Correlation Between Allianz Technology and Cboe UK

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

By analyzing existing cross correlation between Allianz Technology Trust and Cboe UK Consumer, you can compare the effects of market volatilities on Allianz Technology and Cboe UK 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 Allianz Technology with a short position of Cboe UK. Check out your portfolio center. Please also check ongoing floating volatility patterns of Allianz Technology and Cboe UK.

Diversification Opportunities for Allianz Technology and Cboe UK

0.94

Correlation Coefficient

Allianz Technology  Cboe UK

Almost no diversification

The 3 months correlation between Allianz and Cboe is 0.94. Overlapping area represents the amount of risk that can be diversified away by holding Allianz Technology Trust and Cboe UK Consumer in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Cboe UK Consumer and Allianz 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 Allianz Technology Trust are associated (or correlated) with Cboe UK. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Cboe UK Consumer has no effect on the direction of Allianz Technology i.e., Allianz Technology and Cboe UK go up and down completely randomly.

Pair Corralation between Allianz Technology and Cboe UK

Assuming the 90 days trading horizon Allianz Technology Trust is expected to generate 1.52 times more return on investment than Cboe UK. However, Allianz Technology is 1.52 times more volatile than Cboe UK Consumer. It trades about 0.3 of its potential returns per unit of risk. Cboe UK Consumer is currently generating about 0.25 per unit of risk. If you would invest  38,500  in Allianz Technology Trust on September 16, 2024 and sell it today you would earn a total of  3,000  from holding Allianz Technology Trust or generate 7.79% return on investment over 90 days.

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

Allianz Technology Trust  vs.  Cboe UK Consumer

Pair Trading with Allianz Technology and Cboe UK

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

The idea behind Allianz Technology Trust and Cboe UK Consumer 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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.