Industry practices in credit risk modeling and internal capital allocations: implications for a models-based regulatory capital standard

This paper was presented at the conference "Financial services at the crossroads: capital regulation in the twenty-first century" as part of session 2, "Credit risk modeling." The conference, held at the Federal Reserve Bank of New York on February 26-27, 1998, was designed to encourage a consensus between the public and private sectors on an agenda for capital regulation in the new century.Risk ; Econometric models ; Bank capital

Adverse Feedback Loop in the Bank-Based Financial Systems

This paper examines procyclicality of the financial system. The introduction describes the natural and regulatory sources of procyclicality, focusing on the potential procyclical effect of the current Basel II regulatory framework for banks. It also mentions the regulatory tools for mitigating procyclical behaviour by financial institutions currently being discussed in international forums. Under certain conditions, procyclical behaviour of the banking sector can lead to an adverse feedback loop whereby banks, in response to an economic downswing, engage in deleveraging and reduce their lending to the economy in order to maintain the required capital adequacy ratio. This then further negatively affects economic output and impacts back on banks in the form of, for example, increased loan losses. In the main empirical section of the paper, this effect was simulated on the example of the Czech banking sector. The simulation results suggest that under certain assumptions the feedback loop may play an important role.procyclicality; feedback loop; bank regulation; deleveragin

MATHEMATICAL-STATISTICAL MODELS IN INSURANCE

The insurance companies use many different models especially when they look for the optimal solutions of problems in pricing and development of product, complete risk profile of the company, risk quantification, cession of risks, capital adequacy, the location of assets, administration and management of capital and in many other areas. The big world-wide insurance companies invest huge amounts to development of models focused on right pricing insured risks and also risks which are very difficult quantified and non-insurable nowadays, but probably they will influence the insurance and reinsurance market markedly in future. Mentioned risks are risk of global ecological disasters, risk of global climatic conditions, energetic risks, risk of information and communication technologies, etc. The climatic changes bring new and statistic uncharted risks. The insurance companies have to give up reliance only upon risks models strictly based on historical data. The models are simplified images of complicated real systems and modeling is often sole instrument for their understanding. The key to successful modeling is also accession to right information. The insurance companies have to develop database of information and also technologies for specialists responsible for decision making. The problem is not sufficient data of loss experience in some countries. The modeling, if it should be exact, has to work with sufficient data. Because of decrease of costs connected to records archive and database making, it will be not problems in future

MATHEMATICAL-STATISTICAL MODELS IN INSURANCE

The insurance companies use many different models especially when they look for the optimal solutions of problems in pricing and development of product, complete risk profile of the company, risk quantification, cession of risks, capital adequacy, the location of assets, administration and management of capital and in many other areas. The big world-wide insurance companies invest huge amounts to development of models focused on right pricing insured risks and also risks which are very difficult quantified and non-insurable nowadays, but probably they will influence the insurance and reinsurance market markedly in future. Mentioned risks are risk of global ecological disasters, risk of global climatic conditions, energetic risks, risk of information and communication technologies, etc. The climatic changes bring new and statistic uncharted risks. The insurance companies have to give up reliance only upon risks models strictly based on historical data. The models are simplified images of complicated real systems and modeling is often sole instrument for their understanding. The key to successful modeling is also accession to right information. The insurance companies have to develop database of information and also technologies for specialists responsible for decision making. The problem is not sufficient data of loss experience in some countries. The modeling, if it should be exact, has to work with sufficient data. Because of decrease of costs connected to records archive and database making, it will be not problems in future

Role of the Bank for International Settlements in Shaping the World Financial System, The

The Bank for International Settlements ( BIS ) was set up in Basel, Switzerland in 1923 to handle remaining financial issues from World War II largely having to do with German reparation payments. It was the first of the semi-public international banks. Over the years its functions have changed and, largely since the late 1970\u27s, it has served as the situs for the world\u27s central banks and financial regulators to pool ideas and deal with international financial issues. A group of committees, com- posed largely of representatives of central bankers, now meets at BIS and has been issuing memoranda and drafts of regulations on a number of subjects affecting international banking. Among these are the regulation of capital, the management of international conglomerates, and problems resulting from electronic banking. Problems in world banking have sensitized observers to the absence of coordinated regulation and to the need for some form of unified control. That there is a need for one international bank regulators increasingly acknowledged. BIS comes closer than any other organization to fulfilling this function. The International Monetary Fund ( IMF ) comes close but is too politicized and has been too involved in attempting to meet a continuing series of crises to do any long range thinking. Only BIS has attracted the intellectual resources to analyze and resolve international problems in a thoughtful and deliberate manner. Only BIS output is being adopted in the world\u27s banking centers. BIS has been proposed as a world senior financial regulator. This article acknowledges the rationale for such a decision but argues that now is not the time for such an attempt. Banking is, of course, conducted locally even though its reach is international. To anoint any body as a senior regulator with the power to impose rules would require massive compromises among national regulators to achieve one central set of rules. It would also involve an abdication of measures of sovereignty by the constituent states. An effort of this kind would risk destroying the whole concept. Rather than start such a bold stroke at such an inopportune time, this Article argues that the international banking world would fare far better assisting BIS to proceed down the current track. As it continues to mature, and as its edicts are increasingly accepted throughout the world it will continue to approach its rightful place as the world\u27s bank regulator

The Return of the Rogue

The “rogue trader”—a famed figure of the 1990s—recently has returned to prominence due largely to two phenomena. First, recent U.S. mortgage market volatility spilled over into stock, commodity, and derivative markets worldwide, causing large financial institution losses and revealing previously hidden unauthorized positions. Second, the rogue trader has gained importance as banks around the world have focused more attention on operational risk in response to regulatory changes prompted by the Basel II Capital Accord. This Article contends that of the many regulatory options available to the Basel Committee for addressing operational risk it arguably chose the worst: an enforced selfregulatory regime unlikely to substantially alter financial institutions’ ability to successfully manage operational risk. That regime also poses the danger of high costs, a false sense of security, and perverse incentives. Particularly with respect to the low-frequency, high-impact events—including rogue trading—that may be the greatest threat to bank stability and soundness, attempts at enforced self-regulation are unlikely to significantly reduce operational risk, because those financial institutions with the highest operational risk are the least likely to credibly assess that risk and set aside adequate capital under a regime of enforced self-regulation

Econometrics: A Bird’s Eye View

As a unified discipline, econometrics is still relatively young and has been transforming and expanding very rapidly over the past few decades. Major advances have taken place in the analysis of cross sectional data by means of semi-parametric and non-parametric techniques. Heterogeneity of economic relations across individuals, firms and industries is increasingly acknowledged and attempts have been made to take them into account either by integrating out their effects or by modeling the sources of heterogeneity when suitable panel data exists. The counterfactual considerations that underlie policy analysis and treatment evaluation have been given a more satisfactory foundation. New time series econometric techniques have been developed and employed extensively in the areas of macroeconometrics and finance. Non-linear econometric techniques are used increasingly in the analysis of cross section and time series observations. Applications of Bayesian techniques to econometric problems have been given new impetus largely thanks to advances in computer power and computational techniques. The use of Bayesian techniques have in turn provided the investigators with a unifying framework where the tasks of forecasting, decision making, model evaluation and learning can be considered as parts of the same interactive and iterative process; thus paving the way for establishing the foundation of “real time econometrics”. This paper attempts to provide an overview of some of these developments.history of econometrics, microeconometrics, macroeconometrics, Bayesian econometrics, nonparametric and semi-parametric analysis

Evaluating the German Inventory Cycle Using Data from the Ifo Business Survey

Inventory fluctuations are an important phenomenon in business cycles. However, the preliminary data on inventory investment as published in the German national accounts are tremendously prone to revision and therefore ill-equipped to diagnose the current stance of the inventory cycle. The Ifo business survey contains information on the assessments of inventory stocks in manufacturing as well as in retail andwholesale trade. Static factor analysis anda methodbuild ing on canonical correlations are appliedto construct a composite index of inventory fluctuations. Based on recursive estimates, the different variants are assessedas regards the stability of the weighting schemes andthe ability to forecast the "true" inventory fluctuations better than the preliminary official releases. --inventory investment,revisions,composite indices,canonical correlation,factor models,national accounts data,Ifo business survey,Germany

Evaluating the German Inventory Cycle – Using Data from the Ifo Business Survey

Inventory fluctuations are an important phenomenon in business cycles. However, the preliminary data on inventory investment as published in the German national accounts are tremendously prone to revision and therefore ill-equipped to diagnose the current stance of the inventory cycle. The Ifo business survey contains information on the assessments of inventory stocks in manufacturing as well as in retail and wholesale trade. Static factor analysis and a method building on canonical correlations are applied to construct a composite index of inventory fluctuations. Based on recursive estimates, the different variants are assessed as regards the stability of the weighting schemes and the ability to forecast the “true” inventory fluctuations better than the preliminary official releases.inventory investment, revisions, composite indices, canonical correlation, factor models, national accounts data, Ifo business survey, Germany