Correlation Between MEGA METAL and BIST Electricity

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

Diversification Opportunities for MEGA METAL and BIST Electricity

0.7
  Correlation Coefficient

Poor diversification

The 3 months correlation between MEGA and BIST is 0.7. Overlapping area represents the amount of risk that can be diversified away by holding MEGA METAL and BIST Electricity in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on BIST Electricity and MEGA METAL 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 MEGA METAL are associated (or correlated) with BIST Electricity. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of BIST Electricity has no effect on the direction of MEGA METAL i.e., MEGA METAL and BIST Electricity go up and down completely randomly.
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Pair Corralation between MEGA METAL and BIST Electricity

Assuming the 90 days trading horizon MEGA METAL is expected to under-perform the BIST Electricity. In addition to that, MEGA METAL is 1.25 times more volatile than BIST Electricity. It trades about -0.09 of its total potential returns per unit of risk. BIST Electricity is currently generating about -0.08 per unit of volatility. If you would invest  51,935  in BIST Electricity on December 30, 2024 and sell it today you would lose (5,339) from holding BIST Electricity or give up 10.28% of portfolio value over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthSignificant
Accuracy100.0%
ValuesDaily Returns

MEGA METAL  vs.  BIST Electricity

 Performance 
       Timeline  

MEGA METAL and BIST Electricity Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with MEGA METAL and BIST Electricity

The main advantage of trading using opposite MEGA METAL and BIST Electricity positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if MEGA METAL position performs unexpectedly, BIST Electricity 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 BIST Electricity will offset losses from the drop in BIST Electricity's long position.
The idea behind MEGA METAL and BIST Electricity 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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.

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