Correlation Between OMX Helsinki and Harvia Oyj

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Can any of the company-specific risk be diversified away by investing in both OMX Helsinki and Harvia Oyj 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 Helsinki and Harvia Oyj into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between OMX Helsinki 25 and Harvia Oyj, you can compare the effects of market volatilities on OMX Helsinki and Harvia Oyj 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 Helsinki with a short position of Harvia Oyj. Check out your portfolio center. Please also check ongoing floating volatility patterns of OMX Helsinki and Harvia Oyj.

Diversification Opportunities for OMX Helsinki and Harvia Oyj

0.32
  Correlation Coefficient

Weak diversification

The 3 months correlation between OMX and Harvia is 0.32. Overlapping area represents the amount of risk that can be diversified away by holding OMX Helsinki 25 and Harvia Oyj in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Harvia Oyj and OMX Helsinki 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 Helsinki 25 are associated (or correlated) with Harvia Oyj. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Harvia Oyj has no effect on the direction of OMX Helsinki i.e., OMX Helsinki and Harvia Oyj go up and down completely randomly.
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Pair Corralation between OMX Helsinki and Harvia Oyj

Assuming the 90 days trading horizon OMX Helsinki 25 is expected to under-perform the Harvia Oyj. But the index apears to be less risky and, when comparing its historical volatility, OMX Helsinki 25 is 2.84 times less risky than Harvia Oyj. The index trades about -0.03 of its potential returns per unit of risk. The Harvia Oyj is currently generating about 0.09 of returns per unit of risk over similar time horizon. If you would invest  1,832  in Harvia Oyj on August 31, 2024 and sell it today you would earn a total of  2,548  from holding Harvia Oyj or generate 139.08% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthVery Weak
Accuracy99.79%
ValuesDaily Returns

OMX Helsinki 25  vs.  Harvia Oyj

 Performance 
       Timeline  

OMX Helsinki and Harvia Oyj Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with OMX Helsinki and Harvia Oyj

The main advantage of trading using opposite OMX Helsinki and Harvia Oyj positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if OMX Helsinki position performs unexpectedly, Harvia Oyj 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 Harvia Oyj will offset losses from the drop in Harvia Oyj's long position.
The idea behind OMX Helsinki 25 and Harvia Oyj 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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.

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