These arguments make it difficult to specify strict regulatory rules for all seasons. They point to the need for a forward-looking, horizon scanning approach with scope for supervisory judgement and macroprudential discretion (BCBS (2017)). This does not, however, obviate the potential benefits from seeking, over time, to specify clearer mandates and regulatory reaction functions, especially on the macroprudential front. Incentives and Arbitrage  The empirical exercise in the previous section looked at how a set of regulatory standards, applied counterfactually, might have done in spotting stress among a set of banks. Plainly, any such counterfactual 27  All speeches are available online at www.bankofengland.co.uk/speeches  27  exercise is subject to significant caveats. The most important of these is that it cannot take account of how changes in the regulatory regime might themselves have reshaped risk-taking incentives at the time. This Lucas Critique plainly looms large in the field of financial regulation. Financial regulation, like any tax, is very likely to change the behaviour of the party subject to it. This is neither surprising nor, necessarily, undesirable. Indeed, sometimes it is the precise purpose of the regulation in the first place. For example, average risk weights on assets held in the trading book have increased by 45% across a sample of major UK banks between 2006 and 2013. Partly in response, trading books have shrunk by, on average, 24% across these banks and by 45% across the world’s G-SIBs. This was an intended, and probably desirable, behavioural response to a necessary recalibration of regulatory standards.
Aikman et al (2014) discuss where the classification of failure departs from Laeven and Valencia (2010). 23  All speeches are available online at www.bankofengland.co.uk/speeches  23  instrument if policymakers have a low tolerance for failure. That matters if, for example, the costs of higher capital requirements increase non-linearly (Greenwood et al (2017)). These points are also evident if we assess individually the performance of the RWCR and NSFR. Chart 18 and Table 3 below show that hit rates of 80 or 90% can only be achieved with high false alarm rates and stringent calibrations of these metrics. Overall, each metric individually does somewhat worse than the leverage ratio in balancing hit and false alarm rates. And similar results hold when the loan to deposit (LTD) ratio is considered instead of the NSFR in the wider sample (Chart 19).