Risk Management Terminology & Concepts
Risk Management Terminology and Basic Concepts
Concepts of Risk: broadly speaking, risk is exposure to uncertainty. Uncertainty means it may be losses as well as gains in the future, it is a mix of danger and opportunity.
Expected Loss: loss or cost we can expect in normal business or daily life. These losses are not big threats because they are reasonably predictable and are already allowed for in our plans and are priced in the products and services to the customer. Bad debt, spread, etc.
Unexpected Loss: loss or cost that occurs outside the normal business or daily life. Generally, it is much more difficult to forecast and evaluate, and price-in in advance due to the un-expectation involved. Natural disasters, unfavored events happen together, etc.
Real Risk is that these costs will suddenly rise in an entirely unexpected way, or that some other cost will appear from nowhere and steal the money we’ve set aside for our expected outlays.
Risk Management is about how firms actively select the type of level of risk that it is appropriate for them to assume. Do not think of risk management in a defensive term alone.
Risk Taking is to assume additional risk actively for additional gains. Risk management and risk taking aren’t opposites, but two sides of the same coin.
Problems in the Risk Management Process: two key problems with the process are: (1) identifying the correct risks (2) finding an efficient method of transferring the risk.
Risk types
Challenges in risk management process
Risks are not sufficiently dispersed among willing and able participants in the economy
Failing to consistently assist in preventing market disruptions or preventing financial accounting fraud
Complex derivative trading strategies often overstate the financial position of many entities and understate the level of risk assumed by them
Risk management many only involve risk transfer and does not result in overall risk elimination
Measure and manage risk
Quantitative Measures:
Sensitivity Risk Measures
Value at Risk (VaR)
Qualitative Measures:
Scenario Analysis
Stress testing
Sensitivity Risk Measures
Examine how portfolio value responds to a small change in a single risk factor
Equity exposure measures: Beta
Assets with betas more (less) than 1 are considered more (less) volatile than the market as a whole
Fixed-income exposure measures: duration and convexity
Options risk measures: Delta, Gamma, Vega, etc.
Value at Risk (VaR)
The minimum loss that would be expected a certain percentage of the time over a certain period of time given the assumed market conditions.
Example: the 5% VaR of a portfolio is $2.2 million over a one-day period.
Interpretation: the minimum loss that would be expected to occur over one day 5% of the time is $2.2 million.
Scenario Risk Measures
Provides an estimate of the impact on portfolio value of a set of significant change in multiple risk factors
Stress tests: examine the impact on portfolio of a scenario of extreme changes of risk factors
Historical scenario approach: use a set of changes in risk factors that have actually occurred in the past: change of risk factors in financial crisis for example
Hypothetical scenario approach: use a set of hypothetical change in risk factors, not just those that have happened in the past.
Active Management
Alpha: average return in excess of a benchmark. Benchmark is passive and can be produced without any particular investment knowledge or even human intervention.
Excess return (active returns): Rt Ex = Rt – Rt Bmk
Average excess return: 1/T sum t=1 to t=T Rt Ex
(where there are T observations in the sample)
Tracking error: stdev(Rt Ex)
Tracking error constraints are imposed to ensure a manager does not stray too far from the benchmark. The larger the tracking error, the more freedom the manager has.
Information ratio: the average excess return per unit of risk.
IR = active return/tracking error
Special case: when the benchmark is risk-free rate
IR = Sharpe Ratio = (Rt-Rf)/tracking error
Benchmark matters. Failure to adjust the benchmark for risk can make a huge difference in the alpha. An ideal benchmark is well defined, tradable, replicable, adjusted for risk.
Grinold fundamental law: IR is about IC * the square root of BR
Information coefficient (IC): the correlation of the manager’s forecast with the actual returns
The breath of the strategy (BR): how many bets are taken
Creating alpha: by making bets that deviate from that benchmark. The key to generating alpha is forecasting. How good asset managers are at forecasting; how many bets they take
5 inputs to the portfolio construction process
Current portfolio: near certainty
Alphas: are often unreasonable and subject to hidden biases
Covariances
Transition costs
Active risk aversion: target level of active risk consistent with an active risk aversion