Market Dependency

Returns which curves, surfaces and quotes are used when computing the MTM

Parameter Description Default Options
trades
Required
Input trades. Can be QuickTrade, FPML5, LCH, CME or SDR format. If not specified then must specify either portfolios or whatifTrades parameters
valueDate
Optional
The value date in YYYY-MM-DD format.
target
Optional
Target OVERVIEW OVERVIEW , QUOTE_CODES , QUOTE_VALUES
import clarus

response = clarus.market.dependency(trades='USD 10Y 100m pay 1.1%')
print (response)
import com.clarusft.api.model.market.DependencyRequest
import com.clarusft.api.model.market.DependencyResponse

ApiClient clarus = ApiClient.getDefault();
DependencyResponse response = clarus.request(new DependencyRequest().withTrades("USD 10Y 100m pay 1.1%"));
System.out.println(response);
import Clarus

response = Clarus.Market.dependency(trades="USD 10Y 100m pay 1.1%")
print(response)

##
##Need to install packages once, if not already installed
##install.packages('httr')
##install.packages('readr')
##

library('httr')
##library('readr')

## Manually edit and set key/secret here ##
apiKey <- '...'
apiSecret <-'...'

request <- function(category, functionName, ...){
  restUrl  =  paste0('https://apieval.clarusft.com/api/rest/v1/', category, '/',functionName, '.csv')
  response <- POST(url=restUrl, body=list(...), encode='json', authenticate(apiKey, apiSecret, type='basic'))
  if (response$status_code!=200){
      stop(paste0('Request to ', category, '/', functionName, ' failed with status code: ', response$status_code))
  }
  return (response)
}

dataframe <- function(response){
  return (read.csv(text=content(response, 'text'), sep=',', head=TRUE))
}
## filename <- file.path('C:', 'Temp', 'myfile.csv')
## myvalue <- <- read_file(filename)

r <- request('market', 'Dependency', trades='USD 10Y 100m pay 1.1%')
df <- dataframe(r)
print (df)

import requests
import sys
import pandas
import io
#import os

# Example of REST API call to Clarus Microservices #

# Manually edit and set key/secret here #
apiKey = ''
apiSecret = ''

print (sys.version)

def request(category, functionName, **params):
  restUrl = 'https://apieval.clarusft.com/api/rest/v1/' + category + '/' + functionName + '.json'
  r = requests.post(restUrl, json=params, auth=(apiKey, apiSecret))
  r.raise_for_status()
  return r.json()

def dataframe(results):
  return pandas.DataFrame(results['results'])

# filename = os.path.join('C:\\', 'Temp', 'myfile.csv')
# myvalue = open(filename).read()

r = request('market', 'Dependency', trades='USD 10Y 100m pay 1.1%')
df = dataframe(r)
print(pandas.DataFrame.head(df))


use strict;
use warnings;
use MIME::Base64;
use JSON;
use REST::Client;

# Example of REST API call to Clarus Microservices #

my $client = REST::Client->new();
$client->addHeader('Content-Type', 'application/json');

# Manually edit and set key/secret here 
my $apiKey = '';
my $apiSecret = '';

my $encoded_auth = encode_base64("$apiKey:$apiSecret", '');
$client->addHeader('Authorization', "Basic $encoded_auth");

my %params = ('trades' => 'USD 10Y 100m pay 1.1%');

my $urlBase = 'https://apieval.clarusft.com/api/rest/v1/';
my $category = 'market/';
my $name = 'Dependency';
my $outputFormat = '.csv'; #can also be '.json' or '.tsv'
my $fullRESTUrl  =  $urlBase . $category . $name . $outputFormat;

$client->POST($fullRESTUrl,encode_json(\%params));

print 'Response: ' . $client->responseContent() . "\n";
print 'Response status: ' . $client->responseCode() . "\n";


printf('Example of REST API call to Clarus Microservices\n');

function r = request(category, functionName, params)

# Manually edit and set key/secret here #
  apiKey = ''
  apiSecret = ''

  restUrl = ['https://' apiKey ":" apiSecret  "@" 'apieval.clarusft.com/api/rest/v1/' category '/' functionName '.csv'];
  [r, status, message] = urlread (restUrl, 'get', params);
  if (status!=1)
      error(['Failed on ' category '/' functionName ': ' message]);
  endif
end

function ca = toCellArray(csvStr)
  header_row = textscan (csvStr, "%s", 1, 'delimiter','\n');
  headers = strsplit(char(header_row), ",");
  numCols = size(headers)(2);
  format = repmat('%s ', [1 numCols]);
  ca = textscan (csvStr, format, 'delimiter',',', 'endofline',"\n");
end

params = {'trades', 'USD 10Y 100m pay 1.1%'}

r = request('market', 'Dependency', params)
ca = toCellArray(r);

ca

Request Body

Submit to generate...
Response

Submit to generate...

{
  "trades" : "USD 10Y 100m pay 1.1%"
}