open-risk / tailRisk

A library for the calculation of tail risk measures

tailRisk

A C++ library for the calculation of various tail risk measures

Documentation

NB: Documentation still under development.

• Implemented Risk Measures
• Mathematical Documentation available here

Dependencies

• Eigen (Data container and linear algebra calculation library)
• Poco (For parsing JSON inputs and other utilities)
• Stats (A C++ header-only library of statistical distribution functions.)

Example

The data directory contains sample datafiles with various sampled distributions

// Read in some data for a type 0 representation (discrete distribution)
int LossGrid = 1000;
int DataType = 0;
RandomVar L(LossGrid, DataType);
L.ReadFromJSON("../data/example5.json");
L.Print();

// Calculate various measures
double alpha = 0.8;
int threshold = 0;

std::cout << "Mean Value: " << L.Mean() << std::endl;
std::cout << "Median Value: " << L.Median() << std::endl;
std::cout << "STD Value: " << L.StandardDeviation() << std::endl;
std::cout << "Kurtosis: " << L.Kurtosis() << std::endl;
std::cout << "Skeweness: " << L.Skeweness() << std::endl;
std::cout << "Quantile @ " << alpha << ": " << L.Quantile(alpha) << std::endl;
std::cout << "Quantile Index @ " << alpha << ": " << L.Quantile_Index(alpha) << std::endl;
std::cout << "VaR @ " << alpha << ": " << L.VaR(alpha) << std::endl;
std::cout << "Expected Shortfall @ " << alpha << ": " << L.ExpectedShortFall(alpha) << std::endl;
std::cout << "Exceedance Probability: " << L.ExceedanceProbability(threshold) << std::endl;
std::cout << "Mean Excess: " << L.MeanExcess(threshold ) << std::endl;