMX Copenhagen All and Karachi 100 in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Karachi 100 and OMX Copenhagen 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 OMX Copenhagen All are associated (or correlated) with Karachi 100. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Karachi 100 has no effect on the direction of OMX Copenhagen i.e., OMX Copenhagen and Karachi 100 go up and down completely randomly.
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Pair Corralation between OMX Copenhagen and Karachi 100

Assuming the 90 days trading horizon OMX Copenhagen is expected to generate 1.65 times less return on investment than Karachi 100. In addition to that, OMX Copenhagen is 1.28 times more volatile than Karachi 100. It trades about 0.13 of its total potential returns per unit of risk. Karachi 100 is currently generating about 0.27 per unit of volatility. If you would invest  6,481,647  in Karachi 100 on March 15, 2024 and sell it today you would earn a total of  798,096  from holding Karachi 100 or generate 12.31% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthWeak
Accuracy98.31%
ValuesDaily Returns

OMX Copenhagen All  vs.  Karachi 100

 Performance 
       Timeline  

OMX Copenhagen and Karachi 100 Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with OMX Copenhagen and Karachi 100

The main advantage of trading using opposite OMX Copenhagen and Karachi 100 positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if OMX Copenhagen position performs unexpectedly, Karachi 100 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 Karachi 100 will offset losses from the drop in Karachi 100's long position.
The idea behind OMX Copenhagen All and Karachi 100 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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.

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