Better bank liquidity measure should help predict a crash

Our banks seem better prepared than last time to withstand the assaults of market volatility.

All recessions are alike, but each is alike in its own way. The current slowdown in the housing market and the volatility of the stock market have the worrying class looking for a repeat performance of the Wall Street crash in 2008 that led the economy into a lasting funk.

One aspect of the worry involves the question of whether we learned anything from the last, painful recession, or could another sneak up on us, as surprising and unpredicted as the last time? And are our financial institutions better prepared than last time to withstand the assaults of market volatility?

The Federal Reserve was our economy’s last defense still standing after the Wall Street crash. It poured trillions of dollars into financial institutions to prevent further damage to a staggering economy. And throughout the long recession and recent recovery the “Fed” has continued its reshaping and strengthening of the nation’s banks.

The main thrust of the Fed’s effort has been aimed at the banks’ capital positions. The principle that a bank’s strength lies in its capitalization led to a number of regulatory moves that increased the capital requirements, especially for our country’s largest banks.

There was justification for this emphasis in the history of bank failures in modern times. The most often repeated pattern begins with falling profitability, which creates a drain on capital. Efforts to raise profitability cause banks to take on greater risk and this so often leads to ruination.

With the new capital standards achieved, the Fed is exploring a more elusive dimension of financial strength: liquidity. It includes a liquidity coverage requirement in its bank stress tests, for example, and there are also liquidity requirements and rules for banks. But the liquidity measurement systems seem inadequate, especially in terms of predicting problems.

Unlike capital, which is relatively easy to measure and report with familiar accounting rules, liquidity is more complex in its nature. During the last financial crunch, for example, we were reminded that entire liquidity markets could disappear overnight. A financial institution that was dependent on those markets could be transformed from a going concern to corporate carcass in the blink of an eye.

Liquidity is a measure of time. Basically, it is the amount of time that it takes to convert an asset to cash.

In October 2017, three economists — Jennie Bai, Arvind Krishnamurthy and Charles Henri Weymuller — published a research paper in the Journal of Finance that directly addressed the liquidity issue. Entitled, “Measuring Liquidity Mismatch in the Banking Sector” it offered a perspective on bank liquidity that promised to be useful to market analysts and bank regulators alike.

A bank’s assets are all market-dependent for their liquidity, as we would expect in a financial institution. Its principal earning assets are loans, which, in turn, are secured by assets – collateral — of varying levels of liquidity themselves. Home mortgages, for example, are usually secured by houses which, depending on the market temperature, can be sold in a matter of hours or take years to find a buyer. Some other financial assets — US Treasury Bills, by contrast, are as “near cash” as possible and usually can be converted to cash in a matter of minutes.

What the three economists did was to recreate a weighting system that evaluated each of the bank’s assets in terms of its actual market liquidity. They then compared that with the liquidity demands of each the bank’s liabilities. The result of these calculations was an index, a measure of the mismatch in liquidity between the bank’s assets and its liabilities.

The liquidity mismatch measurement approach is new and has not yet been fully explored, although the New York Federal Reserve did use it recently to examine the liquidity effects of some regulatory actions. Its greatest advantage over previous methods is that it will allow the Federal Reserve to incorporate its knowledge of financial markets into the calculations.

The liquidity mismatch idea isn’t limited to banks, of course. Household balance sheets are affected by many of the same forces. Financial advisers are very aware of this, and particularly watchful of potential problems that can arise from the liquidity demands of too much short-term debt such as credit card balances and asset rentals such as automobile leases.

The big question is whether a better measure of bank liquidity will improve our ability to foresee an impending financial crunch or crash. Will it be a better early warning indicator? Probably yes.

No regulations can totally prevent banks from stupid behavior and the last crash had plenty of it. Stupid bank tricks are bound to show up in a liquidity mismatch analysis, though, and provide us with the early warning of that we need to prevent another financial meltdown.

James McCusker is a Bothell economist, educator and consultant.

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