Correlation Between Kosdaq Composite and E Mart

Can any of the company-specific risk be diversified away by investing in both Kosdaq Composite and E Mart 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 Kosdaq Composite and E Mart into the same portfolio, which is an essential part of the fundamental portfolio management process.

By analyzing existing cross correlation between Kosdaq Composite Index and E Mart, you can compare the effects of market volatilities on Kosdaq Composite and E Mart 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 Kosdaq Composite with a short position of E Mart. Check out your portfolio center. Please also check ongoing floating volatility patterns of Kosdaq Composite and E Mart.

Diversification Opportunities for Kosdaq Composite and E Mart

-0.45

Correlation Coefficient

Kosdaq Composite  E Mart

Very good diversification

The 3 months correlation between Kosdaq and 139480 is -0.45. Overlapping area represents the amount of risk that can be diversified away by holding Kosdaq Composite Index and E Mart in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on E Mart and Kosdaq Composite 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 Kosdaq Composite Index are associated (or correlated) with E Mart. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of E Mart has no effect on the direction of Kosdaq Composite i.e., Kosdaq Composite and E Mart go up and down completely randomly.

Pair Corralation between Kosdaq Composite and E Mart

Assuming the 90 days trading horizon Kosdaq Composite Index is expected to under-perform the E Mart. But the index apears to be less risky and, when comparing its historical volatility, Kosdaq Composite Index is 1.45 times less risky than E Mart. The index trades about -0.11 of its potential returns per unit of risk. The E Mart is currently generating about 0.18 of returns per unit of risk over similar time horizon. If you would invest  5,920,000  in E Mart on September 28, 2024 and sell it today you would earn a total of  1,630,000  from holding E Mart or generate 27.53% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Against
Strength	Very Weak
Accuracy	98.36%
Values	Daily Returns

Kosdaq Composite Index  vs.  E Mart

Pair Trading with Kosdaq Composite and E Mart

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

The idea behind Kosdaq Composite Index and E Mart 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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.