LCR and NSFR could produce $1 trillion shortfall in plans for balance-sheet ‘normalisation’
Disclosures show striking differences on pre-hedging, hold times and trade acceptance
Turmoil benefits total return futures, cross-asset arbitrage and dispersion
COMMENTARY: Banks still brushed by Basel rules
The impact of rules devised in Basel continues to be felt across the globe, in the delicate interplay between central banks and the commercial banking system, as well as in the ways banks are exploring to reduce the costs of the regulations.
As it turns off its liquidity tap over the next five years, the US Federal Reserve’s asset portfolio is projected to shrink by $1.9 trillion as a result of ‘balance sheet normalisation’. But that normalisation strategy is contingent on banks’ ability to operate with much lower central bank reserves. Those currently stand at $2.2 trillion.
If the US banking system’s demand for reserve balances drops to $100 billion, the Fed argues, assets in the system open market account (Soma) portfolio shrink from $4.2 trillion currently to $2.3 trillion in the third quarter of 2023. Another study by the New York Fed says if US bank demand for reserves falls to $613 billion, the Soma portfolio could normalise at $2.8 trillion by 2022.
But bankers disagree. These projections, they say, fail to account for the impact of regulations such as the liquidity coverage ratio, which inflate the demand for excess reserves in the banking system.
Five liquidity specialists have told Risk the long-term demand for excess reserves is likely to be in the $1 trillion to $1.5 trillion range, meaning the Fed’s portfolio is not going to shrink as much as projected.
Separately, banks have also renewed calls for changes to the new approval regime for market risk capital models, in an attempt to make one of its key tests easier to pass.
The Basel Committee on Banking Supervision’s Fundamental Review of the Trading Book (FRTB) requires bank trading desks to pass a so-called profit and loss attribution test in order to use the internal models approach. The alternative is the standardised approach, under which they say capital can increase dramatically.
Some are warning that without changes banks may abandon the use of models altogether, leaving them on the cruder, standardised approach to capital. Banks’ criticisms of the regime are not new, and the Basel Committee is understood to be working on a set of proposals that would overhaul the regime.
In Canada, meanwhile, the largest banks are creating their own data pool in response to FRTB, spurning offers of vendors to run a utility to deal with the issue created by risk factors based on markets where data is thin or patchy. When that happens, risks are in greater danger of falling into the non-modellable category – facing punitive add-ons to capital requirements.
The banks themselves will operate the data pool, avoiding fees for packaging the data and supplying it back to them; cost was allegedly the major sticking point that stopped banks signing up to at least one vendor’s solution. A source party to the initial discussions with vendors says: “We didn’t see, at the time, what the value-add of it was. If we can organise the Canadian banks to provide data, why not do it by ourselves, rather than integrating a third party which will basically become the ultimate owner of the banks’ own internal data and will charge fees?”
STAT OF THE WEEK
Looking at annualised volatility of the S&P 500 going back to 1872 and using a hidden Markov model to identify two regimes, BlackRock quant Edward Fishwick says markets were in a low-volatility regime about four-fifths of the time, with a mean level of volatility around 10%. For the remaining one-fifth of that period, volatility had a mean level of 21%. “If you’ve been in this game 20 years you’ll think the world is a really volatile place. If you’d been in it 120, you’d think the recent past was a bit weird,” Fishwick observes.
QUOTE OF THE WEEK
Despite having been around for years, a question remains: can CVA really be hedged? – Damiano Brigo, head of mathematical finance research group at Imperial College, London.