management 2019s discussion and analysis 118 jpmorgan chase & co./2018 form 10-k equivalent to the risk of loan exposures . dre is a less extreme measure of potential credit loss than peak and is used as an input for aggregating derivative credit risk exposures with loans and other credit risk . finally , avg is a measure of the expected fair value of the firm 2019s derivative receivables at future time periods , including the benefit of collateral . avg over the total life of the derivative contract is used as the primary metric for pricing purposes and is used to calculate credit risk capital and the cva , as further described below . the fair value of the firm 2019s derivative receivables incorporates cva to reflect the credit quality of counterparties . cva is based on the firm 2019s avg to a counterparty and the counterparty 2019s credit spread in the credit derivatives market . the firm believes that active risk management is essential to controlling the dynamic credit 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 contracts , as well as interest rate , foreign exchange , equity and commodity derivative contracts . 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 , 2018 ( in billions ) the following table summarizes the ratings profile 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 assigned by s&p and moody 2019s . ratings profile of derivative receivables .

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 $ 11831 31% ( 31 % ) $ 11529 29% ( 29 % ) a+/a1 to a-/a3 7428 19 6919 17 bbb+/baa1 to bbb-/baa3 12536 32 13925 34 bb+/ba1 to b-/b3 6373 16 7397 18 ccc+/caa1 and below 723 2 645 2 total $ 38891 100% ( 100 % ) $ 40415 100% ( 100 % )

as previously noted , the firm uses collateral agreements to mitigate counterparty credit risk . the percentage of the firm 2019s over-the-counter derivative transactions subject to collateral agreements 2014 excluding foreign exchange spot trades , which are not typically covered by collateral agreements due to their short maturity and centrally cleared trades that are settled daily 2014 was approximately 90% ( 90 % ) at both december 31 , 2018 , and december 31 , 2017. .

Question: what is the percentual fluctuation of the aaa/aaa to aa-/aa3's exposure net of all collateral in relation with the bb+/ba1 to b-/b3 during 2017 and 2018?
Answer: 4%
Calculation: subtract(subtract(18, 16), subtract(29%, 31%))
Explanation: its the difference between those percentual variations during 2017 and 2018 .