Correlation Between Uber Technologies and Agilent Technologies

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

Diversification Opportunities for Uber Technologies and Agilent Technologies

0.66
  Correlation Coefficient

Poor diversification

The 3 months correlation between Uber Technologies and Agilent is 0.66. Overlapping area represents the amount of risk that can be diversified away by holding Uber Technologies and Agilent Technologies in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Agilent Technologies and Uber Technologies 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 Uber Technologies are associated (or correlated) with Agilent Technologies. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Agilent Technologies has no effect on the direction of Uber Technologies i.e., Uber Technologies and Agilent Technologies go up and down completely randomly.

Pair Corralation between Uber Technologies and Agilent Technologies

Given the investment horizon of 90 days Uber Technologies is expected to under-perform the Agilent Technologies. In addition to that, Uber Technologies is 1.95 times more volatile than Agilent Technologies. It trades about -0.07 of its total potential returns per unit of risk. Agilent Technologies is currently generating about -0.03 per unit of volatility. If you would invest  14,250  in Agilent Technologies on April 7, 2022 and sell it today you would lose (2,194)  from holding Agilent Technologies or give up 15.4% of portfolio value over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthSignificant
Accuracy100.0%
ValuesDaily Returns

Uber Technologies  vs.  Agilent Technologies

 Performance (%) 
      Timeline 
Uber Technologies 
Uber Technologies Performance
0 of 100
Over the last 90 days Uber Technologies has generated negative risk-adjusted returns adding no value to investors with long positions. Even with weak performance in the last few months, the Stock's technical and fundamental indicators remain relatively invariable which may send shares a bit higher in August 2022. The latest agitation may also be a sign of long-running up-swing for the enterprise retail investors.

Uber Technologies Price Channel

Agilent Technologies 
Agilent Performance
0 of 100
Over the last 90 days Agilent Technologies has generated negative risk-adjusted returns adding no value to investors with long positions. Despite latest weak performance, the Stock's basic indicators remain strong and the current disturbance on Wall Street may also be a sign of long term gains for the company investors.

Agilent Price Channel

Uber Technologies and Agilent Technologies Volatility Contrast

 Predicted Return Density 
      Returns 

Pair Trading with Uber Technologies and Agilent Technologies

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

Uber Technologies

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The effect of pair diversification on risk is to reduce it, but we should note this doesn't apply to all risk types. When we trade pairs against Uber Technologies as a counterpart, there is always some inherent risk that will never be diversified away no matter what. This volatility limits the effect of tactical diversification using pair trading. Uber Technologies' systematic risk is the inherent uncertainty of the entire market, and therefore cannot be mitigated even by pair-trading it against the equity that is not highly correlated to it. On the other hand, Uber Technologies' unsystematic risk describes the types of risk that we can protect against, at least to some degree, by selecting a matching pair that is not perfectly correlated to Uber Technologies.
The idea behind Uber Technologies and Agilent Technologies 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.
Check out your portfolio center. 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 Technical Analysis module to check basic technical indicators and analysis based on most latest market data.

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