Correlation Between KL Technology and JF Technology

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Can any of the company-specific risk be diversified away by investing in both KL Technology and JF Technology 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 JF Technology into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between KL Technology and JF Technology BHD, you can compare the effects of market volatilities on KL Technology and JF Technology 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 JF Technology. Check out your portfolio center. Please also check ongoing floating volatility patterns of KL Technology and JF Technology.

Diversification Opportunities for KL Technology and JF Technology

0.72
  Correlation Coefficient

Poor diversification

The 3 months correlation between KLTE and 0146 is 0.72. Overlapping area represents the amount of risk that can be diversified away by holding KL Technology and JF Technology BHD in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on JF Technology 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 JF Technology. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of JF Technology BHD has no effect on the direction of KL Technology i.e., KL Technology and JF Technology go up and down completely randomly.
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Pair Corralation between KL Technology and JF Technology

Assuming the 90 days trading horizon KL Technology is expected to generate 0.62 times more return on investment than JF Technology. However, KL Technology is 1.6 times less risky than JF Technology. It trades about 0.07 of its potential returns per unit of risk. JF Technology BHD is currently generating about -0.21 per unit of risk. If you would invest  5,893  in KL Technology on August 28, 2024 and sell it today you would earn a total of  139.00  from holding KL Technology or generate 2.36% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthSignificant
Accuracy100.0%
ValuesDaily Returns

KL Technology  vs.  JF Technology BHD

 Performance 
       Timeline  

KL Technology and JF Technology Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with KL Technology and JF Technology

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

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