Correlation Between WIG 30 and Austrian Traded

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Can any of the company-specific risk be diversified away by investing in both WIG 30 and Austrian Traded 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 WIG 30 and Austrian Traded into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between WIG 30 and Austrian Traded Index, you can compare the effects of market volatilities on WIG 30 and Austrian Traded 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 WIG 30 with a short position of Austrian Traded. Check out your portfolio center. Please also check ongoing floating volatility patterns of WIG 30 and Austrian Traded.

Diversification Opportunities for WIG 30 and Austrian Traded

0.78
  Correlation Coefficient

Poor diversification

The 3 months correlation between WIG and Austrian is 0.78. Overlapping area represents the amount of risk that can be diversified away by holding WIG 30 and Austrian Traded Index in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Austrian Traded Index and WIG 30 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 WIG 30 are associated (or correlated) with Austrian Traded. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Austrian Traded Index has no effect on the direction of WIG 30 i.e., WIG 30 and Austrian Traded go up and down completely randomly.
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Pair Corralation between WIG 30 and Austrian Traded

Assuming the 90 days trading horizon WIG 30 is expected to under-perform the Austrian Traded. In addition to that, WIG 30 is 1.54 times more volatile than Austrian Traded Index. It trades about -0.09 of its total potential returns per unit of risk. Austrian Traded Index is currently generating about -0.11 per unit of volatility. If you would invest  373,000  in Austrian Traded Index on August 30, 2024 and sell it today you would lose (22,365) from holding Austrian Traded Index or give up 6.0% of portfolio value over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthSignificant
Accuracy96.88%
ValuesDaily Returns

WIG 30  vs.  Austrian Traded Index

 Performance 
       Timeline  

WIG 30 and Austrian Traded Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with WIG 30 and Austrian Traded

The main advantage of trading using opposite WIG 30 and Austrian Traded positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if WIG 30 position performs unexpectedly, Austrian Traded 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 Austrian Traded will offset losses from the drop in Austrian Traded's long position.
The idea behind WIG 30 and Austrian Traded Index 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 Commodity Channel module to use Commodity Channel Index to analyze current equity momentum.

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