Market Risk Measurement and Assessment

Market Risk Management aims to accurately measure all types of market risks by a comprehensive set of risk metrics reflecting economic and regulatory requirements.

In accordance with economic and regulatory requirements, we measure market and related risks by several key risk metrics:

These measures are viewed as complementary to each other and in aggregate define the market risk framework, by which all businesses can be measured and monitored.

For information on the regulatory capital requirements and RWA for trading market risk including a presentation by approach and risk type please see section “Regulatory Capital Requirements”.

Market Risk Monitoring

Our primary instrument to manage trading market risk is the application of our limit framework. Our Management Board supported by Market Risk Management, sets group-wide value-at-risk, economic capital and portfolio stress testing (extreme) limits for market risk in the trading book. Market Risk Management sub-allocates this overall limit to our Corporate Divisions and individual business units within CB&S (i.e., Global Rates and Credit, Equity, etc.) based on anticipated business plans and risk appetite. Within the individual business units, the business heads establish business limits, by allocating the limit down to individual portfolios or geographical regions.

In practice, Market Risk Management sets key limits, which tend to be global in nature, to capture an exposure to a particular risk factor. Business limits are specific to various factors, including a particular geographical region or specific portfolio.

Value-at-risk, stressed value-at-risk and economic capital limits are used for managing all types of market risk at an overall portfolio level. As an additional and complementary tool for managing certain portfolios or risk types, Market Risk Management performs risk analysis and stress testing. Limits are also set on sensitivity and concentration/liquidity, portfolio stress tests, business-level stress testing and event risk scenarios.

Business units are responsible for adhering to the limits against which exposures are monitored and reported. The market risk limits set by Market Risk Management are monitored on a daily, weekly and monthly basis. Where limits are exceeded, Market Risk Management is responsible for identifying and escalating those excesses on a timely basis.

To manage the exposures inside the limits, the business units apply several risk mitigating measures, most notably the use of:

  • Portfolio management: Risk diversification arises in portfolios which consist of a variety of positions. Since some investments are likely to rise in value when others decline, diversification can help to lower the overall level of risk profile of a portfolio.
  • Hedging: Hedging involves taking positions in related financial assets, such as futures and swaps, and includes derivative products, such as futures, swaps and options. Hedging activities may not always provide effective mitigation against losses due to differences in the terms, specific characteristics or other basis risks that may exist between the hedge instrument and the exposure being hedged.

Market Risk Reporting

Market Risk Management reporting creates transparency on the risk profile and facilitates the understanding of core market risk drivers to all levels of the organization. The Management Board and Senior Governance Committees receive regular reporting, as well as ad hoc reporting as required, on market risk, regulatory capital and stress testing. Senior Risk Committees receive risk information at a number of frequencies, including weekly or monthly.

Additionally, Market Risk Management produces daily and weekly Market Risk specific reports and daily limit excess reports for each asset class.

Market Risk Measurement

Value-at-Risk at Deutsche Bank Group (excluding Postbank)

Value-at-risk is a quantitative measure of the potential loss (in value) of trading positions due to market movements that will not be exceeded in a defined period of time and with a defined confidence level.

Our value-at-risk for the trading businesses is based on our own internal model. In October 1998, the German Banking Supervisory Authority (now the BaFin) approved our internal value-at-risk model for calculating the regulatory market risk capital for our general and specific market risks. Since then the model has been continually refined and approval has been maintained.

We calculate value-at-risk using a 99 % confidence level and a one day holding period. This means we estimate there is a 1 in 100 chance that a mark-to-market loss from our trading positions will be at least as large as the reported value-at-risk. For regulatory purposes, which include the calculation of our capital requirements and risk-weighted assets, the holding period is ten days.

We use one year of historical market data to calculate value-at-risk. The calculation employs a Monte Carlo Simulation technique, and we assume that changes in risk factors follow a well-defined distribution, e.g. normal, lognormal, or non-normal (t, skew-t, Skew-Normal). To determine our aggregated value-at-risk, we use observed correlations between the risk factors during this one year period.

Our value-at-risk model is designed to take into account a comprehensive set of risk factors across all asset classes. Key risk factors are swap/government curves, index and issuer-specific credit curves, funding spreads, single equity and index prices, foreign exchange rates, commodity prices as well as their implied volatilities. To help ensure completeness in the risk coverage, second order risk factors, e.g. CDS index vs. constituent basis, money market basis, implied dividends, option-adjusted spreads and precious metals lease rates are considered in the value-at-risk calculation.

For each business unit a separate value-at-risk is calculated for each risk type, e.g. interest rate risk, credit spread risk, equity risk, foreign exchange risk and commodity risk. For each risk type this is achieved by assigning the sensitivities to the relevant risk type and then simulating changes in the associated risk drivers. “Diversification effect” reflects the fact that the total value-at-risk on a given day will be lower than the sum of the value-at-risk relating to the individual risk types. Simply adding the value-at-risk figures of the individual risk types to arrive at an aggregate value-at-risk would imply the assumption that the losses in all risk types occur simultaneously.

The model incorporates both linear and, especially for derivatives, nonlinear effects through a combination of sensitivity-based and full revaluation approach on a fixed price-implied volatility grid.

The value-at-risk measure enables us to apply a consistent measure across all of our trading businesses and products. It allows a comparison of risk in different businesses, and also provides a means of aggregating and netting positions within a portfolio to reflect correlations and offsets between different asset classes. Furthermore, it facilitates comparisons of our market risk both over time and against our daily trading results.

When using value-at-risk estimates a number of considerations should be taken into account. These include:

  • The use of historical market data may not be a good indicator of potential future events, particularly those that are extreme in nature. This “backward-looking” limitation can cause value-at-risk to understate risk (as in 2008), but can also cause it to be overstated.
  • Assumptions concerning the distribution of changes in risk factors, and the correlation between different risk factors, may not hold true, particularly during market events that are extreme in nature. The one day holding period does not fully capture the market risk arising during periods of illiquidity, when positions cannot be closed out or hedged within one day.
  • Value-at-risk does not indicate the potential loss beyond the 99th quantile.
  • Intra-day risk is not captured.
  • There may be risks in the trading book that are partially or not captured by the value-at-risk model.

We are committed to the ongoing development of our proprietary risk models, and we allocate substantial resources to reviewing and improving them. Additionally, we have further developed and improved our process of systematically capturing and evaluating risks currently not captured in our value-at-risk model. An assessment is made to determine the level of materiality of these risks and material risks are prioritized for inclusion in our internal model. All risks not in value-at-risk are monitored and assessed on a regular basis.

During 2013, improvements were made to the value-at-risk calculation, with the inclusion of the following risks in our internal model:

  • Higher-order risk in commodities to capture P&L moves due to joint movements in underlying commodity price and volatilities;
  • Risk associated with the volatility skew and smile with options on precious metals;
  • Moves in the repo rate for equity repurchase agreements;
  • Credit spread movements between subordinated and senior debt in credit;
  • Joint moves of swap rates and cross-currency basis spreads for cross-currency swaps.

Existing methodology has been rolled-out to further books to capture:

  • Dividend risk
  • CDS quanto for all sovereigns and corporates
  • Money market basis risks.

The ability of using nonnormal distributions (NND) in the modeling of the risk factor return time series has also been extended from FX and commodity to include all risk factors.

Additionally, market data granularity was increased further by distinguishing between first generation commercial mortgage backed securities (CMBS 1.0) and next generation CMBS 2.0. CMBS 2.0 products have more conservative underwriting and securitization standards than compared to CMBS 1.0, therefore meriting a separate market data time series.

Regulatory Backtesting of Trading Market Risk

We continually analyze potential weaknesses of our value-at-risk model using statistical techniques, such as backtesting, and also rely on risk management experience.

Backtesting is a procedure we use in accordance with German regulatory requirements to verify the predictive power of our value-at-risk calculations involving the comparison of hypothetical daily profits and losses under the buy-and-hold assumption. Under this assumption we estimate the P&L impact that would have resulted on a portfolio for a trading day valued with current market prices and parameters assuming it had been left untouched for that day and compare it with the estimates from the value-at-risk model from the preceding day. An outlier is a hypothetical buy-and-hold trading loss that exceeds our value-at-risk from the preceding day. On average, we would expect a 99 % confidence level to give rise to two to three outliers representing 1 % of approximately 260 trading days in any one year. We analyze and document underlying reasons for outliers and classify them either as due to market movements, risks not included in our value-at-risk model, model or process shortcomings. We use the results for further enhancement of our value-at-risk methodology. Formal communications explaining the reasons behind any outlier on Group level are provided to the BaFin.

In addition to the standard backtesting analysis at the value-at-risk quantile, the value-at-risk model performance is further verified by analyzing the distributional fit across the whole of the distribution (full distribution backtesting). Regular backtesting is also undertaken on hypothetical portfolios to test value-at-risk performance of particular products and their hedges.

The Global Backtesting Committee, with participation from Market Risk Management, Market Risk Operations, Risk Analytics and Living Wills, and Finance, meets on a regular basis to review backtesting results as a whole and of individual businesses. The committee analyzes performance fluctuations and assesses the predictive power of our value-at-risk model, which allows us to improve and adjust the risk estimation process accordingly.

An independent model validation team reviews all quantitative aspects of our value-at-risk model on a regular basis. The review covers, but is not limited to, the appropriateness of distribution assumptions of risk factors, recalibration approaches for risk parameters, and model assumptions. Validation results and remediation measures are presented to senior management and are tracked to ensure adherence to deadlines.

Holistic VaR Validation process

The Holistic VaR Validation (HVV) process provides a comprehensive assessment of the value-at-risk model and framework across five control areas: Limits, Backtesting, Process, Model Validation, and Risks-not-in-VaR. HVV runs on a quarterly basis and provides a detailed report for each of the control areas (HVV Control Packs) as well as an HVV Dashboard indicating the health of each control area. In addition the Quarterly Business Line Review (QBLR) provides an overview of the business line trading strategy and the corresponding risk return profile. The associated formal quarterly HVV governance framework is as follows:

  • Level 1: A series of asset-class level HVV Control Pack Review meetings (chaired by the respective Market Risk Management Asset Class Head), at which the HVV Control Pack is reviewed and the HVV Dashboard status is agreed
  • Level 2: The HVV Governance Committee (chaired by the Global Head of Market Risk Management), at which the QBLRs are presented and the overall HVV Dashboard is agreed
  • Level 3: Top-level HVV governance is achieved via a series of senior management briefings including to the CB&S Executive Committee, the Capital and Risk Committee, the Management Board and the Supervisory Board. The briefings provide an executive summary of the quality and control of value-at-risk across the business, an overview of the CB&S business trading strategy and the corresponding risk management strategy.

In 2013, our value-at-risk and stressed value-at-risk multipliers remained at 4 vs. the regulatory floor of 3.

Market Risk Stress Testing

Stress testing is a key risk management technique, which evaluates the potential effects of extreme market events and extreme movements in individual risk factors. It is one of the core quantitative tools used to assess the market risk of Deutsche Bank’s positions and complements VaR and Economic Capital. Market Risk Management performs several types of stress testing to capture the variety of risks: Portfolio stress testing, individual business-level stress tests, Event Risk Scenarios, and also contributes to Group-wide stress testing.

Portfolio stress testing measures the profit and loss impact of potential market events based on pre-defined scenarios of different severities, which are either historical or hypothetical and defined at a macro level. With Portfolio Stress Testing, Market Risk Management completes its perspective on risk provided by other metrics, given that the range of portfolio stress tests fills the gap between the most extreme scenarios (economic capital) and potential daily losses (value-at-risk). Besides dynamic scenarios, we have three static scenarios, which are calculated and monitored on a weekly basis against limits.

For individual business-level stress tests, market risk managers identify relevant risk factors and develop stress scenarios relating either to macro-economic or business-specific developments. Business-level stress tests capture idiosyncratic and basis risks.

Event risk scenario measures the profit and loss impact of historically observable events or hypothetical situations on trading positions for specific emerging market countries and regions. The bank’s trading book exposure to an individual country is stressed under a single scenario, which replicates market movements across that country in times of significant market crisis and reduced liquidity.

Besides these market-risk specific stress tests, Market Risk Management participates in the Group-wide stress test process, where macro-economic scenarios are defined by DB research and each risk department translates that same scenario to the relevant shocks required to apply to their portfolio. This includes credit, market and operational risks. Results are reviewed by the Stress Testing Oversight Committee.

Tail risk or the potential for extreme loss events beyond reported value-at risk is captured via stressed value-at-risk, economic capital, incremental risk charge and comprehensive risk measure. It is also captured via stress testing.