Correlation Between Karachi 100 and Coreshares Index

Can any of the company-specific risk be diversified away by investing in both Karachi 100 and Coreshares Index 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 Karachi 100 and Coreshares Index into the same portfolio, which is an essential part of the fundamental portfolio management process.

By analyzing existing cross correlation between Karachi 100 and Coreshares Index Tracker, you can compare the effects of market volatilities on Karachi 100 and Coreshares Index 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 Karachi 100 with a short position of Coreshares Index. Check out your portfolio center. Please also check ongoing floating volatility patterns of Karachi 100 and Coreshares Index.

Diversification Opportunities for Karachi 100 and Coreshares Index

0.47

Correlation Coefficient

Karachi 100  Coreshares Index

Very weak diversification

The 3 months correlation between Karachi and Coreshares is 0.47. Overlapping area represents the amount of risk that can be diversified away by holding Karachi 100 and Coreshares Index Tracker in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Coreshares Index Tracker and Karachi 100 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 Karachi 100 are associated (or correlated) with Coreshares Index. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Coreshares Index Tracker has no effect on the direction of Karachi 100 i.e., Karachi 100 and Coreshares Index go up and down completely randomly.

Pair Corralation between Karachi 100 and Coreshares Index

Assuming the 90 days trading horizon Karachi 100 is expected to generate 1.14 times more return on investment than Coreshares Index. However, Karachi 100 is 1.14 times more volatile than Coreshares Index Tracker. It trades about 0.36 of its potential returns per unit of risk. Coreshares Index Tracker is currently generating about 0.04 per unit of risk. If you would invest  7,848,822  in Karachi 100 on August 30, 2024 and sell it today you would earn a total of  2,078,103  from holding Karachi 100 or generate 26.48% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Weak
Accuracy	100.0%
Values	Daily Returns

Karachi 100  vs.  Coreshares Index Tracker

Pair Trading with Karachi 100 and Coreshares Index

The main advantage of trading using opposite Karachi 100 and Coreshares Index positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Karachi 100 position performs unexpectedly, Coreshares Index 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 Coreshares Index will offset losses from the drop in Coreshares Index's long position.

The idea behind Karachi 100 and Coreshares Index Tracker 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.