Correlation Between KL Technology and Techbond Group

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

By analyzing existing cross correlation between KL Technology and Techbond Group Bhd, you can compare the effects of market volatilities on KL Technology and Techbond Group 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 Techbond Group. Check out your portfolio center. Please also check ongoing floating volatility patterns of KL Technology and Techbond Group.

Diversification Opportunities for KL Technology and Techbond Group

0.6

Correlation Coefficient

KL Technology  Techbond Group

Poor diversification

The 3 months correlation between KLTE and Techbond is 0.6. Overlapping area represents the amount of risk that can be diversified away by holding KL Technology and Techbond Group Bhd in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Techbond Group Bhd 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 Techbond Group. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Techbond Group Bhd has no effect on the direction of KL Technology i.e., KL Technology and Techbond Group go up and down completely randomly.

Pair Corralation between KL Technology and Techbond Group

Assuming the 90 days trading horizon KL Technology is expected to under-perform the Techbond Group. But the index apears to be less risky and, when comparing its historical volatility, KL Technology is 1.5 times less risky than Techbond Group. The index trades about -0.22 of its potential returns per unit of risk. The Techbond Group Bhd is currently generating about -0.07 of returns per unit of risk over similar time horizon. If you would invest  39.00  in Techbond Group Bhd on December 4, 2024 and sell it today you would lose (4.00) from holding Techbond Group Bhd or give up 10.26% of portfolio value over 90 days.

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

KL Technology  vs.  Techbond Group Bhd

Pair Trading with KL Technology and Techbond Group

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

The idea behind KL Technology and Techbond Group Bhd 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.