Market Risk Discussion:Focus only on the way price risk in the trading portfolios is presented by Citigroup.

Citigroup includes a detailed discussion and analysis of Market Risk in its trading portfolios in its 10-K report. Compare 2005 and 2018 to answer the below questions.

10-K for 2018:Refer to Portfolio 2018 attachment-

approval, permitted product lists, and pre-trade approval for larger, more complex and less liquid transactions. The following chart of total daily trading-related revenue (loss) captures trading volatility and shows the number of days in which revenues for Citi's trading businesses fell within particular ranges. Trading-related revenue includes trading, net interest and other revenue associated with Citi's trading businesses. It excludes DVA, FVA and CVA adjustments incurred due to changes in the credit quality of counterparties, as well as any associated hedges to that CVA. In addition, it excludes fees and other revenue associated with capital markets origination activities. Trading-related revenues are driven by both customer flows and the changes in valuation of the trading inventory. As shown in the chart, positive tradingrelated revenue was achieved for 98.1% of the trading days in 2018. Market Risk of Trading Portfolios Trading portfolios include positions resulting from market making activities, hedges of certain available-for-sale (AFS) debt securities, the CVA relating to derivative counterparties and all associated hedges, fair value option loans, hedges to the loan portfolio within capital markets origination within ICG. The market risk of Citi's trading portfolios is monitored using a combination of quantitative and qualitative measures, including, but not limited to: factor sensitivities; value at risk (VAR); and stress testing. Each trading portfolio across Citi's businesses has its own market risk limit framework encompassing these measures and other controls, including trading mandates, new product Daily Trading-Related Revenue (Loss)(1) Twelve Months ended December 31, 2018 In millions of dollars (1) Reflects the effects of asymmetrical accounting for economic hedges of certain AFS debt securities. Specifically, the change in the fair value of hedging derivatives is included in Trading-related revenue, while the offsetting change in the fair value of hedged AFS debt securities is included in AOCI and not reflected above. 101 TRIAL MODE Click here for more information HTM. For information on these securities, see Note 13 to the Consolidated Financial Statements. Citi believes its VAR model is conservatively calibrated to incorporate fat-tail scaling and the greater of short-term (approximately the most recent month) and long-term (three years) market volatility. The Monte Carlo simulation involves approximately 450,000 market factors, making use of approximately 350,000 time series, with sensitivities updated daily, volatility parameters updated intra-month and correlation parameters updated monthly. The conservative features of the VAR calibration contribute an approximate 20% add-on to what would be a VAR estimated under the assumption of stable and perfectly, normally distributed markets. As shown in the table below, Citi's average trading VAR modestly decreased in 2018 compared to the prior year, mainly due to a minor reduction in average credit spreads, partially offset by a minor increase in interest rate exposure within ICG. Additionally, among secondary factors with limited contribution to Citi's average VAR, equity risk increased mainly due to exposure changes in the Equities business, partially offset by a modest decrease in commodity exposures within ICG. The decrease in Citi's average trading and credit portfolio VAR from 2018 was in line with the decrease in average trading VAR, as the average incremental impact of the credit portfolio was unchanged. Factor Sensitivities Factor sensitivities are expressed as the change in the value of a position for a defined change in a market risk factor, such as a change in the value of a U.S. Treasury bill for a one-basispoint change in interest rates. Citi's market risk management, within the Risk organization, works to ensure that factor sensitivities are calculated, monitored and limited for all material risks taken in the trading portfolios. Value at Risk (VAR) VAR estimates, at a 99% confidence level, the potential decline in the value of a position or a portfolio under normal market conditions assuming a one-day holding period. VAR statistics, which are based on historical data, can be materially different across firms due to differences in portfolio composition, differences in VAR methodologies and differences in model parameters. As a result, Citi believes VAR statistics can be used more effectively as indicators of trends in risk-taking within a firm, rather than as a basis for inferring differences in risk-taking across firms. Citi uses a single, independently approved Monte Carlo simulation VAR model (see "VAR Model Review and Validation" below), which has been designed to capture material risk sensitivities (such as first- and second-order sensitivities of positions to changes in market prices) of various asset classes/risk types (such as interest rate, credit spread, foreign exchange, equity and commodity risks). Citi's VAR includes positions which are measured at fair value; it does not include investment securities classified as AFS or Year-end and Average Trading VAR and Trading and Credit Portfolio VAR December 31, 2018 In millions of dollars Interest rate $ Credit spread Covariance adjustment(1) Fully diversified interest rate and credit spread(2) December 31, 2017 2018 Average 2017 Average 48 $ 60 $ 69 $ 58 55 47 54 48 (23) (24) (25) (20) 80 $ 83 $ 98 $ 86 Foreign exchange 18 25 25 25 Equity 25 22 17 15 $ Commodity Covariance adjustment(1) Total trading VARall market risk factors, including general and specific risk (excluding credit portfolios)(2) Specific risk-only component (3) $ 23 19 17 22 (66) (67) (63) (64) 80 $ 82 $ 94 $ 84 $ 4 $ 4 $ $ 1 Total trading VARgeneral market risk factors only (excluding credit portfolios) $ 76 $ 78 $ 94 $ 83 Incremental impact of the credit portfolio(4) $ 18 $ 10 $ 11 $ 10 Total trading and credit portfolio VAR $ 98 $ 92 $ 105 $ 94 (1) (2) (3) (4) Covariance adjustment (also known as diversification benefit) equals the difference between the total VAR and the sum of the VARs tied to each individual risk type. The benefit reflects the fact that the risks within each and across risk types are not perfectly correlated and, consequently, the total VAR on a given day will be lower than the sum of the VARs relating to each individual risk type. The determination of the primary drivers of changes to the covariance adjustment is made by an examination of the impact of both model parameter and position changes. The total trading VAR includes mark-to-market and certain fair value option trading positions in ICG, with the exception of hedges to the loan portfolio, fair value option loans and all CVA exposures. Available-for-sale and accrual exposures are not included. The specific risk-only component represents the level of equity and fixed income issuer-specific risk embedded in VAR. The credit portfolio is composed of mark-to-market positions associated with non-trading business units, the CVA relating to derivative counterparties and all associated CVA hedges. FVA and DVA are not included. The credit portfolio also includes hedges to the loan portfolio, fair value option loans and hedges within capital markets origination in ICG. 102 TRIAL MODE Click here for more information The table below provides the range of market factor VARs associated with Citi's total trading VAR, inclusive of specific risk: 2017 2018 Low In millions of dollars Interest rate $ Credit spread 38 Fully diversified interest rate and credit spread $ Low High 34 $ 59 $ High 89 $ 29 $ 64 38 118 $ 59 $ 97 63 109 Foreign exchange 13 44 16 49 Equity 15 33 6 27 27 13 Commodity 13 Total trading $ Total trading and credit portfolio 31 56 $ 120 $ 58 $ 116 66 124 67 123 Note: No covariance adjustment can be inferred as the high and low for each market factor will be from different close-of-business dates. The following table provides the VAR for ICG, excluding the CVA relating to derivative counterparties, hedges of CVA, fair value option loans and hedges to the loan portfolio: In millions of dollars composition of Risk Management VAR is discussed under "Value at Risk" above. The applicability of the VAR model for positions eligible for market risk treatment under U.S. regulatory capital rules is periodically reviewed and approved by Citi's U.S. banking regulators. In accordance with Basel III, Regulatory VAR includes all trading book-covered positions and all foreign exchange and commodity exposures. Pursuant to Basel III, Regulatory VAR excludes positions that fail to meet the intent and ability to trade requirements and are therefore classified as non-trading book and categories of exposures that are specifically excluded as covered positions. Regulatory VAR excludes CVA on derivative instruments and DVA on Citi's own fair value option liabilities. CVA hedges are excluded from Regulatory VAR and included in credit risk-weighted assets as computed under the Advanced Approaches for determining riskweighted assets. Dec. 31, 2018 Totalall market risk factors, including general and specific risk $ 79 Averageduring year $ 81 Highduring year 120 Lowduring year 55 VAR Model Review and Validation Generally, Citi's VAR review and model validation process entails reviewing the model framework, major assumptions and implementation of the mathematical algorithm. In addition, as part of the model validation process, product specific back-testing on portfolios is periodically completed and reviewed with Citi's U.S. banking regulators. Furthermore, Regulatory VAR back-testing (as described below) is performed against buy-and-hold profit and loss on a monthly basis for multiple sub-portfolios across the organization (trading desk level, ICG business segment and Citigroup) and the results are shared with U.S. banking regulators. Significant VAR model and assumption changes must be independently validated within Citi's risk management organization. This validation process includes a review by model validation group within Citi's Model Risk Management. In the event of significant model changes, parallel model runs are undertaken prior to implementation. In addition, significant model and assumption changes are subject to the periodic reviews and approval by Citi's U.S. banking regulators. Citi uses the same independently validated VAR model for both Regulatory VAR and Risk Management VAR (i.e., total trading and total trading and credit portfolios VARs) and, as such, the model review and validation process for both purposes is as described above. Regulatory VAR, which is calculated in accordance with Basel III, differs from Risk Management VAR due to the fact that certain positions included in Risk Management VAR are not eligible for market risk treatment in Regulatory VAR. The Regulatory VAR Back-Testing In accordance with Basel III, Citi is required to perform backtesting to evaluate the effectiveness of its Regulatory VAR model. Regulatory VAR back-testing is the process in which the daily one-day VAR, at a 99% confidence interval, is compared to the buy-and-hold profit and loss (i.e., the profit and loss impact if the portfolio is held constant at the end of the day and re-priced the following day). Buy-and-hold profit and loss represents the daily mark-to-market profit and loss attributable to price movements in covered positions from the close of the previous business day. Buy-and-hold profit and loss excludes realized trading revenue, net interest, fees and commissions, intra-day trading profit and loss and changes in reserves. Based on a 99% confidence level, Citi would expect two to three days in any one year where buy-and-hold losses exceeded the Regulatory VAR. Given the conservative calibration of Citi's VAR model (as a result of taking the greater of short- and long-term volatilities and fat-tail scaling of volatilities), Citi would expect fewer exceptions under normal and stable market conditions. Periods of unstable market conditions could increase the number of back-testing exceptions. The following graph shows the daily buy-and-hold profit and loss associated with Citi's covered positions compared to 103 TRIAL MODE Click here for more information Citi's one-day Regulatory VAR during 2018. As of December 31, 2018, there was one back-testing exception observed for Citi's Regulatory VAR for the prior 12 months, due to market moves triggered by political events in Italy. The difference between the 49.8% of days with buy-andhold gains for Regulatory VAR back-testing and the 98.1% of days with trading, net interest and other revenue associated with Citi's trading businesses, shown in the histogram of daily trading-related revenue below, reflects, among other things, that a significant portion of Citi's trading-related revenue is not generated from daily price movements on these positions and exposures, as well as differences in the portfolio composition of Regulatory VAR and Risk Management VAR. Regulatory Trading VAR and Associated Buy-and-Hold Profit and Loss(1)12 Months ended December 31, 2018 In millions of dollars (1) Buy-and-hold profit and loss, as defined by the banking regulators under Basel III, represents the daily mark-to-market revenue movement attributable to the trading position from the close of the previous business day. Buy-and-hold profit and loss excludes realized trading revenue and net interest intra-day trading profit and loss on new and terminated trades, as well as changes in reserves. Therefore, it is not comparable to the trading-related revenue presented in the chart of daily trading-related revenue above. 104 TRIAL MODE Click here for more information Stress Testing Citi performs market risk stress testing on a regular basis to estimate the impact of extreme market movements. It is performed on individual positions and trading portfolios, as well as in aggregate, inclusive of multiple trading portfolios. Citi's market risk management, after consultations with the businesses, develops both systemic and specific stress scenarios, reviews the output of periodic stress testing exercises, and uses the information to assess the ongoing appropriateness of exposure levels and limits. Citi uses two complementary approaches to market risk stress testing across all major risk factors (i.e., equity, foreign exchange, commodity, interest rate and credit spreads): top-down systemic stresses and bottom-up business-specific stresses. Systemic stresses are designed to quantify the potential impact of extreme market movements on an institution-wide basis, and are constructed using both historical periods of market stress and projections of adverse economic scenarios. Business-specific stresses are designed to probe the risks of particular portfolios and market segments, especially those risks that are not fully captured in VAR and systemic stresses. The systemic stress scenarios and business-specific stress scenarios at Citi are used in several reports reviewed by senior management and also to calculate internal risk capital for trading market risk. In general, changes in market values are defined over a one-year horizon. For the most liquid positions and market factors, changes in market values are defined over a shorter two-month horizon. The limited set of positions and market factors whose market value changes are defined over a two-month horizon are those that in management's judgment have historically remained very liquid during financial crises, even as the trading liquidity of most other positions and market factors materially declined. 105 TRIAL MODE Click here for more information