Get Ready, Here Comes the Fundamental Review of the Trading Book

This global regulation is going to cost a lot to implement. The other certainty: Banks’ capital requirements are going to increase.
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Nothing in life is certain except death and taxes … and financial regulation, one might add in the wake of the global financial crisis.

Thousands of pages of new rules governing markets have piled up since 2008. The Dodd-Frank Act arrived in 2010. The European Market Infrastructure Regulation followed in 2012. MiFID II, the European Union’s new Markets in Financial Instruments Directive, is scheduled to take effect next year. Accountants, meanwhile, have been busy preparing for the International Accounting Standards Board’s IFRS 9, which covers how various instruments are reported on financial statements.

Now comes the daddy of them all, the Fundamental Review of the Trading Book (FRTB).

This global regulation is the latest iteration of the Basel Committee on Banking Supervision rules, which specify the amount of capital banks have to hold against the market risk in their trading book. It’s called a review because the basic principles underlying the current rules remain. But it’s fundamental because every part of the calculation is changing.

This story appears in the April/May 2017 issue of Bloomberg Markets.

Cover artwork: Steve Caldwell

So is it a big deal? You better believe it. Consulting firm Oliver Wyman estimates that banks globally will spend a total of $5 billion getting ready for FRTB.

Not only will its implementation cost a lot, but the one certain thing about the process is that capital requirements will rise. This is going to be life-threatening for some trading desks, as heads of divisions assess whether it’s economical to be in certain businesses. To have systems in place and fully tested in time, decisions need to be made now. Regulators expect banks to be ready by the end of 2018.

The current set of rules, known as Basel 2.5, allows a different capital treatment of assets in the banking book than in the trading book. That’s enabled smart bankers to arbitrage the system by moving assets back and forth between the two.

There are two approaches for calculating capital requirements: the Standard Approach (SA) and the Internal Models Approach (IMA). In current practice, SA is so punitive that if a regulator failed to approve a bank’s internal model, the bank would be unable to operate—and so the sanction can’t be applied.

These issues are addressed under FRTB, but at a considerable cost in complexity. The new SA is carefully prescribed, using delta, gamma, and vega risk for seven risk types. For example, the list of maturity buckets required for your interest rate risk is exactly specified. If your risk system outputs a delta ladder using a different list of instruments, bad luck: You’ll need to transpose your risk onto the specified set. And there are classifications. For equity risk, advanced economies are grouped together—so your system has to know that Poland isn’t an advanced economy but Mexico is, for example. There are some offsets allowed within each risk type, but your delta risk-­capital charge is strictly added onto your gamma risk-capital charge, which is why using the standard approach is estimated to double the capital required to be held. Interestingly, even those banks that use IMA to calculate their capital requirement will need to report what the numbers would have been if they were applying SA, so comparisons of results across banks will be much easier.

Earlier this year, Bloomberg began incorporating FRTB analytics into its tools and enterprise products. So, for example, the MARS Market Risk enterprise system includes a complete SA solution for FRTB at no additional cost. For more on this, go to {FRTB <GO>}.
 
 
Larger banks will be looking to implement IMA. This approach is based on so-called expected shortfall instead of Value-at-Risk. Expected shortfall looks at all the states beyond the confidence limit to give a sense of how bad is bad. But the expected shortfall has to be computed in three different scenarios across multiple liquidity horizons and risk factor groupings by risk class, resulting in perhaps 15 or more times as many calculations as under the old rules. This is challenging in terms of “big data” questions and calculation time—can your front-office model run enough times overnight to calculate all the scenarios required? The IMA module for Bloomberg’s MARS platform combines all the required analytics with the scalability needed to handle the increased volume of FRTB simulations.

Go to {BRM <GO>} for the Bloomberg Risk Management platform. BRM calculates both total expected shortfall (moving all variables together) and partial expected shortfall (moving variables for one risk class at a time), as required under the Fundamental Review of the Trading Book.

Using the front-office model instead of an approximate risk department model is going to become much more common. The reason: The results have to pass both profit-and-loss attribution tests (the theoretical P&L implied by your risk system has to match the actual P&L you report) and backtesting. Fail either, and you’re automatically back on the SA, without any appeal or adjudication. IMA is now done on a desk-level basis, so the first order of business for senior managers will be to group their trades into a desk structure that optimizes the capital charge across the firm. That will lead to some interesting discussions among heads of desks.

Two other wrinkles are coming. First, some pricing models for exotic trades use inputs that aren’t directly observable in the market, such as correlations. These so-called non-modellable risk factors incur a punishing extra charge. And the definition of non-modellable? It’s anything that doesn’t trade 24 times in a year, with not more than a month between each trade. So suddenly it becomes very important to collect a record of every trade of long-dated, deep-out-of-the-money equity skew, for example.

Second, there’s an additional extra charge for times of stress. Banks must go back to at least 2007 to find the most stressful 12-month period and run their model through that to calculate the extra charge.

How can you address these problems? First, you can draw on Bloomberg’s historical data in your calculations. In addition, Bloomberg has created an FRTB data service in which participating banks submit the trades they’ve seen. Bloomberg then anonymizes and aggregates the data and makes the complete collection available to each member, so everyone benefits. The first trial of the service has just been successfully completed, and banks can sign up now, before the product launch next year.

FRTB is coming. Now’s the time to get ready.
 
Sinclair is a fixed-income market specialist at Bloomberg in London.
 

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