nep-rmg New Economics Papers
on Risk Management
Issue of 2017‒11‒12
thirteen papers chosen by
Stan Miles
Thompson Rivers University

  1. Choosing Stress Scenarios for Systemic Risk Through Dimension Reduction By Pritsker, Matthew
  2. Bank capital allocation under multiple constraints By Tirupam Goel; Ulf Lewrick; Agnė Nikola Tarashev
  3. Network models of financial systemic risk: A review By Fabio Caccioli; Paolo Barucca; Teruyoshi Kobayashi
  4. Bondholder Reorganization of Systemically Important Financial Institutions By Steven Gjerstad
  5. The perverse incentive for insurance instruments that are derivatives: solving the jackpot problem with a clawback lien for default insurance notes By Brian P. Hanley
  6. How Bad Is a Bad Loan? Distinguishing Inherent Credit Risk from Inefficient Lending (Does the Capital Market Price This Difference?) By Joseph Hughes; Choon-Geol Moon
  7. Predicting Exchange Rate Volatility in Brazil: an approach using quantile autoregression By Alessandra Pasqualina Viola; Marcelo Cabus Klotzle; Antonio Carlos Figueiredo Pinto; Wagner Piazza Gaglianone
  8. Design of Macro-prudential Stress Tests By Orlov, Dmitry; Zryumov, Pavel; Skrzypacz, Andrzej
  9. Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors By Todd E Clark; Michael W McCracken; Elmar Mertens
  10. Regime switching behavior of volatilities of Islamic equities: evidence from Markov- Switching GARCH models for some selected broad based indices By Reza, Md. Ridwan; Masih, Mansur
  11. Forecasting compositional risk allocations By Tim J. Boonen; Montserrat Guillén; Miguel Santolino
  12. Implied volatility smile dynamics in the presence of jumps By Martin Magris; Perttu Barholm; Juho Kanniainen
  13. Retirement in the Shadow (Banking) By Guillermo Ordoñez; Facundo Piguillem

  1. By: Pritsker, Matthew (Federal Reserve Bank of Boston)
    Abstract: Regulatory stress-testing is an important tool for ensuring banking system health in many countries around the world. Current methodologies ensure banks are well capitalized against the scenarios in the test, but it is unclear how resilient banks will be to other plausible scenarios. This paper proposes a new methodology for choosing scenarios that uses a measure of systemic risk with Correlation Pursuit variable selection, and Sliced Inverse Regression factor analysis, to select variables and create factors based on their ability to explain variation in the systemic risk measure. The main result is under appropriate regularity conditions, when the banking system is well capitalized against stress-scenarios based on movements in the factors, then an approximation of systemic risk is low, i.e. the banking system will be well capitalized against the other plausible scenarios that could affect it with high probability. The paper also shows there are circumstances when several scenarios may be required to achieve systemic risk objectives. The methodology should be useful for regulatory stress-testing of banks. Although not done in this paper, the methodology can potentially be adapted for stress-testing of other financial firms including insurance companies and central counterparties.
    Keywords: Stress Testing; financial stability; banking
    JEL: G21 G28
    Date: 2017–09–05
  2. By: Tirupam Goel; Ulf Lewrick; Agnė Nikola Tarashev
    Abstract: Banks allocate capital across business units while facing multiple constraints that may bind contemporaneously or only in future states. When risks rise or risk management strengthens, a bank reallocates capital to the more efficient unit. This unit would have generated higher constraint- and risk-adjusted returns while satisfying a tightened constraint at the old capital allocation. Calibrated to US data, our model reveals that, when credit or market risk increases, market-making attracts capital and lending shrinks. Leverage constraints affect banks only when measured risks are low. At low credit risk, tighter leverage constraints may reduce market-making but support lending.
    Keywords: internal capital market, Value-at-Risk, leverage ratio, risk-adjusted return on capital
    JEL: G21 G28 G3
    Date: 2017–10
  3. By: Fabio Caccioli (Department of Computer Science, University College London, UK); Paolo Barucca (Department of Banking and Finance, University of Zurich, Switzerland); Teruyoshi Kobayashi (Graduate School of Economics, Kobe University)
    Abstract: The global financial system can be represented as a large complex network in which banks, hedge funds and other financial institutions are interconnected to each other through visible and invisible financial linkages. Recently, a lot of attention has been paid to the understanding of the mechanisms that can lead to a breakdown of this network. This can happen when the existing financial links turn from being a means of risk diversification to channels for the propagation of risk across financial institutions. In this review article, we summarize recent developments in the modeling of financial systemic risk. We focus in particular on network approaches, such as models of default cascades due to bilateral exposures or to overlapping portfolios, and we also report on recent findings on the empirical structure of interbank networks. The current review provides a landscape of the newly arising interdisciplinary field lying at the intersection of several disciplines, such as network science, physics, engineering, economics, and ecology.
    Date: 2017–11
  4. By: Steven Gjerstad (Economic Science Institute, Chapman University)
    Abstract: Paper presented at conference on Systemic Risk and the Organization of the Financial System, Chapman University, May 13, 2017. This paper describes a resolution process for faltering financial firms that quickly allocates losses to bondholders and transfers ownership of the firm to them. This process overcomes the most serious flaws in resolution plans submitted by banks under Dodd-Frank Title I and in the FDIC receivership procedure in Dodd-Frank Title II by restoring the balance sheet of a failing financial institution and immediately replacing the management and board of directors who allowed its demise. In almost all bank failures, this process would eliminate the need for government involvement beyond court certification of the reorganization. The procedure overcomes the serious incentive distortions and inefficiencies that result from bailouts, and avoids the destruction of value and financial market turmoil that would result from the bankruptcies and liquidations that Dodd-Frank requires for distressed and failing banks.
    Date: 2017
  5. By: Brian P. Hanley
    Abstract: When an insurance note is also a derivative a serious problem arises because a derivative must be fulfilled immediately. This feature of derivatives prevents claims processing procedures that screen out ineligible claims. This, in turn, creates a perverse incentive for insured holders of notes to commit acts that result in payment. This problem first surfaced with CDS contracts, which are part of a class of loan insurance I term a default insurance note. Without an address to this problem, within the average range of returns for a large venture capital portfolio, a venture-bank makes less money the better their investments do, in a continuous function. The highest rate of return is a total loss, 64% more than a top portfolio. Here, a strategy for removing this perverse incentive is defined, consisting of a clawback lien that returns part of the payment value as a lien on the firm that is the beneficiary of the insurance. This is presented as the final major component for implementing a default insurance note system so that venture-banking can operate to maximum benefit. Removing the perverse incentive also minimizes disincentive for underwriters to deny DIN coverage to new venture capital firms, or to those firms that have historical earnings which are below average.
    Date: 2017–10
  6. By: Joseph Hughes (Rutgers University); Choon-Geol Moon (Hanyang University)
    Abstract: We develop a novel technique to decompose banks’ ratio of nonperforming loans to total loans into two components: first, a minimum ratio that represents best-practice lending given the volume and composition of a bank’s loans, the average contractual interest rate charged on these loans, and market conditions such as the average GDP growth rate and market concentration; and, second, a ratio, the difference between the bank’s observed ratio of nonperforming loans and the best-practice minimum ratio, that represents the bank’s proficiency at loan making. The best-practice ratio of nonperforming loans, the ratio a bank would experience if it were fully efficient at credit-risk evaluation and loan monitoring, represents the inherent credit risk of the loan portfolio and is estimated by stochastic frontier techniques. We apply the technique to 2013 data on top-tier U.S. bank holding companies. We divide them into five size groups. The largest banks with consolidated assets exceeding $250 billion experience the highest ratio of nonperformance among the five groups. Moreover, the inherent credit risk of their lending is the highest among the five groups. On the other hand, their inefficiency at lending is one of the lowest among the five. Thus, the high ratio of nonperformance of the largest financial institutions appears to result from lending to riskier borrowers, not inefficiency at lending. Small community banks under $1 billion also exhibit higher inherent credit risk than all other size groups except the largest banks. In contrast, their loan-making inefficiency is highest among the five size groups. Restricting the sample to publicly traded bank holding companies and gauging financial performance by market value, we find the ratio of nonperforming loans to total loans is on average negatively related to financial performance except at the largest banks. When nonperformance is decomposed into inherent credit risk and lending inefficiency, taking more inherent credit risk enhances market value at many more large banks while lending inefficiency is negatively related to market value at all banks. Market discipline appears to reward riskier lending at large banks and discourage lending inefficiency at all banks.
    Keywords: commercial banking, credit risk, nonperforming loans, lending efficiency
    JEL: G21 L25 C58
    Date: 2017–10–30
  7. By: Alessandra Pasqualina Viola; Marcelo Cabus Klotzle; Antonio Carlos Figueiredo Pinto; Wagner Piazza Gaglianone
    Abstract: We apply quantile regression in some of its new formulations to analyze exchange rate volatility. We use the conditional autoregressive value at risk (CAViaR) model of Engle and Manganelli (2004), which applies autoregressive functions to quantile regression to estimate volatility. That model has proved effective when compared to others for various purposes. We not only compare the forecasting power of models based on quantile regression with some models of the GARCH family, but also examine the behavior of the exchange rate along its conditional distribution and its consequent volatility. When applying CAViaR in the whole distribution, our results show differentiation of the angular coefficients for each quantile interval of the distribution for the asymmetric CAViaR model. With respect to the exchange rate volatility, we build forecasts from 60 models and use two models as reference to apply the predictive ability test of Giacomini and White (2006). The results indicate that the prediction of the asymmetric CAViaR model with quantile interval of (1, 99) is better than (or equal to) 66% of the models and worse than 34%. In turn, the other benchmark model, the GARCH (1,1), is worse than 71% of the models, better than 13%, and equal in forecasting precision to 16% of the models
    Date: 2017–11
  8. By: Orlov, Dmitry (University of Rochester); Zryumov, Pavel (University of PA); Skrzypacz, Andrzej (Stanford University)
    Abstract: We study the design of macro-prudential stress tests and capital requirements. The tests provide information about correlation in banks portfolios. The regulator chooses contingent capital requirements that create a liquidity buffer in case of a fire sale. The optimal stress test discloses information partially: when systemic risk is low, capital requirements reflect full information. When systemic risk is high, the regulator pools information and requires all banks to hold precautionary liquidity. With heterogeneous banks, weak banks determine level of transparency and strong banks are often required to hold excess capital when systemic risk is high. Moreover, dynamic disclosure and capital adjustments can improve welfare.
    Date: 2017–05
  9. By: Todd E Clark; Michael W McCracken; Elmar Mertens
    Abstract: We develop uncertainty measures for point forecasts from surveys such as the Survey of Professional Forecasters, Blue Chip, or the Federal Open Market Committee's Summary of Economic Projections. At a given point of time, these surveys provide forecasts for macroeconomic variables at multiple horizons. To track time-varying uncertainty in the associated forecast errors, we derive a multiple-horizon speci cation of stochastic volatility. Compared to constant-variance approaches, our stochastic-volatility model improves the accuracy of uncertainty measures for survey forecasts.
    Keywords: stochastic volatility, survey forecasts, fan charts
    JEL: E37 C53
    Date: 2017–10
  10. By: Reza, Md. Ridwan; Masih, Mansur
    Abstract: In this era of shaky global economic and financial conditions for about a decade now since the global financial crisis 2008, how the volatilities of Islamic equities worldwide are behaving, especially in terms of their regime changing behavior, if any, is the main issue of concern in this paper. To this end, a relatively novel technique, namely, Markov regime switching GARCH (MSGARCH) is applied to some selected broad based Islamic equity indices from both advanced and emerging world and of their combinations. The results tend to indicate that in general there is no persistence in any particular regime to prevail, rather a high regime switching behavior between volatile and less volatile regimes are present in Islamic equities around the world. This perhaps reflects the prolonged uncertainties prevailing in the world economies and therefore implies higher risk for the investors in predicting their investment outcome.
    Keywords: volatilities of Islamic equities, Markov regime switching, MSGARCH, GARCH
    JEL: C22 C58 G15
    Date: 2017–07–10
  11. By: Tim J. Boonen (University of Amsterdam); Montserrat Guillén (Riskcenter, Department of Econometrics, University of Barcelona. Diagonal Av. 690, 08034, Barcelona, Spain.); Miguel Santolino (Riskcenter, Department of Econometrics, University of Barcelona. Diagonal Av. 690, 08034, Barcelona, Spain.)
    Abstract: We analyse models for panel data that arise in risk allocation problems,when a given set of sources are the cause of an aggregate risk value. We focus on the modeling and forecasting of proportional contributions to risk. Compositional data methods are proposed and the regression is flexible to incorporate external information from other variables. We guarantee that projected proportional contributions add up to 100%, and we introduce a method to generate confidence regions with the same restriction. An illustration using data from the stock exchange is provided.
    Keywords: Simplex, capital allocation, dynamic management.
    JEL: C02 G22 D81
    Date: 2017–10
  12. By: Martin Magris; Perttu Barholm; Juho Kanniainen
    Abstract: The main purpose of this work is to examine the behavior of the implied volatility smiles around jumps, contributing to the literature with a high-frequency analysis of the smile dynamics based on intra-day option data. From our high-frequency SPX S\&P500 index option dataset, we utilize the first three principal components to characterize the implied volatility smile and analyze its dynamics by the distribution of the scores' means and variances and other statistics for the first hour of the day, in scenarios where jumps are detected and not. Our analyses clearly suggest that changes in the volatility smiles have abnormal properties around jumps compared with the absence of jumps, regardless of maturity and type of the option.
    Date: 2017–11
  13. By: Guillermo Ordoñez (University of Pennsylvania and NBER); Facundo Piguillem (EIEF and CEPR)
    Abstract: The U.S.economy has recently experienced a large increase in life expectancy and in shadow banking activities. We argue these two phenomena are intimately related. Agents resort on financial intermediaries to buy insurance against an uncertain life span after retirement. When they expect to live longer they are more prone to rely on financial intermediaries that are riskier but offer better terms for insurance – shadow banks. We calibrate the model to replicate the level of financial intermediation in 1980, introduce the observed change in life expectancy and show that the demographic transition is critical to account for the boom both of shadow banking and credit that preceded the recent U.S. financial crisis. We construct a counterfactual without shadow banks and show that they may have contributed 0.5 GDP, which is larger than the cost of the crisis of around 0.2 GDP.
    Date: 2017

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