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OP; ratio; market; asset; foreign currency; asset quality; market liquidity indicator; average equity; on-balance-sheet assets; Financial soundness indicators; Real estate prices; Loans; Stress testing; Capital adequacy requirements; Global; Europe; Africa; Middle East; Western Hemisphere
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Abstract

This explanation of indicators included in the core set and the encouraged set of FSIs provided to clarify this paper’s discussion. The terms may not correspond precisely to official definitions or standards. The Compilation Guide on Financial Soundness Indicators will clarify the definitions of the indicators included in Table A1.1 below.

References

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Appendix I Explanation of FSI Terms

This explanation of indicators included in the core set and the encouraged set of FSIs provided to clarify this paper’s discussion. The terms may not correspond precisely to official definitions or standards. The Compilation Guide on Financial Soundness Indicators will clarify the definitions of the indicators included in Table A1.1 below.

Table A1.1.

Explanation of FSI Terms

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Data on credit, which is a more comprehensive concept than loans* can be used as an alternative to loans. Credit (assets for which the counter-party incurs debt liabilities) includes loans, securities other than shares, and miscellaneous receivables.

Appendix II Aggregation Issues

Simple aggregation of balance sheets and income statements of individual institutions can disguise important structural information, and it is often necessary to supplement the aggregate data with information on dispersion. For example, the capital to asset ratio of a system is calculated by dividing the total capital by total assets, which is essentially the average (or mean) capital to asset ratio of the system. If capital asset ratios were symmetrically distributed, this statistic would also convey information about the middle capital asset ratio (the median) as well as the most frequently observed capital asset ratio (the mode). However, typically the distribution is not symmetric; hence, focusing on the mean values only may be misleading as the mean can be affected by value of outliers—for example, one very strongly capitalized bank could be more than offsetting many other undercapitalized banks.

Descriptive statistics on data dispersion provide ways to supplement mean values with additional information. Data skewness can be particularly useful, as it provides a measure of the size and direction of asymmetry in the distribution of the observations. Positive skewness indicates that aggregation biases the results upwards (a substantial number of institutions are actually below the average), and the opposite is true for negative skewness. Skewness is zero when the distribution is symmetrical—that is, mean, median, and mode are equal. To get a sense of the proportional effect of the outliers, or the thickness of the tails, the kurtosis can also be calculated. Ways to calculate the direction and degree of skewness and the degree of kurtosis are discussed below.

Descriptive Statistics and Data Dispersion

Summary measures for a data set are often referred to as descriptive statistics. Descriptive statistics fall into four main categories: (1) measures of position, (2) measures of variability, (3) measures of skewness, and (4) measures of kurtosis. They can be useful for beginning data analysis, for comparing multiple data sets, and for reporting final results of a survey.

Measures of position (or central tendency) describe where the data are concentrated:

  • Mean (first moment of the distribution, or x− is the mathematical average of the data and is a common measure of central tendency.

  • Median (Med) is the middle observation in a data set. The median is often used when a data set is not symmetrical, or when there are outlying observations.

  • Mode is the value around which the greatest number of observations are concentrated, or the most common observation.

Measures of variability describe the dispersion (or spread) of the data set:

  • Range is the difference between the largest and the smallest observations in the data set. The range has limitations because it depends on only two numbers in the data set.

  • Variance (second moment of the distribution, or σ2) measures the dispersion of the distribution around the mean, taking into account all data points.

  • Standard Deviation (or σ) is the positive square root of the variance, and is the most common measure of variability. Standard deviation indicates how close to the mean the observations are.

Measures of skewness indicate whether the data are symmetrically distributed:

  • Skewness (third moment of the distribution, or Ps) measures the degree of asymmetry of the data set. Positive skewness indicates a longer right-hand side (tail) of the distribution; negative skewness a longer tail on the left. Distributions that are symmetric have identical tails and thus no skewness. One easy way of determining skewness is to compare the values of mean and the median relative to the standard deviation:

γ=x¯−Medσx

A more precise method to calculate skewness is the Pearson coefficient:

μ3σ3=Σi=1n(x−x¯)3⋅niNσx3

Measures of kurtosis indicate whether the data are more or less concentrated toward the center:

  • Kurtosis (fourth moment of the distribution, or μ4) measures the degree of flatness of the distribution near its center, or equivalently the degree of thickness of the tails. It is large if the distribution has sizeable tails that extend much further from the mean than ± σ kurtosis is zero if the distribution is normal. A normalized measure is:

k=μ4σ4=Σi=1n(x−x¯)4⋅niNσx4−3

Appendix III Additional FSIs Identified by Respondents

The User Questionnaire asked respondents to indicate FSIs not covered in the survey that they consider useful, or FSIs they use that differ from those in the survey. Respondents identified a relatively small number of additional FSIs. Conversely, few commented that the list of FSIs was too long.

As already noted in the body of the paper, additional asset price information (real estate, equities, and bank equities) was requested most often, and a number of respondents identified information on the distribution of observations as being useful.

Some of the other additional FSIs identified are listed below.

  • Aggregate growth indicators for various types of lending;

  • Distribution of loans by size of borrower;

  • Indicators of the composition of liabilities (subordinated debt, guarantees, government credits, etc.);

  • Turnover and spreads in securities repo and swaps markets;

  • Number of banks and total assets by CAMELS ranking;

  • Ratings of banks and their distribution;

  • More quickly available “flash indicators,” such as bank and bond yields, that provide current assessments of markets;

  • Developments in payments systems, including collateral held and liquidity.

Other observations by respondents

Respondents made a number of other observations regarding FSIs and their compilation and dissemination.

  • One concern expressed was that aggregation of information on individual financial institutions could result in the offsetting of positions of individual units that could obscure the meaning of some FSIs.

  • Several respondents said that regular compilation of a large range of FSIs might not justify the resource costs. One respondent said that financial institutions were already subject to substantial data reporting requirements and would not welcome new statistical demands. It was suggested that ad hoc compilation of FSIs could be carried out when needed.

  • Several respondents said that many organizations were working on financial stability issues or closely related initiatives. Close cooperation among parties working in the field was considered desirable,

  • One respondent suggested that the selection of FSIs might wait until the completion of the Basel Committee’s work on the new capital adequacy framework.

  • Several comments were made regarding the proper treatment of money market mutual funds and whether they should be included within the depository corporations sector, as done in the survey. It was noted that the risks faced by money market mutual funds could significantly differ from those faced by banking institutions and therefore mutual funds might be excluded from the analysis or might be separately analyzed. Alternatively, it was suggested that all mutual funds should have been covered in the survey because the greatest risks are likely to be faced by non-money market funds that tended to escape supervision by bank supervisors.

  • Several countries commented that flexibility should be sought in presentation of macroprudential information. One G-7 country commented that, “It is not possible to have uniform rules on the presentation of macroprudential indicators. At any rate, caution is advised in view of the heterogeneity that may exist in terms of national concepts and calculation methods.”

Appendix IV Tables of Survey Results

Table A4.1.

FSIs for which Components Are Extensively Compiled

(Very useful FSI—Group I—are in italics)

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Table A4.2.

SDDS Subscribers: Compilation and Dissemination of FSIs and Components

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The denominator used in columns three and five is 50, the total number of SDDS countries as of December 2001.

Table A4.3.

Usefulness of FSIs by Type of User and Type of Economy

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Table A4.3. (concluded)
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Table A4.4.

Compilation and Dissemination of FSIs by Type of Economy

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Table A4.4. (continued)
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Table A4.4. (concluded)
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Appendix V Survey on the Use, Compilation, and Dissemination of Macroprudential Indicators

At the request of its Executive Board, the IMF is conducting a survey of needs and practices related to macroprudential indicators (MPIs)—defined broadly as indicators of the health and stability of financial institutions and of their corporate and household counterparties. The purpose of the survey is to gather information on the use of macroprudential data and on country practices in compiling and disseminating the data. Survey results will be used to identify a set of statistical measures that can be regularly monitored by national authorities in their financial sector assessment work, by the IMF in its surveillance activities, and ultimately by the private sector.

The survey covers the use, compilation, and dissemination of aggregate data on the financial system, and does not cover information on individual institutions. The survey is intended to solicit the views of respondents and is not intended to gather the actual numerical data on MPIs. All responses are confidential. No information will be released in a form that allows public identification of individual country responses.

Work by the IMF on MPIs is part of ongoing efforts in the international community to strengthen the architecture of the global financial system. Among the institutions to initiate action in this area, the IMF has been called upon to assess financial system soundness as part of its surveillance work—a process now underway as part of the joint World Bank-IMF Financial Sector Assessment Program (FSAP), introduced in May 1999. The ability to monitor financial soundness presupposes the availability of valid indicators of the health and stability of financial systems—or MPIs. MPIs allow for assessments based on objective measures of financial soundness. If comparable across countries—through adherence to internationally agreed prudential, accounting, and statistical standards—they facilitate monitoring at the global level and permit comparisons of national conditions with global benchmarks. If made publicly available, they enhance access to key financial information and can contribute to strengthening of market discipline.

The focus of this survey is on indicators of the current health of the financial system, which are primarily derived by aggregating data on the soundness of individual financial institutions. For practical purposes, the survey limits itself to the depository corporations (banking) sector and to their corporate and household counterparties. This focus is appropriate for a first-time survey in this area, but it is recognized that further research is needed on the effects of nondepository financial institutions and securities markets on financial stability.

MPIs are only one of the tools of macroprudential analysis. The assessment of financial system soundness involves coupling the analysis of MPIs with macroeconomic data on overall economic conditions, information on other financial institutions and markets, and qualitative information about the institutional, policy, and regulatory environment. A variety of techniques can be used in macroprudential analysis, including stress tests, sensitivity analysis, and other methodologies.

Instructions for Completing the Survey

The survey is being sent to the central banks of all IMF member countries. The survey has two major parts, which are addressed to different organizations in your country. We would like to request the assistance of your institution in identifying the appropriate respondents for each part of the survey, forwarding the questionnaires, and collecting the responses (see below). We would appreciate the return of the completed survey to us by July 28, 2000.

Part I: User Questionnaire. This questionnaire is addressed to (1) financial sector supervisors, (2) analysis and policy officials within the central bank or other government authorities involved in the analysis of financial system soundness, and (3) financial market participants and analysts in academia or the private sector. Six copies of the user questionnaire are provided, for distribution by the central bank. The central bank may find it useful to select respondents based on their ability to contribute to a balanced depiction of the needs for MPIs in the country. In order to protect the confidentiality of private sector and academic respondents, we would like to request that the central bank prepare an overview of their responses, which should be returned to the IMF.

  • Part I (a): User Questionnaire: Covers usefulness of specific MPIs and requirements for frequency of compilation.

  • Part I (b): Supplementary Issues: Covers additional questions related to the needs for, and analysis of, MPIs.

Part II: Compilation and Dissemination Questionnaire. This questionnaire is intended for staff within the monetary or supervisory authorities, or other government institutions, responsible for the compilation of MPIs and components of MPIs, and for their dissemination to the public, where appropriate. The selection of the respondents will depend upon the institutional setup in each country.

  • Part II (a): Compilation and Dissemination Questionnaire: Covers practices related to the compilation and dissemination of MPIs or components of MPIs.

  • Part II (b): Supplementary Issues: Covers technical questions on factors affecting the compilation and dissemination of MPIs or components of MPIs.

  • Part II (c): Valuation Issues: Covers valuation practices affecting MPIs or components of MPIs.

Coverage: The survey covers the depository corporations subsector, which corresponds roughly to the banking sector. It includes all major divisions of depository corporations, including commercial banks, branches and subsidiaries of foreign banks operating in your country, money market funds that issue deposit-like shares, foreign currency and foreign trade banks, international banking facilities, investment banks, mortgage banking institutions, credit unions, specialized banks, and others as appropriate. Government-owned or -controlled depository corporations are included. For the purpose of this survey, the central bank is excluded. Mutual funds whose liabilities to investors are close substitutes for bank deposits should be included in the survey, but other mutual funds should be excluded.

MPIs and MPI components: The questionnaires list a number of aggregate indicators that, based on surveillance and empirical work at the IMF and else- where, are considered useful for assessing the health and stability of financial systems. The survey also gathers information on components of MPIs to ascertain whether the underlying information exists to compile MPIs that are not now being compiled. The exact definitions of each indicator or its components may vary from country to country. Respondents are kindly asked to indicate cases where the MPIs used or available are similar to, but not identical to, those presented in the survey.

Special issues pages: The User Questionnaire and the Compilation and Dissemination Questionnaire each include a page devoted to a series of questions on special issues related to MPIs.

Additional comments: Respondents may wish to provide supplemental information important for the analysis of financial stability conditions in their country, important indicators not listed in the survey, special conditions that affect compilation and dissemination of MPIs, and alternatives to the definitions and descriptions of MPIs provided in the survey. “Comments” cells for this purpose corresponding to each MPI have been created on the User Questionnaire, Part I (a), and spaces for general comments are provided at the ends of the User Questionnaire Part I (a) and the Compilation and Dissemination Questionnaire Part II (a). Other comments may be entered elsewhere in the spreadsheets by right-clicking your mouse button to select “Insert Comment.”

Optional reports on other financial institutions and markets: Central banks may also choose to provide separate reports for other financial institutions or markets that are important for the analysis of overall financial stability conditions in their countries. When doing so, please describe the types of institutions or markets covered and why they are important for macroprudential analysis.

Returning the questionnaire: Responses should be sent to the IMF by July 28, 2000:

— by Internet to: f2survey@IMF.org

— or by mail (diskette or paper copy) to:

  • MPI Survey

  • Financial Institutions Division II

  • Statistics Department

  • International Monetary Fund

  • 700 19th Street, N.W.

  • Washington, D.C. 20431, USA

Contacts regarding the survey: IMF staff may contact you regarding the survey to better understand your needs and compilation practices related to MPIs, or to clarify your responses.

MPI Survey: Explanation of Terms

Disclaimer: This glossary is provided for the convenience of the recipients of this survey. The explanations of the terms may not correspond to official definitions or standards.

Bid-Ask Spread. Difference between the prices at which a market participant is willing to buy and sell a security, such as a Treasury security.

Basel Capital. Capital as defined in the 1988 Capital Accord of the Basel Committee on Banking Supervision and subsequent revisions. The Accord defines three capital elements. Tier 1 capital consists of permanent shareholders’ equity and disclosed reserves; tier 2 capital consists of undisclosed reserves, revaluation reserves, general provisions and loan-loss reserves, hybrid debt-equity capital instruments, and subordinated long-term debt (over five years); tier 3 capital consists of subordinated short-term debt (over two years).

Basel Capital Adequacy Ratio. The ratio of capital, as defined above, divided by risk-weighted assets. Risk-weighted assets equals the sum of each category of asset (and on-balance-sheet equivalents for off-balance-sheet positions) multiplied by a weight representing the credit risk associated with each category.

Basel Capital Deductions. Under the Basel Capital Accord, supervisors may require depository corporations to deduct certain items—such as investments in non-consolidated financial subsidiaries—from capital in order to calculate capital adequacy ratios.

Capital. Sum of equity capital and reserves. It is the amount by which assets exceed liabilities.

Consolidation. Refers to the elimination of stocks and flows between institutional units when they are grouped. In particular, a headquarters office and its branch offices and subsidiaries would report stock and flow data consolidated in a single statement. Global consolidation refers to the elimination of stocks and flows occurring across all offices regardless of their country of location. National consolidation refers to the elimination of stocks and flows occurring across all offices that are residents of a specific country.

Credit. Comprises assets for which the counter-party incurs debt liabilities. Includes loans, securities other than shares, and miscellaneous receivables. Equity instruments, financial derivatives, and lines of credit are excluded.

Debt Service. Repayments of principal and interest on mortgages or other outstanding debt.

Depository Corporation. Financial institutions that engage in banking-type activities, whether or not they are called banks or are subject to supervision by a regulatory/supervisory office. The standard statistical definition includes the central bank and other depository corporations, described below, but for the purposes of this survey, the central bank is excluded.

Duration. Weighted average term-to-maturity of an asset’s cash flow, the weights being the present value of each future cash flow as a percentage of the asset’s full price.

Equity Capital. Issued and fully paid ordinary shares/common stock and noncumulative perpetual preferred stock (but excluding cumulative preferred stock).

Financial Derivative (or derivative instrument). Contract whose value is based on the performance of an underlying financial asset, index, or other investment.

Global Consolidation. An accounting statement including all parts of an enterprise regardless of their locations worldwide (see Consolidation).

Gross Asset (or Liability) Position in Derivatives. The on-balance-sheet value of derivatives in an asset (or liability) position, plus the fair value of off-balance-sheet derivatives in an asset (or liability) position.

Interest Income, Net. Difference between the interest income produced by a financial institution’s earning assets (loans and investments) and its interest expenses.

Loans. Financial assets (1) that are created when a creditor lends funds directly to a debtor; (2) that are evidenced by nonnegotiable documents; or (3) for which no security is issued as evidence of the transaction.

Mortgage. Loans under which the borrower gives the lender a lien on the property (usually real estate) as collateral for repayment of the loan.

National Consolidation. An accounting statement encompassing all parts of an enterprise within a country, but excluding branches and subsidiaries outside the country (see Consolidation).

Net Position. Refers to gross holdings, less gross liabilities, plus net positions under derivatives or other financial commitments in currencies, other financial instruments, or commodities. For example, a net foreign currency position equals gross foreign currency-denominated assets, less gross foreign currency-denominated liabilities, plus the net position under foreign currency financial derivatives and other financial commitments.

Nominal Value of Financial Derivatives. The stated contract value of the underlying item delivered under a financial derivative. For example, an option that has a nominal value of 100,000 francs will deliver 100,000 francs when exercised.

Nonperforming Loan (NPL). A loan is said to be nonperforming when the principal and/or interest payments on it according to the original terms of the borrower’s loan agreement are past due (e.g., by 90 days or more).

Operating Costs. The sum of interest and noninterest (fees and commissions, trading losses, and salary and other current costs) expenses.

Other Depository Corporations. Banks (other than the central bank) and similar institutions that carry out banking functions with the public. A full definition is provided in the System of National Accounts 1993. The definition corresponds with monetary financial institutions as defined in the European System of Account 1995. It includes a variety of institutions regardless of whether they are called banks or are subject to banking supervision, including commercial banks, branches, and subsidiaries of foreign banks operating in the country, money market funds that issue deposit-like shares, foreign currency and foreign trade banks, international banking facilities, investment banks, Islamic banks, mortgage banking institutions, credit unions, specialized banks, and others as appropriate. Government-owned or -controlled depository corporations are included. Mutual funds whose liabilities to investors are close substitutes for bank deposits are included, but other mutual funds are excluded.

Own Funds. Equity capital and reserves.

Profits. Sum remaining after all expenses have been met or deducted from income. Both pretax and post-tax concepts are used.

Reference Rate. A specific lending or borrowing rate considered representative of overall rates that is used as a benchmark for evaluating conditions in interest rate markets.

Related Entities. Affiliated enterprises, owners and management of an enterprise, and individuals related to owners and managers.

Repricing Period for Interest Rates. The average period (usually expressed in months) until existing financial instruments are redeemed or until the interest rates on financial instruments are reset or reindexed.

Turnover. Volume of securities traded during a period (e.g., daily) as a percentage of total securities listed on an exchange.

Table A5.1.

MPI Survey – Part 1 (a): User Questionnaire

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Table A5.2.

MPI Survey—Part I (b): Supplementary Issues

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Table A5.3.

MPI Survey—Part II (a): Compilation and Dissemination Questionnaire

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Table A5.3. (continued)
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Table A5.3. (continued)
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Table A5.3. (continued)
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Table A5.4.

MPI Survey—Part II (b): Supplementary issues

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Table A5.5.

MPI Survey—Part II (c): Valuation Issues

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1

The FSAP was launched jointly by the IMF and the World Bank in May 1999, The program is designed to identify financial system strengths and vulnerabilities and to help to develop appropriate polity responses. Financial System Stability Assessments (FSSAs) are prepared by IMF staff in the context of Article IV consultations, by drawing on the FSAP findings, for discussion in the IMF Executive Board, In the World Bank, the FSAP reports provide the basis for producing Financial Sector Assessments and formulating financial sector development strategies. Sec IMF (2001a, b) and Hilbers (2001).

3

See IMF (2000c, 2001b).

4

The survey explicitly listed around 60 indicators, identified in earlier work.

6

In some countries—for instance, Finland, Hungary, Iceland, Norway, Sweden, and the United Kingdom—central banks publish special reports dealing with financial stability issues.

7

Macroprudemial analysis focuses on the health and stability of financial systems, whereas microprudential analysis deals with the condition of individual financial institutions.

8

Macrocconomic indicators are not included in this definition, given their different source and character. They are, of course, part of the broader macroprudential analysis (see Figure 2.1), however, both as leading indicators of financial sector problems in their own right and as inputs into stress testing. See also Evans, Leone, Gill, and Hilbers (2000).

10

For the purpose of estimation of a robust early warning system, a variable must be reasonably comparable over time and across countries. See Berg, Borensztein, Milesi-Ferretti, and Patillo (1999).

11

Capital adequacy, asset quality, management soundness, earnings, liquidity, sensitivity to market risk.

12

See Carson (2001) for a discussion of the factors affecting data quality.

13

The linkages between the development of a sound banking system and well-functioning banking regulation and supervision are discussed in Sundararajan (1999). See also Sundararajan, Marston, and Basu (2001).

14

For a description of a “net risk” approach to risk assessment in the context of dynamic banking supervisory practices, see Office of the Superintendent of Financial Institutions (1999).

15

The importance of a healthy balance of quantitative and qualitative information in order to provide a meaningful picture of the extent and nature of financial risks has been recently highlighted by the Multidisciplinary Working Group on Enhanced Disclosure of the Financial Stability Forum (2001).

16

It should be noted, however, that regulatory factors could influence the size and movement of FSIs. notably through the establishment of minimum regulatory ratios.

17

The incentive audit approach, outlined by Chat and Johnston (2000), looks at three factors that affect the risk-taking and monitoring behavior of participants (investors, borrowers, and intermediaries) at the core of the financial system: (1) market structure and the availability of financial instruments that affect market discipline; (2) government safety nets, including implicit and explicit exchange rate and deposit/investor guarantees; and (3) the legal and regulatory framework, including high quality enforcement.

18

See, for example. Ball (2001).

19

While FSAP reports provide detailed assessments of strengths and vulnerabilities, observance of standards, institutional structures, and overall stability and developmental needs, the focus of FSSAs is on financial system stability issues of significance for macroeconomic performance and policies. For details, see IMF (2001b). Summary assessments of financial sector standards and codes from the FSAP process are included in the FSSA and are also issued as Reports on Observance of Standards and Codes (ROSCs). See IMF (2001c).

20

Systemic liquidity provision and the functioning of interbank markets can also affect the ability of the system to absorb shocks.

21

For a recent discussion of procyclicality in the financial system, see also Borio, Furfine, and Lowe (2001).

23

Compared with exchange-traded derivatives markets, OTC derivatives markets—in which transactions are not cleared through a centralized clearinghouse—have the following features: management of credit risk is decentralized at the level of individual institutions; there are no formal centralized limits on individual positions, leverage, or margining; there are no formal rules for risk and burden sharing; and there are no formal rules or mechanisms for ensuring market stability and integrity. On OTC derivatives markets, see also IMF (2000b), Chapter IV.

24

The Basel Committee’s 1988 risk measurement framework assigns all bank assets to one of four risk-weighting categories, ranging from zero to 100 percent, depending on the credit risk of the borrower. The Basel Capital Accord requires internationally active banks in Bank for international Settlements (BIS) member countries to maintain a minimum ratio of capital to risk-adjusted assets of 8 percent.

25

Tier 1 capital consists of permanent shareholders’ equity and disclosed reserves; tier 2 capital consists or undisclosed reserves, revaluation reserves, general provisions and loan-loss reserves, hybrid debt-equity capital instruments, and subordinated long-term debt (over five years); tier 3 capital consists of subordinated debt of shorter maturity (two to five years). See Basel Committee (I98K, 1998).

27

The Basel Capital Accord allows banks to include general provisions in tier 2 capital. up to 1.25 percent of (risk) assets.

28

Although accounting and prudential standards usually require the deduction of provisions from loans, international statistical standards recommend recording loans gross of provisions until the loan is written off.

29

Credit (assets for which the counter-party incurs debt liabilities) is a more comprehensive concept than loans, and includes loans, securities other than shares (e.g., bonds), and miscellaneous receivables.

30

Collateral could he taken into account in establishing provisions and a conservative value of the collateral could he deducted from the loan amount.

31

The accounting treatment of provisions must be considered when looking at NPL ratios. As indicated above, in most G-10 countries, local accounting and prudential standards require banks to deduct specific provisions from loans, which adjusts the value of loans in response to changes in quality. In these cases, NPLs should be measured as a percentage of gross, rather than net, loans.

32

See Baldwin and Kourelis (forthcoming).

33

Exposure refers to one or more loans to the same individual or economic group. There is no standard definition of “large.” In some countries, it refers to exposures exceeding 10 percent of regulatory capital.

34

The delta-normal I method uses the linear derivative to approximate the change in portfolio value and the normal distribution as the underlying statistical model of asset returns.

36

Schinasi, Craig, Drees, and Kramer (2000) report that in 1998 contracts between the major players accounted for roughly one-half of notional principal in interest rate derivatives and one-third in foreign exchange derivatives.

37

The ratios can he calculated with various income measures—for example, before or alter provisions and before or after tax charges and I net) extraordinary items.

38

Indicators of the maturity structure should distinguish between domestic and foreign liabilities and indicate the currency denomination of the liabilities.

39

The need to Further develop broad principles for quantifying funding liquidity risk was recently highlighted by the Multidisciplinary Working Group on Enhanced Disclosure of the Financial Stability Forum. See Financial Stability Forum (2001).

40

See Committee on the Global Financial System (1999). Notably. in times of particular financial distress, dealers may not be willing to make a market at all in certain securities. Such instances can be captured through surveys of primary security dealers. See Nelson and Passmore (2001).

41

The turnover ratio is the ratio of the average trading volume over a given period of time to the outstanding volume of securities.

42

See Box 4.1 for further discussion of sectoral balance sheet analysis.

43

Moreover. governments may feel tempted to shift to central banks the cost of bank resolution, at least partially, so as to hide these costs within the central bank balance sheet.

44

Such transactions may also have important implications for the conduct of monetary policy and the financial position of the central bank, as described in Jácome and Madrid (forthcoming).

45

See Chapter V for a discussion of the stress tests that are used in measuring sensitivity to market risk.

46

See Basel Committee (1997. 1998).

47

Duration is the weighted average life of an asset or liability (the weights being the present value of each cash flow as a percentage of the price of the asset or liability). Duration adjusts maturity to account for the size and timing of payments between now and maturity (e.g., the duration of a zero-coupon bond is equal to its maturity). In general, duration rises with maturity, falls with the frequency of coupon payments, and falls as the yield rises. The greater the duration of a bond, the greater is its volatility. For working purposes, duration can be defined as the approximate percentage change in price for a 1 percent change in yield. A discussion of the duration model can be found in Chapter V.

48

For details on the methodology, see Basel Committee (1998).

49

A related issue, which is nut explicitly covered in this paper, is that of offshore financial centers and the risks involved in the operations of these centers through links to domestic financial systems. See, for instance, IMF (2000e).

50

In many countries, due to the nature of the instruments issued by NBFIs. their liabilities are not included in the narrow monetary aggregates (M1 and M2), which typically include the transferable deposit liabilities of the banking sector (mostly commercial hanks). The liabilities of NBFIs are often included in wider monetary aggregates (M1 and M4). or are not included in monetary aggregates at all. In countries with substantial nonbank quasi-deposits, the wider monetary aggregates (M3 and M4) need to be monitored for monetary policy purposes. See IMF (2000f).

51

The Financial Stability Forum recently recommended disclosure of a series of indicators for securities firms, insurance companies, and leveraged investment funds, in addition to banks. These included indicators of market risk, funding liquidity risk, and credit risk, as well as information of the nonlife insurance sector. These indicators are aimed at disclosure at the individual institution level. The Forum recognizes the need for further development of risk assessment concepts and methods in this area. See Financial Stability Forum (2001).

55

There is a vast literature on the determinants of corporate leverage and its relevance to probability of financial distress and corporate credit ratings. See Rajan and Zingales (1995).

56

See Fitch IBCA (1998). and Standard and Poor’s (2000).

57

Methods to mark asset values to market can be used, although they have shortcomings even at the individual firm level, and are hardly feasible at the aggregate level. Similarly, market values of equity are sometimes used, but these also have shortcomings as stock prices have a short-term bias, are correlated to alternative investment opportunities and are highly volatile, and may ultimately not reflect a company’s ability to service its debt.

58

Interest expenses should be calculated to include leasing costs, ideally, earnings should be adjusted to arrive at cash flow available for operations (e.g., by amending for noncash provisions and contingency reserves, asset write-downs that do not affect cash, and blocked funds overseas). See Moody’s (1998).

59

A recent study by Moody’s (2000) concludes that the use of EBITDA interest coverage ratios can be misleading, notably as they (1) overstate cash flow in periods of working capital growth; (2) can be manipulated through aggressive accounting policies: (3) do not consider the amount of required reinvestment; and (4) say nothing about the quality of earnings, EBITDA, however, remains a legitimate tool for analyzing poorly performing corporations.

60

Ratios such as funds flow from operations to total debt (and other off-balance-sheet liabilities) are more meaningful in assessing long-term profitability trends of corporate entities and sectors.

61

In some cases, strengthened financial sector supervision may create relative incentives for firms to borrow abroad, thereby shifting foreign exchange exposure-related vulnerabilities to the corporate sector.

62

In the case of foreign exchange (as well as interest rate) exposures, swaps, caps, and hedges are tools that can significantly affect corporate financial positions.

63

Household consumption patterns can also be a leading indicator of corporate and financial sector distress. For example, there is some evidence that consumers react at an early stage to macro-economic shocks such as higher interest rates, notably in their demand for housing and consumer durables. See Bernanke and Gertler (1995).

64

For instance, a recent paper by De Ruiter and Smant (1999) finds that in the Netherlands high debt ratios do not slow durables consumption.

65

In particular, portfolio diversification reduces risks to house-hold income. This underscores the need to monitor the composition of household balance sheets, not just net wealth, to better gauge vulnerabilities.

66

For a discussion of bank liquidity indicators, see Chapter III.

68

IMF (2000a), in particular Chapter III on “Asset Prices and the Business Cycle,”

69

Real estate markets are characterized by heterogeneity, consisting of a series of geographical and sectoral submarkets that lack a central trading market. No two properties are identical and information on market transactions is often limited and not generally available. Also, real estate markets are typically characterized by infrequent trades, a negotiated pricing process, large transaction costs, and very rigid supply. In contrast to stock markets and other financial markets there is, therefore, no clear market price.

71

Cross-country comparisons of real estate developments, how ever, are complicated by differences among countries in financing structure, tax structure, and the use of real estate as collateral.

72

Commercial real estate prices were not analyzed due to the scarcity of data.

73

Sec Chapter V for details.

74

In particular, some commercial property indices cover only offices, while others include retail property as well as property used for production and storage. There are also technical differences, such as the weights used to combine different localities and qualities of property, as well as whether the mean or the median price in the sample is chosen.

75

Commonly tested shocks include a slowdown in economic growth, balance of payments shocks, and changes in inflation, interest rates, and exchange rates. Equity and security price shocks may also be important, particularly in the most advanced countries where banks and hank borrowers have significant capital market exposures, it is important to identify shocks that are representative of past country experiences, or that are justified by observed volatilities and correlations in the data.

76

The Committee on the Global Financial System (CGFS) has recently undertaken a global census of stress tests in use at major financial institutions. Sec CGFS (2000 and 2001).

77

The Monte Carlo method is a stochastic technique that generates prices by performing repealed statistical sampling experiments from random numbers. It approximates the market’s price generating process.

78

For instance, results from the most complex simulation techniques may be strongly mode I-dependent and sensitive to the parameter used.

79

For a detailed discussion of these approaches, see Blaschke, Jones, Majnoni, and Martinez Peria (2001).

80

In the presence of large, complex financial institutions with insurance activities, however, attention should also be paid to vulnerabilities arising from the nonbanking activities of the group.

81

For a complete review of this literature, see Evans, Leone, Gill, and Hilbers (2000).

82

For examples of market-based indicators for the United Slates, see Nelson and Passmore (2001).

83

For instance, the default mode approach uses an average default probability and the mark-to-market approach uses a default transition matrix based on the borrower’s credit rating.

84

Theses include J.P. Morgan’s Creditmetrics, Credit Suisse’s CreditRisk+, and KMV’s Credit Monitor Model.

86

For the simple repricing model, this requires the sorting of assets and liabilities according to their time to repricing for floating rate instruments, and remaining time to maturity for fixed rate instruments; net assets are then classified in a limited number of time categories or “buckets.” For the duration model, it is necessary to know the timing of future cash flows, which may also be grouped into different buckets.

87

See, for instance, Saunders (2000).

89

For example, the normal distribution is typically used, but it the true distribution has fatter tails, the VaR may underestimate possible losses. Moreover, linear approximations are commonly used to estimate changes in the value of the portfolio, but this may underestimate the VaR if movements in asset prices are large and the portfolio includes many assets with nonlinear pay-offs (e.g., options).

90

Appendix IV, Table A4.3 provides a detailed matrix with usefulness scores for FSIs by type of user and type of economy.

91

For example, among the Group II FSls. six have average usefulness scores in emerging and developing countries that are markedly higher than those in industrial countries.

92

Appendix IV, Table A4.4 provides detailed information on the compilation and dissemination of FSIs.

93

Components refer to the numerators or denominators that allow an indicator to be compiled or elements of the numerator or denominator that allow each, and hence the indicator itself, to be compiled.

94

Table 4.3 reports figures for the least available component of each FSI because all components must be available in order to compile the FSI.

95

A summary presentation of the 30 FSIs is shown in Appendix IV. Table A4.1.

96

Several countries indicate that some FSIs are disseminated while their components are not. If these FSIs are included with the pool of FSIs whose components are disseminated, there would he 13 FSIs altogether (instead of the 8 indicated above) that are potentially available for dissemination.

97

For example, the results suggest that systems to compile statistics on financial derivatives and the financial condition of non-financial sectors are not widely available, as indicated by the limited degree to which components are compiled for FSIs number 2.2—Ratio of total asset position in derivatives to total own funds, 2.3—Ratio of total liability position in derivatives to total own funds, 2.13—Ratio of corporate debt service to income, 2.14—Corporate net foreign currency exposure, and 2.15—Ratio of household debt to GDP.

98

Monetary statistics published in the IMF’s International Financial Statistics are the most comprehensive source for internationally comparable aggregate data on countries’ financial systems. Monetary statistics are compiled on a high-frequency monthly basis within an existing institutional framework, and internationally agreed compilation standards exist, as embodied in the IMF’s Monetary and Financial Statistics Manual. Similarly, euro area monetary statistics are used as a key element of the European Central Hank’s program on macroprudential indicators.

99

A case refers to a single observation of an FSI by a respondent.

100

The availability of FSI data on both consolidation bases could have some important advantages. For example, one respondent noted, “The survey does not address the main statistical aspect, which is reconciliation between the home and host country approach, which will be viable if both supervisory and macroeconomic statistical data sources are used.”

101

Use of historical valuations is in accordance with international statistical standards.

102

Of those who reported doing some sort of research. 61 percent were supervisors, 25 percent were policy or research analysts, and 14 percent were market or other participants. These percentages are similar to the relative weight of each group in the response sample.

103

Financial accelerator models are based on information asymmetries between borrowers and lenders. They postulate that when economic conditions are depressed and corporate net worth is low, access to credit is reduced even for worthwhile borrowers. When conditions improve and corporate net worth increases, renewed access to credit by borrowers adds to the economic stimulus. In both cases, the effects are procyclical. See also Chapter IV.

104

Defined as insurance corporations and pension funds, other financial intermediaries, and financial auxiliaries in line with the IMF’s Monetary and Financial Statistics Manual.

105

The types of data mentioned included trading volumes, bid ask spreads, and credit spreads.

106

The possibility of developing a composite indicator of financial system soundness was discussed at the 1999 Consultative Meeting on macroprudential indicators. There was a general sense that the complex reality of financial markets may 1101 lend itself to being captured in such indicators. In particular, composite indicators could prove simplistic and potentially misleading, as they may conceal or misrepresent problems by offsetting positive and negative signals from different individual components.

107

A summary of the Board discussion can be found al http://www.IMF.org/external/np/mae/FSI/200l/eng/062501.htm.

108

An explanation of terms used to define the indicators can be found in Appendix I.

109

Durations of assets and liabilities are examples of indicators that are highly relevant analytically—which is why they are included in the core set—although their compilation is not wide spread. Appendix I offers alternative indicators in cases where durations are not easily available, at least in the short term.

110

Two FSIs with usefulness ratings above 3.5 were not included on parsimony grounds as they capture aspects of bank vulnerability already covered by other FSIs. Some FSI definitions vary slightly from the ones used in the FSI Survey and they should be considered preliminary pending blither work on the definition of FSIs.

111

However, many countries would have to adjust existing data compilation programs to compile the core FSIs.

Recent Occasional Papers of the International Monetary Fund

212. Financial Soundness Indicators: Analytical Aspects and Country Practices, by V. Sundararajan, Charles Enoch, Armida San Josè, Paul Hilbers, Russell Krueger, Marina Moretti, and Graham Slack. 2002.

211. Capital Account Liberalization and Financial Sector Stability, by a staff team led by Shogo Ishii and Karl Habermeier. 2002.

210. IMF-Supported Programs in Capital Account Crises, by Atish Ghosh, Timothy Lane, Marianne Schulze-Ghattas, Aleš Bulĩt, Javier Hamann, and Alex Mourmouras. 2002.

209. Methodology for Current Account and Exchange Rate Assessments, by Peter Isard, Hamid Faruqee, G. Russell Kincaid, and Martin Fetherston. 2001.

208. Yemen in the 1990s: From Unification to Economic Reform, by Klaus Enders, Sherwyn Williams, Nada Choueiri, Yuri Sobolev, and Jan Walliser. 2001.

207. Malaysia: From Crisis to Recovery, by Kanitta Meesook, II Houng Lee, Olin Liu, Yougesh Khatri, Natalia Tamirisa, Michael Moore, and Mark H. Krysl. 2001.

206. The Dominican Republic: Stabilization, Structural Reform, and Economic Growth, by Alessandro Gius-tiniani, Werner C. Keller, and Randa E. Sab. 2001.

205. Stabilization and Savings Funds for Nonrenewable Resources, by Jeffrey Davis, Rolando Ossowski, James Daniel, and Steven Barnett. 2001.

204. Monetary Union in West Africa (ECOWAS): Is It Desirable and How Could It Be Achieved? by Paul Masson and Catherine Pattillo. 2001.

203. Modern Banking and OTC Derivatives Markets: The Transformation of Global Finance and Its Implications for Systemic Risk, by Garry J. Schinasi, R. Sean Craig, Burkhard Drees, and Charles Kramer. 2000.

202. Adopting Inflation Targeting: Practical Issues for Emerging Market Countries, by Andrea Schaechter, Mark R. Stone, and Mark Zelmer. 2000.

201. Developments and Challenges in the Caribbean Region, by Samuel Itam, Simon Cueva, Erik Lundback, Janet Stotsky, and Stephen Tokarick. 2000.

200. Pension Reform in the Baltics: Issues and Prospects, by Jerald Schiff, Niko Hobdari, Axel Schimmelpfennig, and Roman Zytek. 2000.

199. Ghana: Economic Development in a Democratic Environment, by Sérgio Pereira Leite, Anthony Pelle-chio, Luisa Zanforlin, Girma Begashaw, Stefania Fabrizio, and Joachim Harnack. 2000.

198. Setting Up Treasuries in the Baltics, Russia, and Other Countries of the Former Soviet Union: An Assessment of IMF Technical Assistance, by Barry H. Potter and Jack Diamond, 2000.

197. Deposit Insurance: Actual and Good Practices, by Gillian G.H. Garcia. 2000.

196. Trade and Trade Policies in Eastern and Southern Africa, by a staff team led by Arvind Subramanian, with Enrique Gelbard, Richard Harmsen, Katrin Elborgh-Woytek, and Piroska Nagy. 2000.

195. The Eastern Caribbean Currency Union—Institutions, Performance, and Policy Issues, by Frits van Beek, José Roberto Rosales, Mayra Zermeño, Ruby Randall, and Jorge Shepherd. 2000.

194. Fiscal and Macroeconomic Impact of Privatization, by Jeffrey Davis, Rolando Ossowski, Thomas Richardson, and Steven Barnett. 2000.

193. Exchange Rate Regimes in an Increasingly Integrated World Economy, by Michael Mussa, Paul Masson. Alexander Swoboda, Esteban Jadresic, Paolo Mauro, and Andy Berg. 2000.

192. Macroprudenrial Indicators of Financial System Soundness, by a staff team led by Owen Evans, Alfredo M. Leone, Mahinder Gill, and Paul Hilbers. 2000.

191. Social Issues in IMF-Supported Programs, by Sanjeev Gupta, Louis Dicks-Mireaux, Ritha Khemani, Calvin McDonald, and Marijn Verhoeven. 2000.

190. Capital Controls: Country Experiences with Their Use and Liberalization, by Akira Ariyoshi, Karl Habermeier, Bernard Laurens, Inci ötker-Robe. Jorge Iván Canales Kriljenko, and Andrei Kirilenko, 2000.

189. Current Account and External Sustainability in the Baltics, Russia, and Other Countries of the Former Soviet Union, by Donal McGettigan. 2000.

188. Financial Sector Crisis and Restructuring: Lessons from Asia, by Carl-Johan Lindgren, Tomás J.T Baliño, Charles Enoch, Anne-Marie Guide, Marc Quintyn, and Leslie Teo. 1999.

187. Philippines: Toward Sustainable and Rapid Growth, Recent Developments and the Agenda Ahead, by Markus Rodlauer, Prakash Loungani, Vivek Arora, Charalambos Christofides, Enrique G. De la Piedra, Piyabha Kongsamut, Kristina Kostial, Victoria Summers, and Athanasios Vamvakidis. 2000.

186. Anticipating Balance of Payments Crises; The Role of Early Warning Systems, by Andrew Berg. Eduardo Borensztein. Gian Maria Milesi-Ferretti, and Catherine Pattiilo. 1999.

185. Oman Beyond the Oil Horizon: Policies Toward Sustainable Growth, edited by Ahsan Mansur and Volker Treichel. 1999.

184. Growth Experience in Transition Countries. 1990–98. by Oleh Havrylyshyn. Thomas Wolf, Julian Beren-gaut, Marta Castello-Branco, Ron van Rooden, and Valerie Mercer-Blackman. 1999.

183. Economic Reforms in Kazakhstan, Kyrgyz Republic, Tajikistan, Turkmenistan, and Uzbekistan, by Emine Gürgen, Harry Snoek, Jon Craig, Jimmy McHugh, Ivailo Izvorski, and Ron van Rooden. 1999.

182. Tax Reform in the Baltics, Russia, and Other Countries of the Former Soviet Union, by a staff team led by Liam Ebrill and Oleh Havrylyshyn. 1999.

181. The Netherlands: Transforming a Market Economy, by C. Maxwell Watson, Bas B. Bakker, Jan Kees Martijn, and Ioannis Halikias. 1999.

180. Revenue Implications of Trade Liberalization, by Liam Ebrill, Janet Stotsky, and Reint Gropp. 1999.

179. Disinflation in Transition: 1993–97, by Carlo Cottarelli and Peter Doyle. 1999.

178. IMF-Supported Programs in Indonesia. Korea, and Thailand: A Preliminary Assessment, by Timothy Lane, Atish Ghosh, Javier Hamann, Steven Phillips Marianne Schulze-Ghattas, and Tsidi Tsikata. 1999.

177. Perspectives on Regional Unemployment in Europe, by Paolo Mauro, Eswar Prasad, and Antonio Spilim-bergo. 1999.

176. Back to the Future: Postwar Reconstruction and Stabilization in Lebanon, edited by Sena Eken and Thomas Helbling. 1999.

175. Macroeconomic Developments in the Baltics, Russia, and Other Countries of the Former Soviet Union, 1992–97, by Luis M. Valdivieso. 1998.

174. Impact of EMU on Selected Non-European Union Countries, by R. Feldman, K. Nashashibi, R. Nord, P. Allum, D. Desruelle, K. Enders, R. Kahn, and H. Temprano-Arroyo. 1998.

173. The Baltic Countries: From Economic Stabilization to EU Accession, by Julian Berengaut, Augusto Lopez-Claros, Françoise Le Gall, Dennis Jones, Richard Stern, Ann-Margret Westin, Effie Psalida, Pietro Garibaldi. 1998.

172. Capital Account Liberalization: Theoretical and Practical Aspects, by a staff team led by Barry Eichen-green and Michael Mussa, with Giovanni Dell’Ariccia, Enrica Detragiache, Gian Maria Milesi-Ferretti, and Andrew Tweedie. 1998.

171. Monetary Policy in Dollarized Economies, by Tomás Baliño, Adam Bennett, and Eduardo Borensztein, 1998.

170. The West African Economic and Monetary Union: Recent Developments and Policy Issues, by a staff team led by Ernesto Hernández-Catá and comprising Christian A. François, Paul Masson, Pascal Bou-vier, Patrick Peroz, Dominique Desruelle, and Athanasios Vamvakidis. 1998.

169. Financial Sector Development in Sub-Saharan African Countries, by Hassanali Mehran, Piero Ugolini, Jean Phillipe Briffaux, George Iden, Tonny Lybek, Stephen Swaray, and Peter Hayward. 1998.

168. Exit Strategies: Policy Options for Countries Seeking Greater Exchange Rale Flexibility, by a staff team led by Barry Eichengreen and Paul Masson with Hugh Bredenkamp, Barry Johnston, Javier Hamann, Esteban Jadresic, and Inci Ötker.1998.

167. Exchange Rate Assessment: Extensions of the Macroeconomic Balance Approach, edited by Peter Isard and Hamid Faruqee. 1998.

166. Hedge Funds and Financial Market Dynamics, by a staff team led by Barry Eichengreen and Donald Mathieson with Bankim Chadha, Anne Jansen, Laura Kodres, and Sunil Sharma. 1998.

165. Algeria: Stabilization and Transition to the Market, by Karim Nashashibi, Patricia Alonso-Gamo, Stefania Bazzoni, Alain Féler, Nicole Laframboise, and Sebastian Paris Horvitz. 1998.

Note: For information on the title and availability of Occasional Papers not listed, please consult the IMF Publications Catalog or contact IMF Publication Services.

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Cover Financial Soundness Indicators
Financial Soundness Indicators
Analytical Aspects and Country Practices
ISBN:
9781589060869
ISSN:
0251-6365
Publication Date:
08 Apr 2002
Publisher:
International Monetary Fund
DOI:
https://doi.org/10.5089/9781589060869.084
Pages:
111

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