Correlation Between BIST Electricity and Lokman Hekim

Can any of the company-specific risk be diversified away by investing in both BIST Electricity and Lokman Hekim 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 BIST Electricity and Lokman Hekim into the same portfolio, which is an essential part of the fundamental portfolio management process.

By analyzing existing cross correlation between BIST Electricity and Lokman Hekim Engurusag, you can compare the effects of market volatilities on BIST Electricity and Lokman Hekim 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 BIST Electricity with a short position of Lokman Hekim. Check out your portfolio center. Please also check ongoing floating volatility patterns of BIST Electricity and Lokman Hekim.

Diversification Opportunities for BIST Electricity and Lokman Hekim

0.71

Correlation Coefficient

BIST Electricity  Lokman Hekim

Poor diversification

The 3 months correlation between BIST and Lokman is 0.71. Overlapping area represents the amount of risk that can be diversified away by holding BIST Electricity and Lokman Hekim Engurusag in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Lokman Hekim Engurusag and BIST Electricity 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 BIST Electricity are associated (or correlated) with Lokman Hekim. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Lokman Hekim Engurusag has no effect on the direction of BIST Electricity i.e., BIST Electricity and Lokman Hekim go up and down completely randomly.

Pair Corralation between BIST Electricity and Lokman Hekim

Assuming the 90 days trading horizon BIST Electricity is expected to generate 0.76 times more return on investment than Lokman Hekim. However, BIST Electricity is 1.32 times less risky than Lokman Hekim. It trades about 0.26 of its potential returns per unit of risk. Lokman Hekim Engurusag is currently generating about 0.04 per unit of risk. If you would invest  48,091  in BIST Electricity on September 22, 2024 and sell it today you would earn a total of  2,523  from holding BIST Electricity or generate 5.25% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Significant
Accuracy	95.65%
Values	Daily Returns

BIST Electricity  vs.  Lokman Hekim Engurusag

Pair Trading with BIST Electricity and Lokman Hekim

The main advantage of trading using opposite BIST Electricity and Lokman Hekim positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if BIST Electricity position performs unexpectedly, Lokman Hekim 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 Lokman Hekim will offset losses from the drop in Lokman Hekim's long position.

The idea behind BIST Electricity and Lokman Hekim Engurusag 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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.