Correlation Between OMX Stockholm and BEL Small

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

Diversification Opportunities for OMX Stockholm and BEL Small

0.86
  Correlation Coefficient

Very poor diversification

The 3 months correlation between OMX and BEL is 0.86. Overlapping area represents the amount of risk that can be diversified away by holding OMX Stockholm Mid and BEL Small in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on BEL Small and OMX Stockholm 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 Stockholm Mid are associated (or correlated) with BEL Small. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of BEL Small has no effect on the direction of OMX Stockholm i.e., OMX Stockholm and BEL Small go up and down completely randomly.
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Pair Corralation between OMX Stockholm and BEL Small

Assuming the 90 days trading horizon OMX Stockholm Mid is expected to generate 1.46 times more return on investment than BEL Small. However, OMX Stockholm is 1.46 times more volatile than BEL Small. It trades about -0.02 of its potential returns per unit of risk. BEL Small is currently generating about -0.18 per unit of risk. If you would invest  168,677  in OMX Stockholm Mid on September 1, 2024 and sell it today you would lose (5,190) from holding OMX Stockholm Mid or give up 3.08% of portfolio value over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthStrong
Accuracy100.0%
ValuesDaily Returns

OMX Stockholm Mid  vs.  BEL Small

 Performance 
       Timeline  

OMX Stockholm and BEL Small Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with OMX Stockholm and BEL Small

The main advantage of trading using opposite OMX Stockholm and BEL Small positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if OMX Stockholm position performs unexpectedly, BEL Small 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 BEL Small will offset losses from the drop in BEL Small's long position.
The idea behind OMX Stockholm Mid and BEL Small 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 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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