Deviation risk measure

In financial mathematics, a deviation risk measure is a function to quantify financial risk (and not necessarily downside risk) in a different method than a general risk measure. Deviation risk measures generalize the concept of standard deviation.

Mathematical definition

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A function  , where   is the L2 space of random variables (random portfolio returns), is a deviation risk measure if

  1. Shift-invariant:   for any  
  2. Normalization:  
  3. Positively homogeneous:   for any   and  
  4. Sublinearity:   for any  
  5. Positivity:   for all nonconstant X, and   for any constant X.[1][2]

Relation to risk measure

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There is a one-to-one relationship between a deviation risk measure D and an expectation-bounded risk measure R where for any  

  •  
  •  .

R is expectation bounded if   for any nonconstant X and   for any constant X.

If   for every X (where   is the essential infimum), then there is a relationship between D and a coherent risk measure.[1]

Examples

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The most well-known examples of risk deviation measures are:[1]

  • Standard deviation  ;
  • Average absolute deviation  ;
  • Lower and upper semi-deviations   and  , where   and  ;
  • Range-based deviations, for example,   and  ;
  • Conditional value-at-risk (CVaR) deviation, defined for any   by  , where   is Expected shortfall.

See also

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References

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  1. ^ a b c Rockafellar, Tyrrell; Uryasev, Stanislav; Zabarankin, Michael (2002). "Deviation Measures in Risk Analysis and Optimization". SSRN 365640. {{cite journal}}: Cite journal requires |journal= (help)
  2. ^ Cheng, Siwei; Liu, Yanhui; Wang, Shouyang (2004). "Progress in Risk Measurement". Advanced Modelling and Optimization. 6 (1).