Correlation Between WIG 30 and SPASX Dividend

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

Diversification Opportunities for WIG 30 and SPASX Dividend

-0.32
  Correlation Coefficient

Very good diversification

The 3 months correlation between WIG and SPASX is -0.32. Overlapping area represents the amount of risk that can be diversified away by holding WIG 30 and SPASX Dividend Opportunities in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SPASX Dividend Oppor 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 SPASX Dividend. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SPASX Dividend Oppor has no effect on the direction of WIG 30 i.e., WIG 30 and SPASX Dividend go up and down completely randomly.
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Pair Corralation between WIG 30 and SPASX Dividend

Assuming the 90 days trading horizon WIG 30 is expected to under-perform the SPASX Dividend. In addition to that, WIG 30 is 2.02 times more volatile than SPASX Dividend Opportunities. It trades about -0.09 of its total potential returns per unit of risk. SPASX Dividend Opportunities is currently generating about 0.05 per unit of volatility. If you would invest  165,960  in SPASX Dividend Opportunities on August 30, 2024 and sell it today you would earn a total of  3,120  from holding SPASX Dividend Opportunities or generate 1.88% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Against 
StrengthInsignificant
Accuracy96.88%
ValuesDaily Returns

WIG 30  vs.  SPASX Dividend Opportunities

 Performance 
       Timeline  

WIG 30 and SPASX Dividend Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with WIG 30 and SPASX Dividend

The main advantage of trading using opposite WIG 30 and SPASX Dividend positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if WIG 30 position performs unexpectedly, SPASX Dividend 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 SPASX Dividend will offset losses from the drop in SPASX Dividend's long position.
The idea behind WIG 30 and SPASX Dividend Opportunities 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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.

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