Correlation Between UNIQA Insurance and Cboe UK

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Can any of the company-specific risk be diversified away by investing in both UNIQA Insurance 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 UNIQA Insurance and Cboe UK into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between UNIQA Insurance Group and Cboe UK Consumer, you can compare the effects of market volatilities on UNIQA Insurance 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 UNIQA Insurance with a short position of Cboe UK. Check out your portfolio center. Please also check ongoing floating volatility patterns of UNIQA Insurance and Cboe UK.

Diversification Opportunities for UNIQA Insurance and Cboe UK

0.29
  Correlation Coefficient

Modest diversification

The 3 months correlation between UNIQA and Cboe is 0.29. Overlapping area represents the amount of risk that can be diversified away by holding UNIQA Insurance Group 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 UNIQA Insurance 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 UNIQA Insurance Group 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 UNIQA Insurance i.e., UNIQA Insurance and Cboe UK go up and down completely randomly.
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Pair Corralation between UNIQA Insurance and Cboe UK

Assuming the 90 days trading horizon UNIQA Insurance Group is expected to generate 0.56 times more return on investment than Cboe UK. However, UNIQA Insurance Group is 1.8 times less risky than Cboe UK. It trades about 0.6 of its potential returns per unit of risk. Cboe UK Consumer is currently generating about -0.05 per unit of risk. If you would invest  808.00  in UNIQA Insurance Group on November 29, 2024 and sell it today you would earn a total of  63.00  from holding UNIQA Insurance Group or generate 7.8% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthVery Weak
Accuracy100.0%
ValuesDaily Returns

UNIQA Insurance Group  vs.  Cboe UK Consumer

 Performance 
       Timeline  

UNIQA Insurance and Cboe UK Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with UNIQA Insurance and Cboe UK

The main advantage of trading using opposite UNIQA Insurance and Cboe UK positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if UNIQA Insurance 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 UNIQA Insurance Group 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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.

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