policy options

Even in a world with rational expectations, it has been well established theoretically that if the central bank possesses information superior to that available to the public, there is room for effective and socially beneficial countercyclical monetary policy. This paper tests whether confidential information from bank supervisors could be one source of any such informational advantage. In particular, we examine whether information gained from bank supervision activities could substantially improve the forecasts of macroeconomic variables important for guiding monetary policy. We find that confidential supervisory information on bank ratings significantly improves private forecasts of inflation and unemployment rates, thus providing an informational advantage to the Federal Reserve.

this article is to provide a comprehensive review and evaluation of bank capital reform proposals that incorporate a mandatory sub-debt component, and to present a new proposal that we believe incorporates the most desirable characteristics of sub-debt. As general background, in the basic model of financial intermediation, bankers purchase 2

Bank supervisors need timely and reliable information about the financial condition and risk profile of banks in order to conduct effective supervision. Although such information can be obtained in part from regulatory reports and public disclosures, a key source is the on-site bank examination. Bank examinations enable supervisors to confirm the accuracy of information in regulatory reports. More important, perhaps, the examinations allow supervisors to gather confidential information about banks ’ financial conditions and to assess qualitative attributes, such as internal controls and risk management procedures, that affect bank risk profiles. Such confidential information may be valuable to supervisors, yet it is costly to obtain: bank examinations absorb considerable resources on the part of supervisors as

Critical feedback from a number of sources greatly improved this work. Specifically, we would like to thank the following bank supervisors—Carl Anderson, John Block, Joan Cronin, and Kim Nelson—as well as the following economists—Rosalind Bennett, Mark Carey, Bill Emmons, Doug Evanoff,

The cornerstone of bank supervision is a regular schedule of thorough, on-site examinations. Under rules set forth in the Federal Deposit Insurance Corporation Improvement Act of 1991 (FDICIA), most U.S. banks must submit to a full-scope federal or state examination every 12 months; small, well-capitalized banks must be examined every 18 months. These examinations focus on six components of bank safety and soundness: capital protection (C), asset quality (A), management competence (M), earnings strength (E), liquidity risk exposure (L), and market risk sensitivity (S). At the close of each exam, examiners award a grade of one (best) through five (worst) to each component. Supervisors then draw on these six component ratings to assign a composite CAMELS rating, which is also expressed on a scale of one through five. (See the insert for a detailed description of the composite ratings.) In general, banks with composite ratings of one or two are considered safe and sound, whereas banks with ratings of three, four, or five are considered unsatisfactory. As of March 31, 2000, nearly 94 percent of U.S. banks posted composite CAMELS ratings of one or two. Bank supervisors support on-site examinations with off-site surveillance. Off-site surveillance uses quarterly financial data and anecdotal evidence to schedule and plan on-site exams. Although on-site examination is the most effective tool for spotting safety-and-soundness problems, it is costly and R. Alton Gilbert is a vice president and banking advisor, Andrew P. Meyer is an economist, and Mark D. Vaughan is a supervisory policy officer and economist at the Federal Reserve Bank of St. Louis. The

Abstract: Bank supervisors in the United States conduct comprehensive on-site inspections of bank holding companies (BHCs) and assign them a supervisory rating meant to summarize their overall condition. We develop an empirical forecasting model of these ratings that combines supervisory and securities market data. We find that securities market variables, such as BHC stock returns and bond yield spreads, improve the model’s in-sample fit. We also find that debt market variables provide more information on supervisory ratings for BHCs closer to default, while equity market variables provide more information for those further from default. In out-ofsample forecasting, we find that the accuracy of the model with both equity and debt variables is little different from the accuracy of a model based on supervisory information alone. However, the model with securities market data identifies additional ratings downgrades, which supervisors would probably value enough to warrant the use of this extended model for off-site monitoring purposes. Acknowledgments: The views expressed here are those of the authors and not necessarily those of the Federal Reserve Bank of San Francisco or the Federal Reserve System. We thank Rob Bliss for generously sharing his bank holding company debt database with us. We thank Fred Furlong, Reint Gropp, and seminar participants at the Bank

University School of Management Finance and Accounting Seminar Series for comments on an earlier draft. The This paper assesses the timing and magnitude of equity market valuations of bank holding companies (BHCs) in relation to changes in their risk assessments, as proxied by changes in supervisory ratings for these organizations. In particular, equity market indicators such as market-to-book value, abnormal returns, return volatility, market valuation, price covariance, and trading volume are used to determine if they can provide timely market signals as well as add incremental value to models predicting changes in supervisor-assigned BOPEC ratings of bank holding company risk. To analyze this issue, we took 3,974 bank holding company inspections from a sample of bank holding companies whose stock was publicly traded on major exchanges over the 1988–2000 period. We specify two statistical models: (1) an ordered logistic model, which is used to test the ability of lagged financial market variables, lagged financial accounting data, and past supervisory assessments to predict BOPEC rating changes; and (2) an OLS model, which is used to test the relationship of lagged BOPEC rating changes and lagged financial accounting ratios to predict financial market variables. These

The views expressed here are those of the authors and do not necessarily reflect those of the FDIC or its staff. The authors would like to thank Audrey Clement for extensive assistance; and Gerald Hanweck, Andrew Davenport, anonymous referees, and the participants in the 2004 Washington Area Finance Association meetings and the 2004 Western Economic Association The paper examines the informational content of market data when these data are incorporated into traditional models that predict bank failures. To assess whether financial markets can provide timely information about firm distress, we first examine the pre-failure behavior of market variables over long periods before failure. The univariate results document distinct patterns of declining prices, negative returns, declining dividends, and rising return volatility several years before failure. Several other market-related measures, however, such as trading volume and share turnover, show no clear trend. Next we test for the contribution of market variables in relation to Call Report variables in the prediction of bank failures over the 1989–1995 period. The findings show that selected market variables like equity prices, returns, and volatility of returns add important information to the identification of failed institutions beyond the information contained in quarterly accounting data. In-sample and out-of-sample tests show that the use of market data does improve the sample forecast of bank failure.

This article explores the notion that publicly available stock price, return, and other market-related variables can provide timely information about bank and thrift financial condition; the article also determines whether such information can be used to improve the predictive accuracy of traditional off-site monitoring models for the purpose of anticipating changes in the CAMEL ratings assigned by regulators. The SCOR System of Off-Site Monitoring: Its Objectives, Functioning, and Performance (page 17)