New Economics Papers
on Risk Management
Issue of 2012‒11‒17
eleven papers chosen by

  1. Modeling default correlation in a US retail loan portfolio By Bams, Dennis; Pisa, Magdalena; Wolff, Christian C
  2. Ranking Systemically Important Financial Institutions By Mardi Dungey; Matteo Luciani; David Veredas
  3. Using transfer entropy to measure information flows between financial markets By Thomas Dimpfl; Franziska J. Peter; ;
  4. Covered bonds, core markets, and financial stability By Kartik Anand; James Chapman; Prasanna Gai;
  5. Shadow banking: a review of the literature By Tobias Adrian; Adam B. Ashcraft
  6. Risk Management Instruments for Food Price Volatility and Weather Risk in Latin America and the Caribbean: The Use of Risk Management Instruments By Anne G. Murphy; Jason Hartell; Víctor Cárdenas; Jerry R. Skees
  7. Funded Bilateral Valuation Adjustment By Lorenzo Giada; Claudio Nordio
  8. Fitting and Forecasting Sovereign Defaults Using Multiple Risk Signals By Roberto Savona; Marika Vezzoli
  9. "Realized stochastic volatility with leverage and long memory" By Shinichiro Shirota; Takayuki Hizu; Yasuhiro Omori
  10. Long memory and Periodicity in Intraday Volatility By Eduardo Rossi; Dean Fantazzini
  11. Systemic Risks in Global Banking: What Available Data can tell us and What More Data are Needed? By Eugenio Cerutti; Stijn Claessens; Patrick McGuire

  1. By: Bams, Dennis; Pisa, Magdalena; Wolff, Christian C
    Abstract: This paper generalizes the existing asymptotic single-factor model to address issues related to industry heterogeneity, default clustering and parameter uncertainty of capital requirement in US retail loan portfolios. We argue that the Basel II capital requirement overstates the riskiness of small businesses even with prudential adjustments. Moreover, our estimates show that both location and spread of loss distribution bare uncertainty. Their shifts over the course of the recent crisis have important risk management implications. The results are based on a unique representative dataset of US small businesses from 2005 to 2011 and give fundamental insights into the US economy.
    Keywords: Credit risk
    JEL: G2 G3
    Date: 2012–11
  2. By: Mardi Dungey (School of Economics and Finance, University of Tasmania; CFAP University of Cambridge, CAMA ANU); Matteo Luciani (ECARES, Solvay Brussels School of Economics and Management, Université libre de Bruxelles; F.R.S.-FNRS); David Veredas (ECARES, Solvay Brussels School of Economics and Management, and Duisenberg school of finance)
    Abstract: We propose a simple network–based methodology for ranking systemically important financial institutions. We view the risks of firms –including both the financial sector and the real economy– as a network with nodes representing the volatility shocks. The metric for the connections of the nodes is the correlation between these shocks. Daily dynamic centrality measures allow us to rank firms in terms of risk connectedness and firm characteristics. We present a general systemic risk index for the financial sector. Results from applying this approach to all firms in the S&P500 for 2003–2011 are twofold. First, Bank of America, JP Morgan and Wells Fargo are consistently in the top 10 throughout the sample. Citigroup and Lehman Brothers also were consistently in the top 10 up to late 2008. At the end of the sample, insurance firms emerge as systemic. Second, the systemic risk in the financial sector built–up from early 2005, peaked in September 2008, and greatly reduced after the introduction of TARP and the rescue of AIG. Anxiety about European debt markets saw the systemic risk begin to rise again from April 2010. We further decompose these results to find that the systemic risk of insurance and deposit– taking institutions differs importantly, the latter experienced a decline from late 2007, in line with the burst of the housing price bubble, while the former continued to climb up to the rescue of AIG.
    Keywords: Systemic risk; ranking; financial institutions; Lehman
    JEL: G01 G10 G18 G20 G28 G32 G38
    Date: 2012–10–26
  3. By: Thomas Dimpfl; Franziska J. Peter; ;
    Abstract: We use transfer entropy to quantify information flows between financial markets and propose a suitable bootstrap procedure for statistical inference. Transfer entropy is a model-free measure designed as the Kullback-Leibler distance of transition probabilities. Our approach allows to determine, measure and test for information transfer without being restricted to linear dynamics. In our empirical application, we examine the importance of the credit default swap market relative to the corporate bond market for the pricing of credit risk. We also analyze the dynamic relation between market risk and credit risk proxied by the VIX and the iTraxx Europe, respectively. We conduct the analyses for pre-crisis, crisis and post-crisis periods.
    Keywords: entropy; information flow; non-linear dynamics; price discovery; credit risk; CDS
    Date: 2012–08
  4. By: Kartik Anand; James Chapman; Prasanna Gai;
    Abstract: We examine the financial stability implications of covered bonds. Banks issue covered bonds by encumbering assets on their balance sheet and placing them within a dynamic ring fence. As more assets are encumbered, jittery unsecured creditors may run, leading to a banking crisis. We provide conditions for such a crisis to occur. We examine how different over-the-counter market network structures influence the liquidity of secured funding markets and crisis dynamics. We draw on the framework to consider several policy measures aimed at mitigating systemic risk, including caps on asset encumbrance, global legal entity identifiers, and swaps of good for bad collateral by central banks.
    Keywords: covered bonds, over-the-counter markets, systemic risk, asset encumbrance, legal entity identifiers, velocity of collateral
    JEL: G01 G18 G21
    Date: 2012–10
  5. By: Tobias Adrian; Adam B. Ashcraft
    Abstract: We provide an overview of the rapidly evolving literature on shadow credit intermediation. The shadow banking system consists of a web of specialized financial institutions that conduct credit, maturity, and liquidity transformation without direct, explicit access to public backstops. The lack of such access to sources of government liquidity and credit backstops makes shadow banks inherently fragile. Much of shadow banking activities is intertwined with the operations of core regulated institutions such as bank holding companies and insurance companies, thus creating a source of systemic risk for the financial system at large. We review fundamental reasons for the existence of shadow banking, explain the functioning of shadow banking institutions and activities, discuss why shadow banks need to be regulated, and review the impact of recent reform efforts on shadow banking credit intermediation.
    Keywords: Intermediation (Finance) ; Systemic risk ; Financial risk management ; Financial institutions ; Financial market regulatory reform
    Date: 2012
  6. By: Anne G. Murphy; Jason Hartell; Víctor Cárdenas; Jerry R. Skees
    Abstract: This report examines some of the implications of price risk and volatility, and weather risks in the LAC region that are important threats to already vulnerable populations. It considers the advantages and limitations of a set of financial instruments for managing these risks; and identifies potential mechanisms for addressing concerns about the socioeconomic consequences of price and weather volatility. In reviewing the innovations that are being tested in the LAC region and around the world, what is striking is that they appear to be disparate and largely piecemeal solutions to the problems of price and natural disaster risk management - they are not integrated. A more efficient and holistic solution should draw upon the recent efforts of coordination among countries within regions. The importance of risk aggregation and pooling combined with the comparative advantage of International Financial Institutions to access capital and work in a regional context, suggests a strategy to develop a fully multicountry approach to risk management. This strategy calls for establishing a Regional Asset Management Platform (RAMP) that integrates central stakeholders and develops pricing and measurement tools for extreme weather risk management and price volatility in a more efficient fashion. Global drivers of price volatility for major commodities can be managed using international futures exchange markets to some extent. However, regional climate anomalies will also mean that individual countries can suffer price volatility that represents a basis risks when using international futures markets. Thus, combining risk transfer products for regional climate anomalies with the use of careful hedging strategies for global volatility may offer better risk management strategies for either lower than expected prices that adversely affect producers or higher than expected prices that adversely affect consumers.
    Keywords: Environment & Natural Resources :: Disasters, Financial Sector :: Financial Markets, Financial Sector :: Financial Risk, Agriculture & Food Security :: Plant, Animal, & Food Production, Commodity price risk, weather index insurance, agriculture, food security
    Date: 2012–09
  7. By: Lorenzo Giada; Claudio Nordio
    Abstract: We show how the cost of funding the collateral in a particular set up can be equal to the Bilateral Valuation Adjustment with the "funded" probability of default, leading to the definition of a Funded Bilateral Valuation Adjustment (FBVA). That set up can also be viewed by an investor as an effective way to restructure the counterparty risk arising from an uncollateralized transaction with a counterparty, mitigating or even avoiding entirely the additional capital charge introduced by the new Basel III framework.
    Date: 2012–11
  8. By: Roberto Savona (Department of Business Studies, University Of Brescia); Marika Vezzoli (Department of Quantitative Methods, University Of Brescia)
    Abstract: In this paper we face the fitting versus forecasting paradox with the objective of realizing an optimal Early Warning System to better describe and predict past and future sovereign defaults. We do this by proposing a new Regression Tree-based model that signals a potential crisis whenever preselected indicators exceed specific thresholds. Using data on 66 emerging markets over the period 1975-2002, our model provides an accurate description of past data, although not the best description relative to existing competing models (Logit, Stepwise logit, Noise-to-Signal Ratio and Regression Trees), and produces the best forecasts accomodating to different risk aversion targets. By modulating in- and out-of sample model accuracy, our methodology leads to unambiguous empirical results, since we find that illiquidity (short-term debt to reserves ratio), insolvency (reserve growth) and contagion risks act as the main determinants/predictors of past/future debt crises.
    Keywords: Data mining; Evaluating forecasts; Model selection; Panel data; Probability forecasting.
    JEL: C14 C23 G01 H63
    Date: 2012
  9. By: Shinichiro Shirota (Graduate School of Economics, University of Tokyo); Takayuki Hizu (Mitsubishi UFJ Trust and Banking); Yasuhiro Omori (Faculty of Economics, University of Tokyo)
    Abstract: The daily return and the realized volatility are simultaneously modeled in the stochastic volatility model with leverage and long memory. The dependent variable in the stochastic volatility model is the logarithm of the squared return, and its error distribution is approximated by a mixture of normals. In addition, we incorporate the logarithm of the realized volatility into the measurement equation, assuming that the latent log volatility follows an Autoregressive Fractionally Integrated Moving Average (ARFIMA) process to describe its long memory property. Using a state space representation, we propose an ecient Bayesian estimation method implemented using Markov chain Monte Carlo method (MCMC). Model comparisons are performed based on the marginal likelihood, and the volatility forecasting performances are investigated using S&P500 stock index returns.
    Date: 2012–11
  10. By: Eduardo Rossi (Department of Economics and Management, University of Pavia); Dean Fantazzini (Moscow School of Economics, M.V. Lomonosov Moscow State University)
    Abstract: Intraday return volatilities are characterized by the contemporaneous presence of periodicity and long memory. This paper proposes two new parameterizations of the intraday volatility: the Fractionally Integrated Periodic EGARCH and the Seasonal Fractional Integrated Periodic EGARCH, which provide the required flexibility to account for both features. The periodic kurtosis and periodic autocorrelations of power transformations of the absolute returns are computed for both models. The empirical application shows that volatility of the hourly Emini S&P 500 futures returns are characterized by a periodic leverage effect coupled with a statistically significant long-range dependence. An out-of-sample forecasting comparison with alternative models shows that a constrained version of the FI-PEGARCH provides superior forecasts. A simulation experiment is carried out to investigate the effects that sample frequency has on the fractional differencing parameter estimate.
    Keywords: Intraday volatility, Long memory, FI-PEGARCH, SFI-PEGARCH, Periodicmodels.
    JEL: C22 C58 G13
    Date: 2012–11
  11. By: Eugenio Cerutti; Stijn Claessens; Patrick McGuire
    Abstract: The recent financial crisis has shown how interconnected the financial world has become. Shocks in one location or asset class can have a sizable impact on the stability of institutions and markets around the world. But systemic risk analysis is severely hampered by the lack of consistent data that capture the international dimensions of finance. While currently available data can be used more effectively, supervisors and other agencies need more and better data to construct even rudimentary measures of risks in the international financial system. Similarly, market participants need better information on aggregate positions and linkages to appropriately monitor and price risks. Ongoing initiatives that will help in closing data gaps include the G20 Data Gaps Initiative, which recommends the collection of consistent bank-level data for joint analyses and enhancements to existing sets of aggregate statistics, and the enhancement to the BIS international banking statistics.
    JEL: F21 F34 G15 G18 Y1
    Date: 2012–11

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