Correlation Between KL Technology and Public Packages

Can any of the company-specific risk be diversified away by investing in both KL Technology and Public Packages 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 KL Technology and Public Packages into the same portfolio, which is an essential part of the fundamental portfolio management process.

By analyzing existing cross correlation between KL Technology and Public Packages Holdings, you can compare the effects of market volatilities on KL Technology and Public Packages 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 KL Technology with a short position of Public Packages. Check out your portfolio center. Please also check ongoing floating volatility patterns of KL Technology and Public Packages.

Diversification Opportunities for KL Technology and Public Packages

0.41

Correlation Coefficient

KL Technology  Public Packages

Very weak diversification

The 3 months correlation between KLTE and Public is 0.41. Overlapping area represents the amount of risk that can be diversified away by holding KL Technology and Public Packages Holdings in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Public Packages Holdings and KL Technology 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 KL Technology are associated (or correlated) with Public Packages. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Public Packages Holdings has no effect on the direction of KL Technology i.e., KL Technology and Public Packages go up and down completely randomly.

Pair Corralation between KL Technology and Public Packages

Assuming the 90 days trading horizon KL Technology is expected to generate 1.0 times more return on investment than Public Packages. However, KL Technology is 1.0 times less risky than Public Packages. It trades about -0.09 of its potential returns per unit of risk. Public Packages Holdings is currently generating about -0.1 per unit of risk. If you would invest  6,378  in KL Technology on September 3, 2024 and sell it today you would lose (530.00) from holding KL Technology or give up 8.31% of portfolio value over 90 days.

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

KL Technology  vs.  Public Packages Holdings

Pair Trading with KL Technology and Public Packages

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

The idea behind KL Technology and Public Packages Holdings 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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.