UPM.VaR

Generates an upside value at risk (VaR) quantile based on the Upper Partial Moment ratio.

NNS (Nonlinear Nonparametric Statistics) leverages partial moments – the fundamental elements of variance that asymptotically approximate the area under f(x) – to provide a robust foundation for nonlinear analysis while maintaining linear equivalences. Designed for real-world data that violates symmetry, linearity, or distributional assumptions, NNS delivers a comprehensive suite of advanced statistical techniques, including: Numerical integration, Numerical differentiation, Clustering, Correlation, Dependence, Causal analysis, ANOVA, Regression, Classification, Seasonality, Autoregressive modeling, Normalization, Stochastic superiority / dominance and Advanced Monte Carlo sampling. All routines based on: Viole, F. and Nawrocki, D. (2013), Nonlinear Nonparametric Statistics: Using Partial Moments (ISBN: 1490523995, Second edition: <https://ovvo-financial.github.io/NNS/book/>).

Fred Viole

Nonlinear Nonparametric Statistics

Roberto Spadim

Rasheed Khoshnaw

UPM.VaR function

<dl><dt>percentile</dt>
<dd>numeric [0, 1]; The percentile for right-tail VaR.</dd>
<dt>degree</dt>
<dd>integer; <code>(degree = 0)</code> for discrete distributions, <code>(degree = 1)</code> for continuous distributions.</dd>
<dt>x</dt>
<dd>a numeric vector.</dd></dl>

Arguments

Fred Viole, OVVO Financial Systems

Author

UPM VaR — UPM.VaR

<dl>

<dt>percentile</dt>
<dd>numeric [0, 1]; The percentile for right-tail VaR.</dd>


<dt>degree</dt>
<dd>integer; <code>(degree = 0)</code> for discrete distributions, <code>(degree = 1)</code> for continuous distributions.</dd>


<dt>x</dt>
<dd>a numeric vector.</dd>

</dl>

UPM.VaR: UPM VaR

Description

Usage

Value

Arguments

Author

References

Examples