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It might mean that bank supervisors would not accept a bank’s having very high volatility of its market value, even though its capital ratios were sufficiently high to keep its probability of insolvency within the acceptable range. One reason for concern with volatility of bank equity and asset value may be that severity of loss may not also be tightly tied to probability of failure. Another may be that estimates of the volatility of assets may be a vital input in determining the amount of capital required above that implied by the Basel risk-weighted-assets formula.
Here we present measures of the volatilities of individual banks that are implied
by the prices of options on the banks’ shares. These data come from markets whose
prices, and thus measures of IV, can be observed virtually continually at low cost.
These prices come from markets that are widely regarded as being efficient and deep.
IV’s contain both important common movements across banks and important
bank-specific movements in banks’ risks. We present evidence that the extent to
which the riskiness of a bank’s assets translate into IV of its share price depends positively
on the leverage (or equivalently, the inverse of the capital ratio) of a bank. For
two of the three banks we examined in detail, we show that the IV’s have lower
RMSE’s in forecasting future volatility of bank share prices than HV’s do.
We also show that banks’ IV’s share important common movements with their
own share prices and with yield spreads on their subordinated debt. However, IV’s
also importantly diverge from the paths followed by share prices and yield spreads.
Thus, IV’s are likely to add information about bank risk that is timely, relatively
cheap to acquire, objective, and useful.
Adding a measure of IV to the information that supervisors and others use to evaluate
the volatility and failure probability of a bank can alter the point estimates and
the confidence in those point estimates. We show that measures of IV are not perfectly,
and sometimes not highly, correlated with HV, not to mention with signals
from other models and the debt markets. At the same time, measures of IV tend to
be significantly correlated with what it purports to forecast – actual, future volatility.
These correlations suggest that using measures of IV in conjunction with other measures,
such as measures of HV, EDFs, and yield spreads on bank debts, may well improve
the accuracy of forecasts of bank outcomes.We discuss generally and show in a#p#分頁(yè)標(biāo)題#e#
specific case how various measures might be combined to improve signals about the
future of banks. This is not to suggest that this is the only or the best way to combine
such signals. It will take further work to determine whether, for example, a more categorical
approach would better forecast bank outcomes. An alternative to the regression
approach that we show is to evaluate changes in risk by tallying how many
separate signals from a bank point toward risk changing in the same direction.

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