Correlation Between KL Technology and Sand Nisko

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

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

Diversification Opportunities for KL Technology and Sand Nisko

-0.43

Correlation Coefficient

KL Technology  Sand Nisko

Very good diversification

The 3 months correlation between KLTE and Sand is -0.43. Overlapping area represents the amount of risk that can be diversified away by holding KL Technology and Sand Nisko Capital in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Sand Nisko Capital 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 Sand Nisko. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Sand Nisko Capital has no effect on the direction of KL Technology i.e., KL Technology and Sand Nisko go up and down completely randomly.

Pair Corralation between KL Technology and Sand Nisko

Assuming the 90 days trading horizon KL Technology is expected to generate 635.8 times less return on investment than Sand Nisko. But when comparing it to its historical volatility, KL Technology is 30.28 times less risky than Sand Nisko. It trades about 0.01 of its potential returns per unit of risk. Sand Nisko Capital is currently generating about 0.14 of returns per unit of risk over similar time horizon. If you would invest  38.00  in Sand Nisko Capital on September 20, 2024 and sell it today you would lose (28.00) from holding Sand Nisko Capital or give up 73.68% of portfolio value over 90 days.

Time Period	3 Months [change]
Direction	Moves Against
Strength	Very Weak
Accuracy	99.79%
Values	Daily Returns

KL Technology  vs.  Sand Nisko Capital

Pair Trading with KL Technology and Sand Nisko

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

The idea behind KL Technology and Sand Nisko Capital 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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.