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Q & A with John Hull, author of Risk Management and Financial Institutions

What caused the credit crisis that started in 2007?
Among the factors underlying the crisis are: the U.S. government's desire to encourage home ownership, low interest rates, irrational exuberance, inappropriate incentives, regulatory arbitrage, lax lending standards, too much reliance on credit ratings, a lack of understanding of the criteria used by credit rating agencies, and an unwillingness to listen to risk managers.

One key lesson from the crisis is that correlations always increase in stressed market conditions. (For example, the correlation between default rates in California and Florida during the crisis was much higher than usual. ) Another lesson is that, for almost any asset class, the recovery rates of lenders decline when default rates increase. (We have all heard stories of houses during the crisis selling for as little as 25% of their pre-crisis values.)

How are over-the-counter markets changing?
In the past, trades in the over-the-counter (OTC) market have usually been cleared bilaterally. This means that, when two parties A and B agree on a trade, they are responsible for handling payments and managing credit risk. Usually they have entered into what is known as an ISDA Master Agreement. This covers all their trades and defines the collateral that must be posted, what happens if one side fails to live up to its obligations, and so on.

This is changing. OTC markets are becoming more like the exchange-traded markets. There is a requirement that OTC transactions be executed whenever possible on either exchanges or what are known as swap execution facilities (SEFs). A SEF is an electronic platform where market participants can post bids and offers or accept the bids or offers of other market participants to complete trades.

There is also a requirement that standardized OTC trades (with a few exceptions) be cleared through central clearing parties (CCPs). This means that once a trade has been agreed it is presented to a CCP and the CCP stands between the two parties. For example, suppose A and B have agreed to an interest rate swap where A pays a fixed rate of interest of 5% to B and receives the LIBOR rate of interest from B. The CCP would enter into two offsetting transactions. It would pay LIBOR to A and receive the fixed rate from A. It would pay the fixed rate to B and receive LIBOR from B. Similarly to an exchange clearinghouse, it would require collateral in the form of initial margin and maintenance margin from both parties. The new rules will have a huge effect on OTC markets. Prior to the crisis about 25% of OTC trades were handled by CCPs. After the new rules come into force this is expected to rise to 75%. Non-standard trades will continue to be cleared bilaterally, but they have not escaped the attention of regulators. They will usually have to be well collateralized and will be subject to relatively high capital requirements.

How will Basel III affect banks?
Basel III is being phased in over several years. Banks will be required to keep much more equity capital than previously and the rules defining what constitutes equity capital will be tightened. This means that it will be more difficult for banks to reach their return on equity (ROE) targets. In theory, shareholders should be prepared to accept a lower ROE than before because banks are less risky. In practice, this may not be the case. Indeed, it is conceivable that the rules will prove to be counterproductive in that they will lead to banks seeking higher returns by taking more risks--particularly if they can find ways of doing so that do not generate higher regulatory equity capital requirements.

Basel III has for the first time introduced minimum liquidity requirements for banks. These requirements will lead banks to search for stable sources of funding and liquid investments. Retail deposits are considered more stable than wholesale deposits and so we may see more competition among banks for retail deposits. Banks will be under pressure to get illiquid assets off their balance sheets. They are therefore likely to find the securitization of loans even more attractive than they have in the past.

Is value at risk the best risk measure?
Value at risk (VaR) has the advantage of simplicity. It answers the question senior managers tend to be most interested in: "How much could we lose?" To be more precise, it answers the question "What loss level are we X% certain will not be exceeded in time T?" It is natural to ask whether, if we are to represent risk by a single number, VaR is the best number.

Apart from simplicity, one advantage of VaR is that it can be back-tested fairly easily. (A bank can calculate what results it would have got if its current procedures for estimating VaR had been used in the past and keep track of how often the VaR level would have been exceeded.) One undesirable property of VaR is that it does not necessarily reflect the benefits of diversification. When two positions are combined, VaR for the combined position can be greater than the sum of the VaRs for the original positions. One consequence of this is that VaR can sometimes be reduced by splitting a portfolio into a number of components. Another undesirable property is that VaR does not say anything about what the size of the loss will be in those (hopefully rare) cases where the VaR level is exceeded.

A measure which is more complicated than VaR, but overcomes some of its weaknesses, is expected shortfall. To calculate expected shortfall a company first chooses a time horizon T and a confidence level X and calculates VaR in the usual way. The expected shortfall is set equal to the expected loss in time T conditional on the loss being greater than VaR.

One popular misconception is that VaR assumes that gains and losses are normally distributed. The most common method for calculating VaR, historical simulation, does not make this assumption. However, it does assume that what will happen between today and tomorrow is a random sample from what happened in the most recent N days (where N might be 250, 500 or 1000). As a result of the recent credit crisis regulators have introduced what is known as "stressed VaR." This assumes that what will happen between today and tomorrow is a random sample from what happened during a 250 day period in the past that would be particularly stressful for the bank's current portfolio.

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