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Adjust all cvar functions to receive weights and alphatest on argumen…
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…ts and project build update
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@prcolaco
prcolaco committed Nov 23, 2019
1 parent 3cb52cf commit c58778d
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Showing 8 changed files with 103 additions and 275 deletions.
4 changes: 3 additions & 1 deletion binding.gyp
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Expand Up @@ -4,7 +4,9 @@
'target_name': 'riskjs',
'sources': [
'src/RiskJS.cpp',
'src/ptf_mc_var.cpp',
'src/CVaRHistorical.cpp',
'src/CVaRMonteCarlo.cpp',
'src/CVaRVarianceCovariance.cpp',
'src/compute_returns_eigen.cpp',
'src/instrument.cpp',
'src/path.cpp',
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22 changes: 22 additions & 0 deletions src/CVaR.h
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@@ -0,0 +1,22 @@
// Portfolio VaR through MC simulation
// from test_ptf_mc_var.cpp

#pragma once


#include <string>
#include <vector>


namespace RiskJS {

// Vectors types for function arguments
typedef std::vector<std::string> priceRow;
typedef std::vector<priceRow> priceData;
typedef std::vector<double> weightData;

double CVaRMonteCarlo(priceData rawPrices, weightData weights, double alphatest);
double CVaRHistorical(priceData rawPrices, weightData weights, double alphatest);
double CVaRVarianceCovariance(priceData rawPrices, weightData weights, double alphatest);

} // namespace RiskJS
40 changes: 16 additions & 24 deletions src/CVaRHistorical.cpp
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Expand Up @@ -6,7 +6,7 @@

#include <Eigen/Dense>

#include "ptf_mc_var.h"
#include "CVaR.h"

#include "compute_returns_eigen.h"
#include "compute_var.h"
Expand All @@ -27,17 +27,17 @@ using namespace Eigen;
using namespace std;


double CVaRHistorical(priceData data) {
double CVaRHistorical(priceData rawPrices, weightData weights, double alphatest) {
// Remove lines with missing values
size_t n(data.size() - 1);
size_t m(data[0].size() - 1);
size_t n(rawPrices.size() - 1);
size_t m(rawPrices[0].size() - 1);

Mat _prices;
_prices.resize(m,Vec(n));

for(size_t i = 1;i < n+1;++i){
for(size_t j = 1;j < data[i].size();++j){
string tmp = data[i][j];
for(size_t j = 1;j < rawPrices[i].size();++j){
string tmp = rawPrices[i][j];
if(tmp.empty()){
_prices[j-1][i-1] = 99999.;
}
Expand All @@ -47,10 +47,10 @@ double CVaRHistorical(priceData data) {
}
}

vector<string> indexNames(data[0].size() - 1);
vector<string> indexNames(rawPrices[0].size() - 1);

for(size_t i = 1;i < data[0].size();++i){
indexNames[i-1] = data[0][i];
for(size_t i = 1;i < rawPrices[0].size();++i){
indexNames[i-1] = rawPrices[0][i];
}

// Remove missing values to compute trailling returns
Expand All @@ -68,29 +68,21 @@ double CVaRHistorical(priceData data) {
std::shared_ptr<ComputeReturn> cr(new ComputeReturn(prices,1,windowsize,true));

// create portfolio
double a = double(1./m);
std::vector<double> weights{a,a}; //initialization. Equi-weighted asset for mere convenience
Ptf _ptf;
for(size_t i = 0;i < m;++i){
Ptf _ptf;
for(size_t i = 0;i < m;++i){
shared_ptr<Instrument> instrument(new DeltaOne());
auto p = std::make_pair(i,instrument);
_ptf.push_back(p);
}
shared_ptr<Portfolio> ptf(new Portfolio(_ptf, weights, cr, false, 1.e+07));
_ptf.push_back(p);
}
shared_ptr<Portfolio> ptf(new Portfolio(_ptf, weights, cr, false, 1.e+07));

HistoricalVaR model;

double alphatest = .95; // set alpha level, example 0.9 for 95% CVaR

// CVaRhistorical
model.setAlpha(1.0-alphatest);
double CVaRHistorical = model(0,ptf->getReturns());
cout << "CVaRHistorical: " << CVaRHistorical << endl;
double CVaRHistorical = model(0,ptf->getReturns());

return CVaRHistorical;

}

}


}
136 changes: 36 additions & 100 deletions src/CVaRMonteCarlo.cpp
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@@ -1,16 +1,13 @@
//test_ptf_mc_var.cpp
// Portfolio VaR through MC simulation
// from test_ptf_mc_var.cpp

//test portfolio VaR through MC simulation

#include <iostream>
#include <string>
#include <fstream>
#include <sstream>
#include <vector>
#include<memory>

#include <Eigen/Dense>

#include "CVaR.h"

#include "compute_returns_eigen.h"
#include "compute_var.h"
#include "path.h"
Expand All @@ -23,136 +20,75 @@
#include <boost/math/special_functions/erf.hpp>
using boost::math::erfc_inv;

using namespace Eigen;
using namespace std;

void readCSV(std::istream &input, std::vector< std::vector<std::string> > &output)
//https://www.gamedev.net/topic/444193-c-how-to-load-in-a-csv-file/
{
std::string csvLine;
// read every line from the stream
while( std::getline(input, csvLine) )
{
std::istringstream csvStream(csvLine);
std::vector<std::string> csvColumn;
std::string csvElement;
// read every element from the line that is seperated by commas
// and put it into the vector or strings
while( std::getline(csvStream, csvElement, ',') )
{
csvColumn.push_back(csvElement);
}
output.push_back(csvColumn);
}
}


int main()
{

try{

// Read daily price history for crypto assets, in USD
//Date,EOS,DAPP
//2018-11-19,3.5,0.5
//2018-11-20,3.6,0.6

std::fstream file("/home/gg/VaR/test/data.csv", ios::in);
if(!file.is_open())
{
std::cout << "File not found!\n";
return 1;
}
// typedef to save typing for the following object
typedef std::vector< std::vector<std::string> > csvVector;
csvVector csvData;

readCSV(file, csvData);
namespace RiskJS {

//test
for(size_t i = 0;i < 5; ++i){
for(size_t j = 0;j < csvData[i].size();++j){
cout << csvData[i][j] << '\t';

}
using namespace Eigen;
using namespace std;

cout << endl;
}
cout << endl;

double CVaRMonteCarlo(priceData rawPrices, weightData weights, double alphatest) {
// Remove lines with missing values

size_t n(csvData.size() - 1);
size_t m(csvData[0].size() - 1);
size_t n(rawPrices.size() - 1);
size_t m(rawPrices[0].size() - 1);

Mat _prices;
_prices.resize(m,Vec(n));

for(size_t i = 1;i < n+1;++i){
for(size_t j = 1;j < csvData[i].size();++j){
std::string tmp = csvData[i][j];
for(size_t j = 1;j < rawPrices[i].size();++j){
string tmp = rawPrices[i][j];
if(tmp.empty()){
_prices[j-1][i-1] = 99999.;
}
else{
_prices[j-1][i-1] = std::stod(tmp);
_prices[j-1][i-1] = stod(tmp);
}
}
}

std::vector<std::string> indexNames(csvData[0].size() - 1);
vector<string> indexNames(rawPrices[0].size() - 1);

for(size_t i = 1;i < csvData[0].size();++i){
indexNames[i-1] = csvData[0][i];
for(size_t i = 1;i < rawPrices[0].size();++i){
indexNames[i-1] = rawPrices[0][i];
}

//Remove missing values to compute trailling returns
//Asynchornous time series. Shift to the next value
// Remove missing values to compute trailling returns
// Asynchornous time series. Shift to the next value
Mat prices;
prices.resize(m,Vec(0));

for(size_t i = 0;i < _prices.size();++i){
for(size_t j = 0;j < _prices[i].size();++j){
if(!((_prices[i][j] == 99999) || (_prices[i][j] == 0)))
prices[i].push_back(_prices[i][j]);
}
}
for(size_t i = 0;i < _prices.size();++i){
for(size_t j = 0;j < _prices[i].size();++j){
if(!((_prices[i][j] == 99999) || (_prices[i][j] == 0)))
prices[i].push_back(_prices[i][j]);
}
}
unsigned int windowsize = prices[0].size()-2;
std::shared_ptr<ComputeReturn> cr(new ComputeReturn(prices,1,windowsize,true));

// create portfolio
double a = double(1./m);
std::vector<double> weights{a,a}; //initialization. Equi-weighted asset for mere convenience
Ptf _ptf;
for(size_t i = 0;i < m;++i){
shared_ptr<Instrument> instrument(new DeltaOne());
auto p = std::make_pair(i,instrument);
_ptf.push_back(p);
}
shared_ptr<Portfolio> ptf(new Portfolio(_ptf, weights, cr, false, 1.e+07));
Ptf _ptf;
for(size_t i = 0;i < m;++i){
shared_ptr<Instrument> instrument(new DeltaOne());
auto p = std::make_pair(i,instrument);
_ptf.push_back(p);
}
shared_ptr<Portfolio> ptf(new Portfolio(_ptf, weights, cr, false, 1.e+07));

HistoricalVaR model;

double alphatest = .95; // set alpha level, example 0.9 for 95% CVaR

// CVaRMonteCarlo
// Simulate crypto rtn using AR(1)xGARCH(1,1) through brute force Monte-Carlo
std::vector<AR1xGARCH11> processes(2);
// CVaRMonteCarlo
// Simulate crypto rtn using AR(1)xGARCH(1,1) through brute force Monte-Carlo
std::vector<AR1xGARCH11> processes(2);
processes[0] = AR1xGARCH11(); // first crypto asset AR1xGARCH11( 0.,0.5,omega, alpha=.24, beta=.76); note beta, alpha, omega correspond to python arch_model
processes[1] = AR1xGARCH11(); // 2nd crypto asset
Path1x1 process;
rng _rng;
VaRPtfMCCompute<HistoricalVaR, AR1xGARCH11> VaRMonteCarlo(ptf,model, processes, _rng, 1.0-alphatest);
double CVaRMonteCarlo = VaRMonteCarlo.computeVaR();
cout << "CVaRMonteCarlo: " << CVaRMonteCarlo << endl;

return 0;

} catch (const std::exception& e) { // caught by reference to base
std::cout << " a standard exception was caught, with message '"
<< e.what() << "'\n";
}

return CVaRMonteCarlo;
}


}
38 changes: 15 additions & 23 deletions src/CVaRVarianceCovariance.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,7 @@

#include <Eigen/Dense>

#include "ptf_mc_var.h"
#include "CVaR.h"

#include "compute_returns_eigen.h"
#include "compute_var.h"
Expand All @@ -27,17 +27,17 @@ using namespace Eigen;
using namespace std;


double CVaRVarianceCovariance(priceData data) {
double CVaRVarianceCovariance(priceData rawPrices, weightData weights, double alphatest) {
// Remove lines with missing values
size_t n(data.size() - 1);
size_t m(data[0].size() - 1);
size_t n(rawPrices.size() - 1);
size_t m(rawPrices[0].size() - 1);

Mat _prices;
_prices.resize(m,Vec(n));

for(size_t i = 1;i < n+1;++i){
for(size_t j = 1;j < data[i].size();++j){
string tmp = data[i][j];
for(size_t j = 1;j < rawPrices[i].size();++j){
string tmp = rawPrices[i][j];
if(tmp.empty()){
_prices[j-1][i-1] = 99999.;
}
Expand All @@ -47,10 +47,10 @@ double CVaRVarianceCovariance(priceData data) {
}
}

vector<string> indexNames(data[0].size() - 1);
vector<string> indexNames(rawPrices[0].size() - 1);

for(size_t i = 1;i < data[0].size();++i){
indexNames[i-1] = data[0][i];
for(size_t i = 1;i < rawPrices[0].size();++i){
indexNames[i-1] = rawPrices[0][i];
}

// Remove missing values to compute trailling returns
Expand All @@ -68,29 +68,21 @@ double CVaRVarianceCovariance(priceData data) {
std::shared_ptr<ComputeReturn> cr(new ComputeReturn(prices,1,windowsize,true));

// create portfolio
double a = double(1./m);
std::vector<double> weights{a,a}; //initialization. Equi-weighted asset for mere convenience
Ptf _ptf;
for(size_t i = 0;i < m;++i){
Ptf _ptf;
for(size_t i = 0;i < m;++i){
shared_ptr<Instrument> instrument(new DeltaOne());
auto p = std::make_pair(i,instrument);
_ptf.push_back(p);
}
shared_ptr<Portfolio> ptf(new Portfolio(_ptf, weights, cr, false, 1.e+07));
_ptf.push_back(p);
}
shared_ptr<Portfolio> ptf(new Portfolio(_ptf, weights, cr, false, 1.e+07));

HistoricalVaR model;

double alphatest = .95; // set alpha level, example 0.9 for 95% CVaR

// CVaRVarianceCovariance
// as currently used in VIGOR
double CVaRVarianceCovariance = -100.0 * std::log(1.0 + (((std::exp(-1.0*(std::pow(-1.0*std::sqrt(2.0)*erfc_inv(2.0*alphatest),2.0))/2.0)/(std::sqrt(2.0*M_PI)))/(1.0-alphatest)) * (ptf->getPtfSdev()/100)));
cout << "CVaRVarianceCovariance: " << CVaRVarianceCovariance << endl;

return CVaRVarianceCovariance;

}

}


}
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