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Related Correlations Analysis


Correlation Matchups

Over a given time period, the two securities move together when the Correlation Coefficient is positive. Conversely, the two assets move in opposite directions when the Correlation Coefficient is negative. Determining your positions' relationship to each other is valuable for analyzing and projecting your portfolio's future expected return and risk.

High positive correlations

UBERMSFT
MRKF
JPMCRM
XOMMRK
XOMF
AUBER
  

High negative correlations

MRKUBER
MRKMSFT
XOMMSFT
XOMA
FMSFT
XOMUBER

Risk-Adjusted Indicators

There is a big difference between a company's stock performing well and the company itself doing well as a business compared to the competition. There are so many exceptions to the norm that investors cannot definitively determine what's good or bad unless they analyze multiple risk-adjusted performance indicators across the competitive landscape. These indicators are quantitative in nature and help investors forecast volatility and risk-adjusted expected returns across various positions.
Mean DeviationJensen AlphaSortino RatioTreynor RatioSemi DeviationExpected ShortfallPotential UpsideValue @RiskMaximum Drawdown
META  1.61 (0.08) 0.00 (0.04) 0.00 
 3.43 
 11.42 
MSFT  1.23 (0.32) 0.00 (1.41) 0.00 
 1.85 
 13.28 
UBER  1.46 (0.30) 0.00 (0.36) 0.00 
 2.46 
 10.23 
F  1.24  0.05  0.04  0.08  1.23 
 3.38 
 7.16 
T  0.96  0.05  0.02  0.23  1.04 
 1.85 
 3.77 
A  1.19 (0.18) 0.00 (0.10) 0.00 
 2.90 
 7.85 
CRM  1.54 (0.30) 0.00 (0.25) 0.00 
 2.94 
 12.37 
JPM  1.09 (0.03)(0.01) 0.01  1.67 
 1.88 
 7.38 
MRK  1.28  0.33  0.24  0.50  1.13 
 3.59 
 8.09 
XOM  1.08  0.31  0.23  3.83  0.95 
 2.38 
 5.82 

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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 Price Exposure Probability module to analyze equity upside and downside potential for a given time horizon across multiple markets.

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