the goldman sachs group , inc . and subsidiaries notes to consolidated financial statements in the tables above : 2030 the gross fair values exclude the effects of both counterparty netting and collateral netting , and therefore are not representative of the firm 2019s exposure . 2030 counterparty netting is reflected in each level to the extent that receivable and payable balances are netted within the same level and is included in counterparty netting in levels . where the counterparty netting is across levels , the netting is included in cross-level counterparty netting . 2030 derivative assets are shown as positive amounts and derivative liabilities are shown as negative amounts . significant unobservable inputs the table below presents the amount of level 3 assets ( liabilities ) , and ranges , averages and medians of significant unobservable inputs used to value the firm 2019s level 3 derivatives . level 3 assets ( liabilities ) and range of significant unobservable inputs ( average/median ) as of december $ in millions 2017 2016 .
what is the percentage change in net comodities from 2016 to 2017?
in the table above : 2030 derivative assets are shown as positive amounts and derivative liabilities are shown as negative amounts . 2030 ranges represent the significant unobservable inputs that were used in the valuation of each type of derivative . 2030 averages represent the arithmetic average of the inputs and are not weighted by the relative fair value or notional of the respective financial instruments . an average greater than the median indicates that the majority of inputs are below the average . for example , the difference between the average and the median for credit spreads and oil spread inputs indicates that the majority of the inputs fall in the lower end of the range . 2030 the ranges , averages and medians of these inputs are not representative of the appropriate inputs to use when calculating the fair value of any one derivative . for example , the highest correlation for interest rate derivatives is appropriate for valuing a specific interest rate derivative but may not be appropriate for valuing any other interest rate derivative . accordingly , the ranges of inputs do not represent uncertainty in , or possible ranges of , fair value measurements of the firm 2019s level 3 derivatives . 2030 interest rates , currencies and equities derivatives are valued using option pricing models , credit derivatives are valued using option pricing , correlation and discounted cash flow models , and commodities derivatives are valued using option pricing and discounted cash flow models . 2030 the fair value of any one instrument may be determined using multiple valuation techniques . for example , option pricing models and discounted cash flows models are typically used together to determine fair value . therefore , the level 3 balance encompasses both of these techniques . 2030 correlation within currencies and equities includes cross- product type correlation . 2030 natural gas spread represents the spread per million british thermal units of natural gas . 2030 oil spread represents the spread per barrel of oil and refined products . range of significant unobservable inputs the following is information about the ranges of significant unobservable inputs used to value the firm 2019s level 3 derivative instruments : 2030 correlation . ranges for correlation cover a variety of underliers both within one product type ( e.g. , equity index and equity single stock names ) and across product types ( e.g. , correlation of an interest rate and a currency ) , as well as across regions . generally , cross-product type correlation inputs are used to value more complex instruments and are lower than correlation inputs on assets within the same derivative product type . 2030 volatility . ranges for volatility cover numerous underliers across a variety of markets , maturities and strike prices . for example , volatility of equity indices is generally lower than volatility of single stocks . 2030 credit spreads , upfront credit points and recovery rates . the ranges for credit spreads , upfront credit points and recovery rates cover a variety of underliers ( index and single names ) , regions , sectors , maturities and credit qualities ( high-yield and investment-grade ) . the broad range of this population gives rise to the width of the ranges of significant unobservable inputs . 130 goldman sachs 2017 form 10-k .