{"pre_text": ["jpmorgan chase & co./2016 annual report 103 risk in the derivatives portfolio .", "in addition , the firm 2019s risk management process takes into consideration the potential impact of wrong-way risk , which is broadly defined as the potential for increased correlation between the firm 2019s exposure to a counterparty ( avg ) and the counterparty 2019s credit quality .", "many factors may influence the nature and magnitude of these correlations over time .", "to the extent that these correlations are identified , the firm may adjust the cva associated with that counterparty 2019s avg .", "the firm risk manages exposure to changes in cva by entering into credit derivative transactions , as well as interest rate , foreign exchange , equity and commodity derivative transactions .", "the accompanying graph shows exposure profiles to the firm 2019s current derivatives portfolio over the next 10 years as calculated by the peak , dre and avg metrics .", "the three measures generally show that exposure will decline after the first year , if no new trades are added to the portfolio .", "exposure profile of derivatives measures december 31 , 2016 ( in billions ) the following table summarizes the ratings profile by derivative counterparty of the firm 2019s derivative receivables , including credit derivatives , net of all collateral , at the dates indicated .", "the ratings scale is based on the firm 2019s internal ratings , which generally correspond to the ratings as defined by s&p and moody 2019s .", "ratings profile of derivative receivables rating equivalent 2016 2015 ( a ) december 31 , ( in millions , except ratios ) exposure net of all collateral % (  % ) of exposure net of all collateral exposure net of all collateral % (  % ) of exposure net of all collateral ."], "post_text": ["( a ) prior period amounts have been revised to conform with the current period presentation .", "as previously noted , the firm uses collateral agreements to mitigate counterparty credit risk .", "the percentage of the firm 2019s derivatives transactions subject to collateral agreements 2014 excluding foreign exchange spot trades , which are not typically covered by collateral agreements due to their short maturity 2014 was 90% ( 90 % ) as of december 31 , 2016 , largely unchanged compared with 87% ( 87 % ) as of december 31 , 2015 .", "credit derivatives the firm uses credit derivatives for two primary purposes : first , in its capacity as a market-maker , and second , as an end-user to manage the firm 2019s own credit risk associated with various exposures .", "for a detailed description of credit derivatives , see credit derivatives in note 6 .", "credit portfolio management activities included in the firm 2019s end-user activities are credit derivatives used to mitigate the credit risk associated with traditional lending activities ( loans and unfunded commitments ) and derivatives counterparty exposure in the firm 2019s wholesale businesses ( collectively , 201ccredit portfolio management 201d activities ) .", "information on credit portfolio management activities is provided in the table below .", "for further information on derivatives used in credit portfolio management activities , see credit derivatives in note 6 .", "the firm also uses credit derivatives as an end-user to manage other exposures , including credit risk arising from certain securities held in the firm 2019s market-making businesses .", "these credit derivatives are not included in credit portfolio management activities ; for further information on these credit derivatives as well as credit derivatives used in the firm 2019s capacity as a market-maker in credit derivatives , see credit derivatives in note 6. ."], "table": [["rating equivalent december 31 ( in millions except ratios )", "rating equivalent exposure net of all collateral", "rating equivalent % (  % ) of exposure netof all collateral", "exposure net of all collateral", "% (  % ) of exposure netof all collateral"], ["aaa/aaa to aa-/aa3", "$ 11449", "28% ( 28 % )", "$ 10371", "24% ( 24 % )"], ["a+/a1 to a-/a3", "8505", "20", "10595", "25"], ["bbb+/baa1 to bbb-/baa3", "13127", "32", "13807", "32"], ["bb+/ba1 to b-/b3", "7308", "18", "7500", "17"], ["ccc+/caa1 and below", "984", "2", "824", "2"], ["total", "$ 41373", "100% ( 100 % )", "$ 43097", "100% ( 100 % )"]], "table_ori": [["Rating equivalent", "2016", "2015<sup>(a)</sup>"], ["December 31,(in millions, except ratios)", "Exposure net of all collateral", "% of exposure netof all collateral", "Exposure net of all collateral", "% of exposure netof all collateral"], ["AAA/Aaa to AA-/Aa3", "$11,449", "28%", "$10,371", "24%"], ["A+/A1 to A-/A3", "8,505", "20", "10,595", "25"], ["BBB+/Baa1 to BBB-/Baa3", "13,127", "32", "13,807", "32"], ["BB+/Ba1 to B-/B3", "7,308", "18", "7,500", "17"], ["CCC+/Caa1 and below", "984", "2", "824", "2"], ["Total", "$41,373", "100%", "$43,097", "100%"]]}

Question: what percentage of the 2015 ratings profile of derivative receivables had a rating equivalent for junk ratings?
Evidence:
table_4: rating equivalent december 31 ( in millions except ratios ) the bb+/ba1 to b-/b3 of rating equivalent exposure net of all collateral is 7308 ; the bb+/ba1 to b-/b3 of rating equivalent % ( % ) of exposure netof all collateral is 18 ; the bb+/ba1 to b-/b3 of exposure net of all collateral is 7500 ; the bb+/ba1 to b-/b3 of % ( % ) of exposure netof all collateral is 17 ;
Program: add(17, const_2)
Answer:
str_answer: 19
exe_answer: 19