unconditionalNormal

Unconditional expected shortfall (ES) backtest by Acerbi-Szekely with critical values for normal distributions

Syntax

TestResults = unconditionalNormal(ebt)

TestResults = unconditionalNormal(ebt,Name,Value)

Description

TestResults = unconditionalNormal(ebt) runs the unconditional expected shortfall (ES) backtest by Acerbi-Szekely (2014) using precomputed critical values and assuming that the returns distribution is standard normal.

TestResults = unconditionalNormal(ebt,Name,Value) adds an optional name-value pair argument for TestLevel.

Examples

Run an Unconditional ES Backtest

Create an esbacktest object.

load ESBacktestData
ebt = esbacktest(Returns,VaRModel1,ESModel1,'VaRLevel',VaRLevel)

ebt = 
  esbacktest with properties:

    PortfolioData: [1966×1 double]
          VaRData: [1966×1 double]
           ESData: [1966×1 double]
             Time: [1966×1 double]
      PortfolioID: "Portfolio"
            VaRID: "VaR"
         VaRLevel: 0.9750

Generate the TestResults report for the unconditional ES backtest that assumes the returns distribution is standard normal.

TestResults = unconditionalNormal(ebt,'TestLevel',0.99)

TestResults=1×9 table
    PortfolioID    VaRID    VaRLevel    UnconditionalNormal     PValue      TestStatistic    CriticalValue    Observations    TestLevel
    ___________    _____    ________    ___________________    _________    _____________    _____________    ____________    _________

    "Portfolio"    "VaR"     0.975            reject           0.0054099      -0.38265         -0.34639           1966          0.99   

Input Arguments

ebt — esbacktest object

object

esbacktest (ebt) object, which contains a copy of the given data (the PortfolioData, VarData, and ESData properties) and all combinations of portfolio ID, VaR ID, and VaR levels to be tested. For more information on creating an esbacktest object, see esbacktest.

Name-Value Arguments

Specify optional pairs of arguments as Name1=Value1,...,NameN=ValueN, where Name is the argument name and Value is the corresponding value. Name-value arguments must appear after other arguments, but the order of the pairs does not matter.

Before R2021a, use commas to separate each name and value, and enclose Name in quotes.

Example: TestResults = unconditionalNormal(ebt,'TestLevel',0.99)

TestLevel — Test confidence level

0.95 (default) | numeric value between 0.5 and 0.9999

Test confidence level, specified as the comma-separated pair consisting of 'TestLevel' and a numeric value between 0.5 and 0.9999.

Data Types: double

Output Arguments

TestResults — Results

table

Results, returned as a table where the rows correspond to all combinations of portfolio ID, VaR ID, and VaR levels to be tested. The columns correspond to the following information:

• 'PortfolioID' — Portfolio ID for the given data.

• 'VaRID' — VaR ID for each of the VaR data columns provided.

• 'VaRLevel' — VaR level for the corresponding VaR data column.

• 'UnconditionalNormal'— Categorical array with categories 'accept' and 'reject' that indicate the result of the unconditional normal test.

• 'PValue'— P-value of the unconditional normal test, interpolated from the precomputed critical values under the assumption that the returns follow a standard normal distribution.

  Note

  p-values < 0.0001 are truncated to the minimum (0.0001) and p-values > 0.5 are displayed as a maximum (0.5).

• 'TestStatistic'— Unconditional normal test statistic.

• 'CriticalValue'— Precomputed critical value for the corresponding test level and number of observations. Critical values are obtained under the assumption that the returns follow a standard normal distribution.

• 'Observations'— Number of observations.

• 'TestLevel'— Test confidence level.

Note

For the test results, the terms 'accept' and 'reject' are used for convenience. Technically, a test does not accept a model; rather, a test fails to reject it.

More About

Unconditional Test by Acerbi and Szekely

The unconditional test (also known as the second Acerbi-Szekely test) scales the losses by the corresponding ES value.

The unconditional test statistic is based on the unconditional relationship

$$E{S}_t=-E_t\left[\frac{X_t{I}_t}{p_{VaR}}\right]$$

where

X_t is the portfolio outcome, that is, the portfolio return or portfolio profit and loss for period t.

P_VaR is the probability of VaR failure defined as 1-VaR level.

ES_t is the estimated expected shortfall for period t.

I_t is the VaR failure indicator on period t with a value of 1 if X_t < -VaR, and 0 otherwise.

The unconditional test statistic is defined as

$$Z_{uncond}=\frac{1}{N{p}_{VaR}}{\displaystyle \sum _{t=1}^N\frac{X_t{I}_t}{E{S}_t}+1}$$

The critical values for the unconditional test statistic, which form the basis for table-based tests, are stable across a range of distributions. The esbacktest class runs the unconditional test against precomputed critical values under two distributional assumptions: normal distribution (thin tails) using unconditionalNormal and t distribution with 3 degrees of freedom (heavy tails) using unconditionalT).

References

[1] Acerbi, C., and B. Szekely. Backtesting Expected Shortfall. MSCI Inc. December, 2014.

Version History

Introduced in R2017b