Correlation Between Karachi 100 and Shadab Textile

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

By analyzing existing cross correlation between Karachi 100 and Shadab Textile Mills, you can compare the effects of market volatilities on Karachi 100 and Shadab Textile 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 Shadab Textile. Check out your portfolio center. Please also check ongoing floating volatility patterns of Karachi 100 and Shadab Textile.

Diversification Opportunities for Karachi 100 and Shadab Textile

0.11

Correlation Coefficient

Karachi 100  Shadab Textile

Average diversification

The 3 months correlation between Karachi and Shadab is 0.11. Overlapping area represents the amount of risk that can be diversified away by holding Karachi 100 and Shadab Textile Mills in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Shadab Textile Mills 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 Shadab Textile. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Shadab Textile Mills has no effect on the direction of Karachi 100 i.e., Karachi 100 and Shadab Textile go up and down completely randomly.

Pair Corralation between Karachi 100 and Shadab Textile

Assuming the 90 days trading horizon Karachi 100 is expected to generate 2.46 times less return on investment than Shadab Textile. But when comparing it to its historical volatility, Karachi 100 is 3.74 times less risky than Shadab Textile. It trades about 0.06 of its potential returns per unit of risk. Shadab Textile Mills is currently generating about 0.04 of returns per unit of risk over similar time horizon. If you would invest  2,159  in Shadab Textile Mills on December 24, 2024 and sell it today you would earn a total of  111.00  from holding Shadab Textile Mills or generate 5.14% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Insignificant
Accuracy	96.83%
Values	Daily Returns

Karachi 100  vs.  Shadab Textile Mills

Pair Trading with Karachi 100 and Shadab Textile

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

The idea behind Karachi 100 and Shadab Textile Mills 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 Competition Analyzer module to analyze and compare many basic indicators for a group of related or unrelated entities.