strategies and to choose the most appropriate strategy, given the prevailing market conditions. formal models help firms with larger risk appetites - - in other words, those willing to take on additional risk - - evaluate their capacity to absorb and manage such risks and to take on the risk shifted from others. i contend that firms with larger appetites for risk will be relatively more willing to take on additional risk if they can model and manage it better. without formal risk management, a firm would still be able, in times of high market volatility, to sense that its risk had risen. but it would be uncertain about exactly how the market volatility had affected it. the firm would, in effect, be flying by the seat of its pants. the uncertainty, it seems clear, would lead to less - effective decisionmaking and less ability to transfer risk to someone willing to bear it since others, too, would face the same uncertainty. greater uncertainty would also heighten the potential that markets would simply seize up. though models in general help reduce uncertainty and increase efficiency, the sophistication and structure of risk - management models vary widely, belying the notion that their use would create herdlike behavior. this point applies with full force to value - at - risk models in use at u. s. commercial banks, a topic about which the federal reserve has gained considerable knowledge through supervisory oversight. our examiners have observed how banks implement a common objective - measuring the value at risk of the bank ’ s trading account - in diverse ways. other sources of diversity among financial firms include differences in customer bases and product lines. these additional sources of variation create considerable heterogeneity in financial firms ’ trading strategies, in their risk - taking, and in their responses to market shocks. nonetheless firms should be aware of the models that their competitors are using and alert to the possibility that a single model could carry undue weight in the assessment of risk in a particular market. still, neither the models nor the actual risk positions are now, or are likely to be, as similar as assumed by observers concerned about the negative implications of model - based risk management. in addition, it would be a mistake to think that decisionmaking at financial firms has become, or is likely to become, so rigidly bound by models that the models would dominate the process in any meaningful sense. judgment, experience, exposure limits, and procedures for exceptions are also significant and, at times, critical, and it is important that

these more traditional elements of risk management continue to play key roles. areas for improvement in risk modeling although i believe that some of the criticisms of recent advances in risk management are misguided, events of the past several years have highlighted several areas for improvement. on balance, formal risk modeling has improved risk management, but making further improvements is important. for example, market participants have been made keenly aware of the implicit assumptions about market liquidity embedded in models and of the ways in which market, credit, and liquidity risk can interact. one common criticism of risk - management models is that they ignore the risk that liquidity may dry up or become depleted in certain markets, making trading difficult, if not impossible. it is certainly true that the first generation of risk - management models did not deal with liquidity in the most sophisticated way, but they did partially address this important issue. for example, the standard measures of value at risk assume that the firm cannot alter its positions for a time as market prices change. in other words, these models assume complete illiquidity throughout a stated holding period. another widely used, but more sophisticated, approach that takes account of liquidity risk is stress testing. unlike value - at - risk models, which usually assume normal market conditions, stress tests help to quantify how much a firm could lose in unusual or stressful scenarios. a typical stress scenario incorporates extremely large shocks of the kind that are almost always associated with reduced market liquidity. in sophisticated cases, these scenarios can be dynamic in that they account for likely changes in the firms ’ positions. a fixed - income dealer, for example, might consider a scenario in which the firm first accumulates a long position in certain bonds because of customer order flow, and then those bonds experience a large price decline at the same time that liquidity decreases or dries up. a survey done last year by the group of ten central banks found that nearly all internationally active banks use stress tests to help them understand their risk profiles and to communicate with senior management. even relatively simple methods can be used, to some extent, to quantify the liquidity risk that firms face. for example, the liquidity of each asset position in an investment portfolio can be measured as the number of days it would take to liquidate that position, assuming that the firm limited its trading on any day to 20 percent of average daily volume. aggregate portfolio liquidity would be the weighted average of this statistic across the entire portfolio. with