The Risk Map: A New Tool for Validating Risk Models
The Risk Map: A New Tool for Validating Risk Models
By Gilbert Colletaz, Christophe Hurlin, and Christophe Perignon
SSRN (2012)
Abstract Paper

Gilbert Colletaz

University of Orleans

France

Coder Page  

Christophe Hurlin

University of Orleans

France

Coder Page  

Christophe Perignon

HEC Paris

France

Coder Page  

The goal of this code is to automatically create a "Risk Map" from a series of Value-at-Risk (VaR) and profit and loss (P&L). Given the time series of VaR(α) and P&L, we generate the corresponding time series for VaR(α'), with α'<α through calibration. This is done by extracting the conditional variance of the P&L from VaR(α) and then plugging it into the formula for VaR(α'). A "super exception" is then defined as P&L < -VaR(α'). We formally test whether the sequence of exceptions and super exceptions satisfies standard backtesting conditions. Finally, the Risk Map graphically summarizes all information about the performance of the risk model.
Created
June 16, 2011
Software:
Matlab
Visits
431
Last update
July 25, 2013
Ranking
51
Runs
146
Code downloads
90
Abstract
This paper presents a new tool for validating risk models. This tool, called the Risk Map, jointly accounts for the number and the magnitude of extreme losses and graphically summarizes all information about the performance of a risk model. It relies on the concept of Value-at-Risk (VaR) super exception, which is defined as a situation in which the loss exceeds both the standard VaR and a VaR defined at an extremely low coverage probability. We then formally test whether the sequences of exceptions and super exceptions is rejected by standard model validation tests. We show that the Risk Map can be used to validate market, credit, operational, or systemic (e.g. CoVaR) risk estimates or to assess the performance of the margin system of a clearing house.
Colletaz, G., C. Hurlin, and C. Perignon, "The Risk Map: A New Tool for Validating Risk Models", SSRN.
Coverage rate α
Coverage rate α
Coverage rate α'
Coverage rate α'
P&L
P&L
VaR(alpha)
VaR(alpha)
Waiting time

Please cite the publication as :

Colletaz, G., C. Hurlin, and C. Perignon, "The Risk Map: A New Tool for Validating Risk Models", SSRN.

Please cite the companion website as :

Colletaz, G., C. Hurlin, and C. Perignon, "The Risk Map: A New Tool for Validating Risk Models", RunMyCode companion website, http://www.execandshare.org/CompanionSite/Site2

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Variable/Parameters Description, constraint Comments
Coverage rate α
    α denotes the standard coverage rate of the VaR forecasts.
    Coverage rate α'
      α' denotes the coverage rate used to defined the super VaR exceptions. α' has to be smaller than α.
      P&L
        This series corresponds to the observed P&L. The sample size T is implicit.
        VaR(alpha)
          This series corresponds to the VaR(α). The sample size T is implicit.
          Variable/Parameters Description Visualisation
          Coverage rate α α=1% in the case of the Caixa Bank.
          Coverage rate α' We choose by convention α'=0.2% to define super-exceptions.
          P&L This series corresponds to the daily P&L for La Caixa bank (2007-2008). T=500.
          VaR(alpha) This series corresponds to the VaR(1%) issued from La Caixa's internal risk models
          The Risk Map: A New Tool for Validating Risk Models
          G. Colletaz, C. Hurlin, and C. Perignon (2011)
          Computing Date Status Actions
          Coders:

          Gilbert Colletaz also created these companion sites

          Backtesting Value-at-Risk: A GMM Duration-based Test
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          This paper proposes a new duration-based backtesting procedure for VaR forecasts. The GMM test framework proposed by Bontemps (2006) to test for the distributional assumption (i.e. the geometric distribution) is applied to the case of the VaR forecasts validity. Using simple J-statistic based on the moments defined by the orthonormal polynomials associated with the geometric distribution, this new approach tackles most of the drawbacks usually associated to duration based backtesting procedures. First, its implementation is extremely easy. Second, it allows for a separate test for unconditional coverage, independence and conditional coverage hypothesis (Christoffersen, 1998). Third, Monte-Carlo simulations show that for realistic sample sizes, our GMM test outperforms traditional duration based test. Besides, we study the consequences of the estimation risk on the duration-based backtesting tests and propose a sub-sampling approach for robust inference derived from Escanciano and Olmo (2009). An empirical application for Nasdaq returns confirms that using GMM test leads to major consequences for the ex-post evaluation of the risk by regulation authorities.
          Colletaz, G., B. Candelon, C. Hurlin, and S. Tokpavi, "Backtesting Value-at-Risk: A GMM Duration-based Test", Journal of Financial Econometrics, 9(2), 314-343 .
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          Asymptotic Distribution-Free Diagnostic Tests For Heteroskedastic Time Series
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          This article investigates model checks for a class of possibly nonlinear heteroskedastic time series models, including but not restricted to ARMA-GARCH models. We propose omnibus tests based on functionals of certain weighted standardized residual empirical processes. The new tests are asymptotically distribution-free, suitable when the conditioning set is infinite-dimensional, and consistent against a class of Pitman’s local alternatives converging at the parametric rate n-1/2, with n the sample size. A Monte Carlo study shows that the simulated level of the proposed tests is close to the asymptotic level already for moderate sample sizes and that tests have a satisfactory power performance. Finally, we illustrate our methodology with an application to the well-known S&P 500 daily stock index. The paper also contains an asymptotic uniform expansion for weighted residual empirical processes when initial conditions are considered, a result of independent interest.
          Colletaz, G., "Asymptotic Distribution-Free Diagnostic Tests For Heteroskedastic Time Series", Econometric Theory, 26(03), 744-773.
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          Network Effects and Infrastructure Productivity in Developing Countries
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          This paper proposes to investigate the threshold effects of the productivity of infrastructure investment in developing countries within a panel data framework. Various speci.cations of an augmented production function that allow for endogenous thresholds are considered. The overwhelming outcome is the presence of strong threshold effects in the relationship between output and private and public inputs. Whatever the transition mechanism used, the testing procedures lead to strong rejection of the linearity of this relationship. In particular, the productivity of infrastructure investment generally exhibits some network effects. When the available stock of infrastructure is very low, investment in this sector has the same productivity as non-infrastructure investment. On the contrary, when a minimumnetwork is available, the marginal productivity of infrastructure investment is generally largely greater than the productivity of other investments. Finally, when the main network is achieved, its marginal productivity becomes similar to the productivity of other investment.
          Candelon, B., G. Colletaz, and C. Hurlin, "Network Effects and Infrastructure Productivity in Developing Countries", Maastricht University.
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          Abstract
          Risk exposures are typically quantified in terms of a "Value at Risk" (VaR) estimate. A VaR estimate corresponds to a specific critical value of a portfolio's potential one-day profit and loss probability distribution. Given their function both as internal risk management tools and as potential regulatory measures of risk exposure, it is important to quantify the accuracy of an institution's VaR estimates. This study shows that the formal statistical procedures that would typically be used in performance-based VaR verification tests require large samples to produce a reliable assessment of a model's accuracy in predicting the size and likelihood of very low probability events. Verification test statistics based on historical trading profits and losses have very poor power in small samples, so it does not appear possible for a bank or its supervisor to verify the accuracy of a VaR estimate unless many years of performance data are available. Historical simulation-based verification test statistics also require long samples to generate accurate results: Estimates of 0.01 critical values exhibit substantial errors even in samples as large as ten years of daily data.
          Hurlin, C., C. Perignon, "Techniques for Verifying the Accuracy of Risk Management Models", Journal of Derivatives, 3, 73-84.
          Authors: Kupiec
          Coders: Hurlin
          Perignon
          Last update
          04/17/2012
          Ranking
          57
          Runs
          26
          Visits
          339
          A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test
          Abstract
          The panel data unit root test suggested by Levin and Lin (LL) has been widely used in several applications, notably in papers on tests of the purchasing power parity hypothesis. This test is based on a very restrictive hypothesis which is rarely ever of interest in practice. The Im–Pesaran–Shin (IPS) test relaxes the restrictive assumption of the LL test. This paper argues that although the IPS test has been offered as a generalization of the LL test, it is best viewed as a test for summarizing the evidence from a number of independent tests of the sample hypothesis. This problem has a long statistical history going back to R. A. Fisher. This paper suggests the Fisher test as a panel data unit root test, compares it with the LL and IPS tests, and the Bonferroni bounds test which is valid for correlated tests. Overall, the evidence points to the Fisher test with bootstrap-based critical values as the preferred choice. We also suggest the use of the Fisher test for testing stationarity as the null and also in testing for cointegration in panel data.
          Hurlin, C., "A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test", Oxford Bulletin of Economics and Statistics, 61, 631-652.
          Authors: Maddala
          Wu
          Coders: Hurlin
          Last update
          10/08/2012
          Ranking
          59
          Runs
          217
          Visits
          129
          Is Public Capital Really Productive? A Methodological Reappraisal
          Abstract
          We present an evaluation of the main empirical approaches used in the literature to estimate the contribution of public capital stock to growth and private factors' productivity. Based on a simple stochastic general equilibrium model, built as to reproduce the main long-run relations observed in US post-war historical data, we show that the production function approach may not be reliable to estimate this contribution. Our analysis reveals that this approach largely overestimates the public capital elasticity, given the presence of a common stochastic trend shared by all non-stationary inputs.
          Minea, A., and C. Hurlin, "Is Public Capital Really Productive? A Methodological Reappraisal", University of Orleans.
          Authors: Minea
          Hurlin
          Coders: Minea
          Hurlin
          Last update
          09/10/2012
          Ranking
          43
          Runs
          3
          Visits
          42
          Margin Backtesting
          Abstract
          This paper presents a validation framework for collateral requirements or margins on a derivatives exchange. It can be used by investors, risk managers, and regulators to check the accuracy of a margining system. The statistical tests presented in this study are based either on the number, frequency, magnitude, or timing of margin exceedances, which are de…ned as situations in which the trading loss of a market participant exceeds his or her margin. We also propose an original way to validate globally the margining system by aggregating individual backtesting statistics ob- tained for each market participant.
          Hurlin, C., and C. Perignon, "Margin Backtesting", University of Orleans, HEC Paris.
          Authors: Hurlin
          Perignon
          Coders: Hurlin
          Perignon
          Last update
          07/23/2014
          Ranking
          36
          Runs
          377
          Visits
          433
          Testing for Granger Non-causality in Heterogeneous Panels
          Abstract
          This paper proposes a very simple test of Granger (1969) non-causality for hetero- geneous panel data models. Our test statistic is based on the individual Wald statistics of Granger non causality averaged across the cross-section units. First, this statistic is shown to converge sequentially to a standard normal distribution. Second, the semi- asymptotic distribution of the average statistic is characterized for a fixed T sample. A standardized statistic based on an approximation of the moments of Wald statistics is hence proposed. Third, Monte Carlo experiments show that our standardized panel statistics have very good small sample properties, even in the presence of cross-sectional dependence.
          Dumitrescu, E., and C. Hurlin, "Testing for Granger Non-causality in Heterogeneous Panels", Economic Modelling, Forthcoming.
          Authors: Dumitrescu
          Hurlin
          Coders: Dumitrescu
          Hurlin
          Last update
          07/12/2017
          Ranking
          40
          Runs
          451
          Visits
          502
          Value-at-Risk (Chapter 5: Computing VaR)
          Abstract
          Book description: To accommodate sweeping global economic changes, the risk management field has evolved substantially since the first edition of Value at Risk, making this revised edition a must. Updates include a new chapter on liquidity risk, information on the latest risk instruments and the expanded derivatives market, recent developments in Monte Carlo methods, and more. Value at Risk will help professional risk managers understand, and operate within, today’s dynamic new risk environment.
          Hurlin, C., C. Perignon, "Value-at-Risk (Chapter 5: Computing VaR)", MacGraw-Hill, Third Edition.
          Authors: Jorion
          Coders: Hurlin
          Perignon
          Last update
          03/19/2012
          Ranking
          44
          Runs
          63
          Visits
          328
          Backtesting Value-at-Risk Accuracy: A Simple New Test
          Abstract
          This paper proposes a new test of value-at-risk (VAR) validation. Our test exploits the idea that the sequence of VAR violations (hit function) – taking value 1 - α if there is a violation, and -α otherwise – for a nominal coverage rate α verifies the properties of a martingale difference if the model used to quantify risk is adequate (Berkowitz et al., 2005). More precisely, we use the multivariate portmanteau statistic of Li and McLeod (1981), an extension to the multivariate framework of the test of Box and Pierce (1970), to jointly test the absence of autocorrelation in the vector of hit sequences for various coverage rates considered relevant for the management of extreme risks. We show that this shift to a multivariate dimension appreciably improves the power properties of the VAR validation test for reasonable sample sizes.
          Hurlin, C., and S. Tokpavi, "Backtesting Value-at-Risk Accuracy: A Simple New Test", Journal of Risk, 9, 19-37.
          Authors: Hurlin
          Tokpavi
          Coders: Hurlin
          Tokpavi
          Last update
          03/13/2012
          Ranking
          49
          Runs
          2
          Visits
          240
          Unit Root Tests for Panel Data
          Abstract
          This paper develops unit root tests for panel data. These tests are devised under more general assumptions than the tests previously proposed. First, the number of groups in the panel data is assumed to be either finite or infinite. Second, each group is assumed to have different types of nonstochastic and stochastic components. Third, the time series spans for the groups are assumed to be all different. Fourth, the alternative where some groups have a unit root and others do not can be dealt with by the tests. The tests can also be used for the null of stationarity and for cointegration, once relevant changes are made in the model, hypotheses, assumptions and underlying tests. The main idea for our unit root tests is to combine p-values from a unit root test applied to each group in the panel data. Combining p-values to formulate tests is a common practice in meta-analysis. This paper also reports the finite sample performance of our combination unit root tests and Im et al.'s [Mimeo (1995)] t-bar test. The results show that most of the combination tests are more powerful than the t-bar test in finite samples. Application of the combination unit root tests to the post-Bretton Woods US real exchange rate data provides some evidence in favor of the PPP hypothesis.
          Hurlin, C., "Unit Root Tests for Panel Data", Journal of International Money and Finance, 20, 249-272.
          Authors: Choi
          Coders: Hurlin
          Last update
          10/08/2012
          Ranking
          60
          Runs
          62
          Visits
          261
          Testing for Unit Roots in Heterogeneous Panels
          Abstract
          This paper proposes unit root tests for dynamic heterogeneous panels based on the mean of individual unit root statistics. In particular it proposes a standardized t-bar test statistic based on the (augmented) Dickey–Fuller statistics averaged across the groups. Under a general setting this statistic is shown to converge in probability to a standard normal variate sequentially with T (the time series dimension) →∞, followed by N (the cross sectional dimension) →∞. A diagonal convergence result with T and N→∞ while N/T→k,k being a finite non-negative constant, is also conjectured. In the special case where errors in individual Dickey–Fuller (DF) regressions are serially uncorrelated a modified version of the standardized t-bar statistic is shown to be distributed as standard normal as N→∞ for a fixed T, so long as T>5 in the case of DF regressions with intercepts and T>6 in the case of DF regressions with intercepts and linear time trends. An exact fixed N and T test is also developed using the simple average of the DF statistics. Monte Carlo results show that if a large enough lag order is selected for the underlying ADF regressions, then the small sample performances of the t-bar test is reasonably satisfactory and generally better than the test proposed by Levin and Lin (Unpublished manuscript, University of California, San Diego, 1993).
          Hurlin, C., "Testing for Unit Roots in Heterogeneous Panels ", Journal of Econometrics, 115, 53-74.
          Authors: Im
          Pesaran
          Shin
          Coders: Hurlin
          Last update
          10/08/2012
          Ranking
          61
          Runs
          57
          Visits
          106
          Testing for a Unit Root in Panels with Dynamic Factors
          Abstract
          This paper studies testing for a unit root for large n and T panels in which the cross-sectional units are correlated. To model this cross-sectional correlation, we assume that the data are generated by an unknown number of unobservable common factors. We propose unit root tests in this environment and derive their (Gaussian) asymptotic distribution under the null hypothesis of a unit root and local alternatives. We show that these tests have significant asymptotic power when the model has no incidental trends. However, when there are incidental trends in the model and it is necessary to remove heterogeneous deterministic components, we show that these tests have no power against the same local alternatives. Through Monte Carlo simulations, we provide evidence on the finite sample properties of these new tests.
          Hurlin, C., "Testing for a Unit Root in Panels with Dynamic Factors", Journal of Econometrics, 122, 81-126.
          Authors: Moon
          Perron
          Coders: Hurlin
          Last update
          10/08/2012
          Ranking
          62
          Runs
          399
          Visits
          124
          Determining the Number of Factors in Approximate Factors Models
          Abstract
          In this paper we develop some econometric theory for factor models of large dimensions. The focus is the determination of the number of factors (r), which is an unresolved issue in the rapidly growing literature on multifactor models. We first establish the convergence rate for the factor estimates that will allow for consistent estimation of r. We then propose some panel criteria and show that the number of factors can be consistently estimated using the criteria. The theory is developed under the framework of large cross-sections (N) and large time dimensions (T). No restriction is imposed on the relation between N and T. Simulations show that the proposed criteria have good finite sample properties in many configurations of the panel data encountered in practice.
          Hurlin, C., "Determining the Number of Factors in Approximate Factors Models", Econometrica, 70, 191-221.
          Authors: Bai
          Ng
          Coders: Hurlin
          Last update
          01/29/2013
          Ranking
          39
          Runs
          66
          Visits
          230
          Maximum Likelihood Methods for Models of Markets in Disequilibrium
          Abstract
          For the abstract, please click on: http://www.jstor.org/discover/10.2307/1914215?uid=3738016&uid=2&uid=4&sid=56146953873
          Hurlin, C., "Maximum Likelihood Methods for Models of Markets in Disequilibrium", Econometrica, 42, 1013-1030.
          Authors: Maddala
          Nelson
          Coders: Hurlin
          Last update
          02/15/2013
          Ranking
          50
          Runs
          85
          Visits
          391
          Why don’t Banks Lend to the Private Sector in Egypt?
          Abstract
          Bank credit to the private sector fell as a share to GDP during the last decade, in spite of a successful bank recapitalization in the middle of the 2000s and high and stable growth before the recent macroeconomic turmoil. This paper explains this trend based on both bank supply factors and demand for credit from the private sector. First the paper describes the evolution of the banks’ sources and uses of funds in the period 2005-2011, characterized by two different cycles of external capital flows. Then it estimates supply and demand equations of credit to the private sector, using quarterly data for the period 1999-2011. First, the system of simultaneous equations is estimated assuming continuous market clearing. Then the system is estimated allowing for transitory disequilibrium. In general, the main results are robust to the market clearing assumption. Our main findings show that, while real industrial production and the stock market have a significant impact on credit demand, deposits and claims on government affected the supply of credit in Egypt. Finally, both models yield similar results for the most recent period of private credit contraction: the single most important factor explaining the largest share of the decline is the expansion of banking credit to the public sector. The slowdown in economic activity and the contraction of bank deposits explain the remainder of the predicted contraction in bank credit to the private sector.
          Herrera, S., C. Hurlin, and C. Zaki, "Why don’t Banks Lend to the Private Sector in Egypt? ", World Bank Working Paper Series.
          Authors: Herrera
          Hurlin
          Zaki
          Coders: Herrera
          Hurlin
          Zaki
          Last update
          10/17/2013
          Ranking
          56
          Runs
          252
          Visits
          112
          Are Public Investment Efficient in Creating Capital Stocks in Developing Countries? Estimates of Government Net Capital Stocks for 26 Developing Countries, 1970-2002
          Abstract
          In many poor countries, the problem is not that governments do not invest, but that these investments do not create productive capital. So, the cost of public investments does not correspond to the value of the capital stocks. In this paper, we propose an original non parametric approach to evaluate the efficiency function that links variations (net of depreciation) of stocks to public investments. We consider four sectors (electricity, telecommunications, roads and railways) of two Latin American countries (Mexico and Colombia). We show that there is a large discrepancy between the amount of investments and the value of increases in stocks.
          Arestoff, F., and C. Hurlin, "Are Public Investment Efficient in Creating Capital Stocks in Developing Countries? Estimates of Government Net Capital Stocks for 26 Developing Countries, 1970-2002 ", Economics Bulletin, 30, 1515-1531.
          Authors: Arestoff
          Hurlin
          Coders: Arestoff
          Hurlin
          Last update
          10/08/2012
          Ranking
          11
          Runs
          N.A.
          Visits
          26

          Christophe Perignon also created these companion sites

          A New Approach to Comparing VaR Estimation Methods
          Abstract
          We develop a novel backtesting framework based on multidimensional Value-at-Risk (VaR) that focuses on the left tail of the distribution of the bank trading revenues. Our coverage test is a multivariate generalization of the unconditional test of Kupiec (Journal of Derivatives, 1995). Applying our method to actual daily bank trading revenues, we find that non-parametric VaR methods, such as GARCH-based methods or filtered Historical Simulation, work best for bank trading revenues.
          Perignon, C., and D. Smith, C. Hurlin, "A New Approach to Comparing VaR Estimation Methods", Journal of Derivatives , 15, 54-66.
          Authors: Perignon
          Smith
          Coders: Perignon
          Smith
          Hurlin
          Last update
          07/16/2012
          Ranking
          54
          Runs
          11
          Visits
          270
          Backtesting Value-at-Risk: A Duration-Based Approach
          Abstract
          Financial risk model evaluation or backtesting is a key part of the internal model’s approach to market risk management as laid out by the Basle Committee on Banking Supervision. However, existing backtesting methods have relatively low power in realistic small sample settings. Our contribution is the exploration of new tools for backtesting based on the duration of days between the violations of the Value-at-Risk. Our Monte Carlo results show that in realistic situations, the new duration-based tests have considerably better power properties than the previously suggested tests.
          Hurlin, C., and C. Perignon, "Backtesting Value-at-Risk: A Duration-Based Approach", Journal of Financial Econometrics, 2, 84-108.
          Authors: Pelletier
          Christoffersen
          Coders: Hurlin
          Perignon
          Last update
          07/23/2012
          Ranking
          26
          Runs
          17
          Visits
          207
          Evaluating Interval Forecasts
          Abstract
          A complete theory for evaluating interval forecasts has not been worked out to date. Most of the literature implicitly assumes homoskedastic errors even when this is clearly violated and proceed by merely testing for correct unconditional coverage. Consequently, the author sets out to build a consistent framework for conditional interval forecast evaluation, which is crucial when higher-order moment dynamics are present. The new methodology is demonstrated in an application to the exchange rate forecasting procedures advocated in risk management.
          Hurlin, C., C. Perignon, "Evaluating Interval Forecasts", International Economic Review, 39, 841-862.
          Authors: Christoffersen
          Coders: Hurlin
          Perignon
          Last update
          03/09/2012
          Ranking
          32
          Runs
          57
          Visits
          167
          The Best of Both Worlds: A Hybrid Approach to Calculating Value at Risk
          Abstract
          The hybrid approach combines the two most popular approaches to VaR estimation: RiskMetrics and Historical Simulation. It estimates the VaR of a portfolio by applying exponentially declining weights to past returns and then finding the appropriate percentile of this time-weighted empirical distribution. This new approach is very simple to implement. Empirical tests show a significant improvement in the precision of VaR forecasts using the hybrid approach relative to these popular approaches.
          Hurlin, C., C. Perignon, "The Best of Both Worlds: A Hybrid Approach to Calculating Value at Risk", Risk, 1, 64-67.
          Authors: Boudoukh
          Richardson
          Whitelaw
          Coders: Hurlin
          Perignon
          Last update
          07/17/2012
          Ranking
          52
          Runs
          4
          Visits
          67
          Diversification and Value-at-Risk
          Abstract
          A pervasive and puzzling feature of banks’ Value-at-Risk (VaR) is its abnormally high level, which leads to excessive regulatory capital. A possible explanation for the tendency of commercial banks to overstate their VaR is that they incompletely account for the diversification effect among broad risk categories (e.g., equity, interest rate, commodity, credit spread, and foreign exchange). By underestimating the diversification effect, bank’s proprietary VaR models produce overly prudent market risk assessments. In this paper, we examine empirically the validity of this hypothesis using actual VaR data from major US commercial banks. In contrast to the VaR diversification hypothesis, we find that US banks show no sign of systematic underestimation of the diversification effect. In particular, diversification effects used by banks is very close to (and quite often larger than) our empirical diversification estimates. A direct implication of this finding is that individual VaRs for each broad risk category, just like aggregate VaRs, are biased risk assessments.
          Perignon, C., and D. Smith, "Diversification and Value-at-Risk", Journal of Banking and Finance, 34.
          Authors: Perignon
          Smith
          Coders: Perignon
          Smith
          Last update
          11/23/2012
          Ranking
          9999
          Runs
          N.A.
          Visits
          45
          A Theoretical and Empirical Comparison of Systemic Risk Measures: MES versus CoVaR
          Abstract
          In this paper, we propose a theoretical and empirical comparison of two popular systemic risk measures - Marginal Expected Shortfall (MES) and Delta Conditional Value at Risk (ΔCoVaR) - that can be estimated using publicly available data. First, we assume that the time-varying correlation completely captures the dependence between firm and market returns. Under this assumption, we derive three analytical results: (i) we show that the MES corresponds to the product of the conditional ES of market returns and the time-varying beta of this institution, (ii) we give an analytical expression of the ΔCoVaR and show that the CoVaR corresponds to the product of the VaR of the firm's returns and the time-varying linear projection coefficient of the market returns on the firm's returns and (iii) we derive the ratio of the MES to the ΔCoVaR. Second, we relax this assumption and propose an empirical comparison for a panel of 61 US financial institutions over the period from January 2000 to December 2010. For each measure, we propose a cross-sectional analysis, a time-series comparison and rankings analysis of these institutions based on the two measures.
          Benoit, S., G. Colletaz, C. Hurlin, and C. Perignon, "A Theoretical and Empirical Comparison of Systemic Risk Measures: MES versus CoVaR", SSRN.
          Authors: Benoit
          Colletaz
          Hurlin
          Perignon
          Coders: Benoit
          Colletaz
          Hurlin
          Perignon
          Last update
          10/25/2012
          Ranking
          53
          Runs
          181
          Visits
          398
          Value-at-Risk (Chapter 7: Portfolio Risk - Analytical Methods)
          Abstract
          Book description: To accommodate sweeping global economic changes, the risk management field has evolved substantially since the first edition of Value at Risk, making this revised edition a must. Updates include a new chapter on liquidity risk, information on the latest risk instruments and the expanded derivatives market, recent developments in Monte Carlo methods, and more. Value at Risk, Second Edition, will help professional risk managers understand, and operate within, today’s dynamic new risk environment.
          Hurlin, C., C. Perignon, "Value-at-Risk (Chapter 7: Portfolio Risk - Analytical Methods)", McGraw-Hill, Second edition.
          Authors: Jorion
          Coders: Hurlin
          Perignon
          Last update
          03/16/2012
          Ranking
          33
          Runs
          9
          Visits
          303
          Techniques for Verifying the Accuracy of Risk Management Models
          Abstract
          Risk exposures are typically quantified in terms of a "Value at Risk" (VaR) estimate. A VaR estimate corresponds to a specific critical value of a portfolio's potential one-day profit and loss probability distribution. Given their function both as internal risk management tools and as potential regulatory measures of risk exposure, it is important to quantify the accuracy of an institution's VaR estimates. This study shows that the formal statistical procedures that would typically be used in performance-based VaR verification tests require large samples to produce a reliable assessment of a model's accuracy in predicting the size and likelihood of very low probability events. Verification test statistics based on historical trading profits and losses have very poor power in small samples, so it does not appear possible for a bank or its supervisor to verify the accuracy of a VaR estimate unless many years of performance data are available. Historical simulation-based verification test statistics also require long samples to generate accurate results: Estimates of 0.01 critical values exhibit substantial errors even in samples as large as ten years of daily data.
          Hurlin, C., C. Perignon, "Techniques for Verifying the Accuracy of Risk Management Models", Journal of Derivatives, 3, 73-84.
          Authors: Kupiec
          Coders: Hurlin
          Perignon
          Last update
          04/17/2012
          Ranking
          57
          Runs
          26
          Visits
          339
          The pernicious effects of contaminated data in risk management
          Abstract
          Banks hold capital to guard against unexpected surges in losses and long freezes in financial markets. The minimum level of capital is set by banking regulators as a function of the banks’ own estimates of their risk exposures. As a result, a great challenge for both banks and regulators is to validate internal risk models. We show that a large fraction of US and international banks uses contaminated data when testing their models. In particular, most banks validate their market risk model using profit-and-loss (P/L) data that include fees and commissions and intraday trading revenues. This practice is inconsistent with the definition of the employed market risk measure. Using both bank data and simulations, we find that data contamination has dramatic implications for model validation and can lead to the acceptance of misspecified risk models. Moreover, our estimates suggest that the use of contaminated data can significantly reduce (market-risk induced) regulatory capital.
          Fresard, L., C. Perignon, and A. Wilhelmsson, "The pernicious effects of contaminated data in risk management", Journal of Banking and Finance, 35.
          Authors: Fresard
          Perignon
          Wilhelmsson
          Coders: Fresard
          Perignon
          Wilhelmsson
          Last update
          11/23/2012
          Ranking
          9999
          Runs
          N.A.
          Visits
          42
          The level and quality of Value-at-Risk disclosure by commercial banks
          Abstract
          In this paper we study both the level of Value-at-Risk (VaR) disclosure and the accuracy of the disclosed VaR figures for a sample of US and international commercial banks. To measure the level of VaR disclosures, we develop a VaR Disclosure Index that captures many different facets of market risk disclosure. Using panel data over the period 1996–2005, we find an overall upward trend in the quantity of information released to the public. We also find that Historical Simulation is by far the most popular VaR method. We assess the accuracy of VaR figures by studying the number of VaR exceedances and whether actual daily VaRs contain information about the volatility of subsequent trading revenues. Unlike the level of VaR disclosure, the quality of VaR disclosure shows no sign of improvement over time. We find that VaR computed using Historical Simulation contains very little information about future volatility.
          Perignon, C., and D. Smith, "The level and quality of Value-at-Risk disclosure by commercial banks", Journal of Banking and Finance, 34.
          Authors: Perignon
          Smith
          Coders: Perignon
          Smith
          Last update
          11/23/2012
          Ranking
          9999
          Runs
          N.A.
          Visits
          25
          A New Approach to Comparing VaR Estimation Methods
          Abstract
          We develop a novel backtesting framework based on multidimensional Value-at-Risk (VaR) that focuses on the left tail of the distribution of the bank trading revenues. Our coverage test is a multivariate generalization of the unconditional test of Kupiec (Journal of Derivatives, 1995). Applying our method to actual daily bank trading revenues, we find that non-parametric VaR methods, such as GARCH-based methods or filtered Historical Simulation, work best for bank trading revenues.
          Perignon, C., and D. Smith, "A New Approach to Comparing VaR Estimation Methods", Journal of Derivatives, Winter.
          Authors: Smith
          Perignon
          Coders: Perignon
          Smith
          Last update
          11/23/2012
          Ranking
          9999
          Runs
          N.A.
          Visits
          43
          Margin Backtesting
          Abstract
          This paper presents a validation framework for collateral requirements or margins on a derivatives exchange. It can be used by investors, risk managers, and regulators to check the accuracy of a margining system. The statistical tests presented in this study are based either on the number, frequency, magnitude, or timing of margin exceedances, which are de…ned as situations in which the trading loss of a market participant exceeds his or her margin. We also propose an original way to validate globally the margining system by aggregating individual backtesting statistics ob- tained for each market participant.
          Hurlin, C., and C. Perignon, "Margin Backtesting", University of Orleans, HEC Paris.
          Authors: Hurlin
          Perignon
          Coders: Hurlin
          Perignon
          Last update
          07/23/2014
          Ranking
          36
          Runs
          377
          Visits
          433
          Value-at-Risk (Chapter 5: Computing VaR)
          Abstract
          Book description: To accommodate sweeping global economic changes, the risk management field has evolved substantially since the first edition of Value at Risk, making this revised edition a must. Updates include a new chapter on liquidity risk, information on the latest risk instruments and the expanded derivatives market, recent developments in Monte Carlo methods, and more. Value at Risk will help professional risk managers understand, and operate within, today’s dynamic new risk environment.
          Hurlin, C., C. Perignon, "Value-at-Risk (Chapter 5: Computing VaR)", MacGraw-Hill, Third Edition.
          Authors: Jorion
          Coders: Hurlin
          Perignon
          Last update
          03/19/2012
          Ranking
          44
          Runs
          63
          Visits
          328

          Other Companion Sites on same paper

          The Risk Map: A New Tool for Validating Risk Models

          Other Companion Sites relative to similar papers

          Backtesting Value-at-Risk: From Dynamic Quantile to Dynamic Binary Tests
          Abstract
          In this paper we propose a new tool for backtesting that examines the quality of Value-at-Risk (VaR) forecasts. To date, the most distinguished regression-based backtest, proposed by Engle and Manganelli (2004), relies on a linear model. However, in view of the dichotomic character of the series of violations, a non-linear model seems more appropriate. In this paper we thus propose a new tool for backtesting (denoted DB) based on a dynamic binary regression model. Our discrete-choice model, e.g. Probit, Logit, links the sequence of violations to a set of explanatory variables including the lagged VaR and thelagged violations in particular. It allows us to separately test the unconditional coverage, the independence and the conditional coverage hypotheses and it is easy to implement. Monte-Carlo experiments show that the DB test exhibits good small sample properties in realistic sample settings (5% coverage rate with estimation risk). An application on a portfolio composed of three assets included in the CAC40 market index is finally proposed.
          Hurlin, C., and E. Dumitrescu, "Backtesting Value-at-Risk: From Dynamic Quantile to Dynamic Binary Tests", Finance, 33.
          Authors: Hurlin
          Pham
          Coders: Hurlin
          Dumitrescu
          Last update
          07/05/2012
          Ranking
          20
          Runs
          46
          Visits
          168
          Why Simple Shrinkage is Still Relevant for Redundant Representations?
          Abstract
          Shrinkage is a well known and appealing denoising technique, introduced originally by Donoho and Johnstone in 1994. The use of shrinkage for denoising is known to be optimal for Gaussian white noise, provided that the sparsity on the signal’s representation is enforced using a unitary transform. Still, shrinkage is also practiced with non-unitary, and even redundant representations, typically leading to very satisfactory results. In this paper we shed some light on this behavior. The main argument in this paper is that such simple shrinkage could be interpreted as the first iteration of an algorithm that solves the basis pursuit denoising (BPDN) problem. While the desired solution of BPDN is hard to obtain in general, we develop in this paper a simple iterative procedure for the BPDN minimization that amounts to step-wise shrinkage. We demonstrate how the simple shrinkage emerges as the first iteration of this novel algorithm. Furthermore, we show how shrinkage can be iterated, turning into an effective algorithm that minimizes the BPDN via simple shrinkage steps, in order to further strengthen the denoising effect.
          Elad, M., "Why Simple Shrinkage is Still Relevant for Redundant Representations?", IEEE Transactions on Information Theory , 52, 5559-5569.
          Authors: Elad
          Coders: Elad
          Last update
          07/06/2012
          Ranking
          28
          Runs
          4
          Visits
          30
          Backtesting Value-at-Risk: A GMM Duration-based Test
          Abstract
          This paper proposes a new duration-based backtesting procedure for VaR forecasts. The GMM test framework proposed by Bontemps (2006) to test for the distributional assumption (i.e. the geometric distribution) is applied to the case of the VaR forecasts validity. Using simple J-statistic based on the moments defined by the orthonormal polynomials associated with the geometric distribution, this new approach tackles most of the drawbacks usually associated to duration based backtesting procedures. First, its implementation is extremely easy. Second, it allows for a separate test for unconditional coverage, independence and conditional coverage hypothesis (Christoffersen, 1998). Third, Monte-Carlo simulations show that for realistic sample sizes, our GMM test outperforms traditional duration based test. Besides, we study the consequences of the estimation risk on the duration-based backtesting tests and propose a sub-sampling approach for robust inference derived from Escanciano and Olmo (2009). An empirical application for Nasdaq returns confirms that using GMM test leads to major consequences for the ex-post evaluation of the risk by regulation authorities.
          Colletaz, G., B. Candelon, C. Hurlin, and S. Tokpavi, "Backtesting Value-at-Risk: A GMM Duration-based Test", Journal of Financial Econometrics, 9(2), 314-343 .
          Authors: Candelon
          Colletaz
          Hurlin
          Tokpavi
          Coders: Colletaz
          Candelon
          Hurlin
          Tokpavi
          Last update
          06/28/2012
          Ranking
          55
          Runs
          23
          Visits
          291
          Prices and Asymptotics for Discrete Variance Swaps
          Abstract
          We derive closed-form expressions for the fair strike of a discrete variance swap for a general time-homogeneous stochastic volatility model. In the special cases of Heston and Hull-White stochastic volatility models we give simple explicit expressions (improving Broadie and Jain (2008a) for the Heston case). We give conditions on parameters under which the fair strike of a discrete variance swap is higher or lower than the continuous variance swap. Interest rates and correlation between underlying price and its volatility are key elements in this analysis. We derive asymptotics for the discrete variance swaps and compare our results with those of Broadie and Jain (2008a), Jarrow et al. (2012) and Keller-Ressel (2011).
          Bernard, C., and Z. Cui, "Prices and Asymptotics for Discrete Variance Swaps", SSRN.
          Authors: Bernard
          Cui
          Coders: Bernard
          Cui
          Last update
          11/22/2012
          Ranking
          N.A.
          Runs
          10
          Visits
          302
          A New Approach to Comparing VaR Estimation Methods
          Abstract
          We develop a novel backtesting framework based on multidimensional Value-at-Risk (VaR) that focuses on the left tail of the distribution of the bank trading revenues. Our coverage test is a multivariate generalization of the unconditional test of Kupiec (Journal of Derivatives, 1995). Applying our method to actual daily bank trading revenues, we find that non-parametric VaR methods, such as GARCH-based methods or filtered Historical Simulation, work best for bank trading revenues.
          Perignon, C., and D. Smith, C. Hurlin, "A New Approach to Comparing VaR Estimation Methods", Journal of Derivatives , 15, 54-66.
          Authors: Perignon
          Smith
          Coders: Perignon
          Smith
          Hurlin
          Last update
          07/16/2012
          Ranking
          54
          Runs
          11
          Visits
          270
          Structural Sign Patterns and Reduced Form Restrictions
          Abstract
          This paper reconsiders the degree to which the signpatterns of hypothesized structural arrays limit the possible outcomes for the signpattern of the corresponding estimated reducedform. The conditions under which any structuralrestrictions would apply were believed to be very narrow, rarely found to apply, and virtually never investigated. As a result, current practice does not test the structural hypothesis in terms of the comparison of the estimated reducedform and the permissible reducedformsignpatterns. This paper shows that such tests are always possible. Namely, that the signpatterns of the hypothesized structural arrays always limit the signpatterns that can be taken on by the estimated reducedform. Given this, it is always possible to falsify a structural hypothesis based only upon the signpattern proposed. Necessary conditions, algorithmic principles, and examples are provided to illustrate the analytic principle and the means of its application.
          Buck, J. A., and G. M. Lady, "Structural Sign Patterns and Reduced Form Restrictions", Economic Modelling, 29, 462-470.
          Authors: Buck
          Lady
          Coders: Buck
          Lady
          Last update
          07/18/2012
          Ranking
          23
          Runs
          N.A.
          Visits
          20
          Structural Models, Information and Inherited Restrictions
          Abstract
          The derived structural estimates of the system βY=γZ|δU impose identifying restrictions on the reduced form estimates ex post. Some or all of the derived structural estimates are presented as evidence of the model’s efficacy. In fact, the reduced form inherits a great deal of information from the structure’s restrictions and hypothesized sign patterns, limiting the allowable signs for the reduced form. A method for measuring a structural model’s statistical information content is proposed. Further, the paper develops a method for enumerating the allowable reduced form outcomes which can be used to falsify the proposed model independently of significant coefficients found for the structural relations.
          Buck, J. A., and G. M. Lady, "Structural Models, Information and Inherited Restrictions", Economic Modelling, 28, 2820-2831.
          Authors: Buck
          Lady
          Coders: Buck
          Lady
          Last update
          07/18/2012
          Ranking
          24
          Runs
          N.A.
          Visits
          28
          Asymptotic Distribution-Free Diagnostic Tests For Heteroskedastic Time Series
          Abstract
          This article investigates model checks for a class of possibly nonlinear heteroskedastic time series models, including but not restricted to ARMA-GARCH models. We propose omnibus tests based on functionals of certain weighted standardized residual empirical processes. The new tests are asymptotically distribution-free, suitable when the conditioning set is infinite-dimensional, and consistent against a class of Pitman’s local alternatives converging at the parametric rate n-1/2, with n the sample size. A Monte Carlo study shows that the simulated level of the proposed tests is close to the asymptotic level already for moderate sample sizes and that tests have a satisfactory power performance. Finally, we illustrate our methodology with an application to the well-known S&P 500 daily stock index. The paper also contains an asymptotic uniform expansion for weighted residual empirical processes when initial conditions are considered, a result of independent interest.
          Colletaz, G., "Asymptotic Distribution-Free Diagnostic Tests For Heteroskedastic Time Series", Econometric Theory, 26(03), 744-773.
          Authors: Escanciano
          Coders: Colletaz
          Last update
          12/06/2013
          Ranking
          18
          Runs
          39
          Visits
          218
          Volatility Forecast Comparison Using Imperfect Volatility Proxies
          Abstract
          The use of a conditionally unbiased, but imperfect, volatility proxy can lead to undesirable outcomes in standard methods for comparing conditional variance forecasts. We motivate our study with analytical results on the distortions caused by some widely used loss functions, when used with standard volatility proxies such as squared returns, the intra-daily range or realised volatility. We then derive necessary and sufficient conditions on the functional form of the loss function for the ranking of competing volatility forecasts to be robust to the presence of noise in the volatility proxy, and derive some useful special cases of this class of “robust” loss functions. The methods are illustrated with an application to the volatility of returns on IBM over the period 1993 to 2003.
          Patton, J. A., "Volatility Forecast Comparison Using Imperfect Volatility Proxies", Journal of Econometrics, 160, 246-256.
          Authors: Patton
          Coders: Patton
          Last update
          11/17/2012
          Ranking
          1
          Runs
          90
          Visits
          993
          The Best of Both Worlds: A Hybrid Approach to Calculating Value at Risk
          Abstract
          The hybrid approach combines the two most popular approaches to VaR estimation: RiskMetrics and Historical Simulation. It estimates the VaR of a portfolio by applying exponentially declining weights to past returns and then finding the appropriate percentile of this time-weighted empirical distribution. This new approach is very simple to implement. Empirical tests show a significant improvement in the precision of VaR forecasts using the hybrid approach relative to these popular approaches.
          Hurlin, C., C. Perignon, "The Best of Both Worlds: A Hybrid Approach to Calculating Value at Risk", Risk, 1, 64-67.
          Authors: Boudoukh
          Richardson
          Whitelaw
          Coders: Hurlin
          Perignon
          Last update
          07/17/2012
          Ranking
          52
          Runs
          4
          Visits
          67
          Competition and the Cost of Debt
          Abstract
          This paper empirically shows that the cost of bank debt is systematically higher for firms that operate in competitive product markets. Using various proxies for product market competition, and reductions of import tariff rates to capture exogenous changes to a firm's competitive environment, I find that competition has a significantly positive effect on the cost of bank debt. Moreover, the analysis reveals that the effect of competition is greater in industries in which small firms face financially strong rivals, in industries with intense strategic interactions between firms, and in illiquid industries. Overall, these findings suggest that banks price financial contracts by taking into account the risk that arises from product market competition.
          Valta, P., "Competition and the Cost of Debt", Journal of Financial Economics, 105.
          Authors: Valta
          Coders: Valta
          Last update
          08/16/2013
          Ranking
          27
          Runs
          N.A.
          Visits
          81
          Testing for Granger Causality in Heterogeneous Mixed Panels
          Abstract
          In this paper, we propose a simple Granger causality procedure based on Meta analysis in heterogeneous mixed panels. Firstly, we examine the finite sample properties of the causality test through Monte Carlo experiments for panels characterized by both cross-section independency and cross-section dependency. Then, we apply the procedure for investigating the export led growth hypothesis in a panel data of twenty OECD countries.
          Emirmahmutoglu, F., "Testing for Granger Causality in Heterogeneous Mixed Panels ", Economic Modelling, 28, 870-876.
          Authors: Emirmahmutoglu
          Kose
          Coders: Emirmahmutoglu
          Last update
          03/19/2013
          Ranking
          9999
          Runs
          N.A.
          Visits
          N.A.
          How to Forecast Long-Run Volatility: Regime Switching and the Estimation of Multifractal Processes
          Abstract
          We propose a discrete-time stochastic volatility model in which regime switching serves three purposes. First, changes in regimes capture low-frequency variations. Second, they specify intermediate-frequency dynamics usually assigned to smooth autoregressive transitions. Finally, high-frequency switches generate substantial outliers. Thus a single mechanism captures three features that are typically viewed as distinct in the literature. Maximum-likelihood estimation is developed and performs well in finite samples. Using exchange rates, we estimate a version of the process with four parameters and more than a thousand states. The multifractal outperforms GARCH, MS-GARCH, and FIGARCH in- and out-of-sample. Considerable gains in forecasting accuracy are obtained at horizons of 10 to 50 days.
          Calvet, E. L., and A. J. Fisher, "How to Forecast Long-Run Volatility: Regime Switching and the Estimation of Multifractal Processes", Journal of Financial Econometrics, 2, 49-83.
          Authors: Calvet
          Fisher
          Coders: Calvet
          Fisher
          Last update
          07/23/2012
          Ranking
          6
          Runs
          118
          Visits
          470
          Testing for Unit Roots in the Presence of Uncertainty Over Both the Trend and Initial Condition
          Abstract
          In this paper we provide a joint treatment of two major problems that surround testing for a unit root in practice: uncertainty as to whether or not a linear deterministic trend is present in the data, and uncertainty as to whether the initial condition of the process is (asymptotically) negligible or not. We suggest decision rules based on the union of rejections of four standard unit root tests (OLS and quasi-differenced demeaned and detrended ADF unit root tests), along with information regarding the magnitude of the trend and initial condition, to allow simultaneously for both trend and initial condition uncertainty.
          Colletaz, G., "Testing for Unit Roots in the Presence of Uncertainty Over Both the Trend and Initial Condition", Journal of Econometrics, 169, 188-95.
          Authors: Harvey
          Leybourne
          Taylor
          Coders: Colletaz
          Last update
          10/08/2012
          Ranking
          48
          Runs
          20
          Visits
          44
          Does Corporate Governance Predict Firms' Market Values? Evidence from Korea
          Abstract
          We report strong OLS and instrumental variable evidence that an overall corporate governance index is an important and likely causal factor in explaining the market value of Korean public companies. We construct a corporate governance index (KCGI, 0~100) for 515 Korean companies based on a 2001 Korea Stock Exchange survey. In OLS, a worst-to-best change in KCGIpredicts a 0.47 increase in Tobin's q (about a 160% increase in share price). This effect is statistically strong (t = 6.12) and robust to choice of market value variable (Tobin's q, market/book, and market/sales), specification of the governance index, and inclusion of extensive control variables. We rely on unique features of Korean legal rules to construct an instrument for KCGI. Good instruments are not available in other comparable studies. Two-stage and three-stage least squares coefficients are larger than OLS coefficients and are highly significant. Thus, this paper offers evidence consistent with a causal relationship between an overall governance index and higher share prices in emerging markets. We also find that Korean firms with 50% outside directors have 0.13 higher Tobin's q (roughly 40% higher share price), after controlling for the rest of KCGI. This effect, too, is likely causal. Thus, we report the first evidence consistent with greater board independence causally predicting higher share prices in emerging markets.
          Kim, W., B. S. Black , and H. Jang, "Does Corporate Governance Predict Firms' Market Values? Evidence from Korea", The Journal of Law, Economics, & Organization, 22, 366-413.
          Authors: Kim
          Black
          Jang
          Coders: Kim
          Black
          Jang
          Last update
          10/08/2012
          Ranking
          5
          Runs
          39
          Visits
          150
          Bartlett's Formula for a General Class of Non Linear Processes
          Abstract
          A Bartlett-type formula is proposed for the asymptotic distribution of the sample autocorrelations of nonlinear processes. The asymptotic covariances between sample autocorrelations are expressed as the sum of two terms. The first term corresponds to the standard Bartlett's formula for linear processes, involving only the autocorrelation function of the observed process. The second term, which is specific to nonlinear processes, involves the autocorrelation function of the observed process, the kurtosis of the linear innovation process and the autocorrelation function of its square. This formula is obtained under a symmetry assumption on the linear innovation process. It is illustrated on ARMA–GARCH models and compared to the standard formula. An empirical application on financial time series is proposed.
          Francq, C., and J. Zakoian, "Bartlett's Formula for a General Class of Non Linear Processes", Journal of Time Series Analysis, 30, 449-465.
          Authors: Francq
          Zakoian
          Coders: Francq
          Zakoian
          Last update
          07/23/2012
          Ranking
          8
          Runs
          65
          Visits
          522
          Forcasting Expected Shortfall with a Generalized Asymetric Student-t Distribution
          Abstract
          Financial returns typically display heavy tails and some skewness, and conditional variance models with these features often outperform more limited models. The difference in performance may be espe- cially important in estimating quantities that depend on tail features, including risk measures such as the expected shortfall. Here, using a recent generalization of the asymmetric Student-t distribution to allow separate parameters to control skewness and the thickness of each tail, we fit daily financial returns and forecast expected shortfall for the S&P 500 index and a number of individual company stocks; the generalized distribution is used for the standardized innovations in a nonlinear, asymmetric GARCH-type model. The results provide empirical evidence for the usefulness of the generalized distribution in improving prediction of downside market risk of financial assets.
          Galbraith, W. J., and D. Zhu, "Forcasting Expected Shortfall with a Generalized Asymetric Student-t Distribution", Centre interuniversitaire de recherche en analyse des organisations.
          Authors: Galbraith
          Zhu
          Coders: Galbraith
          Zhu
          Last update
          07/27/2012
          Ranking
          41
          Runs
          9
          Visits
          143
          Margin Backtesting
          Abstract
          This paper presents a validation framework for collateral requirements or margins on a derivatives exchange. It can be used by investors, risk managers, and regulators to check the accuracy of a margining system. The statistical tests presented in this study are based either on the number, frequency, magnitude, or timing of margin exceedances, which are de…ned as situations in which the trading loss of a market participant exceeds his or her margin. We also propose an original way to validate globally the margining system by aggregating individual backtesting statistics ob- tained for each market participant.
          Hurlin, C., and C. Perignon, "Margin Backtesting", University of Orleans, HEC Paris.
          Authors: Hurlin
          Perignon
          Coders: Hurlin
          Perignon
          Last update
          07/23/2014
          Ranking
          36
          Runs
          377
          Visits
          433
          Testing Interval Forecasts: A GMM-Based Approach
          Abstract
          This paper proposes a new evaluation framework of interval forecasts. Our model free test can be used to evaluate intervals forecasts and/or High Density Region, potentially discontinuous and/or asymmetric. Using simple J-statistic based on the moments defined by the orthonormal polynomials associated with the Binomial distribution, this new approach presents many advantages. First, its implementation is extremely easy. Second, it allows for a separate test for unconditional coverage, independence and conditional coverage hypothesis. Third, Monte-Carlo simulations show that for realistic sample sizes, our GMM test outperforms traditional LR test. These results are corroborated by an empirical application on SP500 and Nikkei stock market indexes. The empirical application for financial returns confirms that using a GMM test leads to major consequences for the ex-post evaluation of interval forecasts produced by linear versus non linear models.
          Dumitrescu, E., C. Hurlin, "Testing Interval Forecasts: A GMM-Based Approach", Journal of Forecasting, -.
          Authors: Dumitrescu
          Hurlin
          Madkour
          Coders: Dumitrescu
          Hurlin
          Last update
          06/05/2012
          Ranking
          10
          Runs
          29
          Visits
          340
          A Theoretical and Empirical Comparison of Systemic Risk Measures: MES versus CoVaR
          Abstract
          In this paper, we propose a theoretical and empirical comparison of two popular systemic risk measures - Marginal Expected Shortfall (MES) and Delta Conditional Value at Risk (ΔCoVaR) - that can be estimated using publicly available data. First, we assume that the time-varying correlation completely captures the dependence between firm and market returns. Under this assumption, we derive three analytical results: (i) we show that the MES corresponds to the product of the conditional ES of market returns and the time-varying beta of this institution, (ii) we give an analytical expression of the ΔCoVaR and show that the CoVaR corresponds to the product of the VaR of the firm's returns and the time-varying linear projection coefficient of the market returns on the firm's returns and (iii) we derive the ratio of the MES to the ΔCoVaR. Second, we relax this assumption and propose an empirical comparison for a panel of 61 US financial institutions over the period from January 2000 to December 2010. For each measure, we propose a cross-sectional analysis, a time-series comparison and rankings analysis of these institutions based on the two measures.
          Benoit, S., G. Colletaz, C. Hurlin, and C. Perignon, "A Theoretical and Empirical Comparison of Systemic Risk Measures: MES versus CoVaR", SSRN.
          Authors: Benoit
          Colletaz
          Hurlin
          Perignon
          Coders: Benoit
          Colletaz
          Hurlin
          Perignon
          Last update
          10/25/2012
          Ranking
          53
          Runs
          181
          Visits
          398
          Is Public Capital Really Productive? A Methodological Reappraisal
          Abstract
          We present an evaluation of the main empirical approaches used in the literature to estimate the contribution of public capital stock to growth and private factors' productivity. Based on a simple stochastic general equilibrium model, built as to reproduce the main long-run relations observed in US post-war historical data, we show that the production function approach may not be reliable to estimate this contribution. Our analysis reveals that this approach largely overestimates the public capital elasticity, given the presence of a common stochastic trend shared by all non-stationary inputs.
          Minea, A., and C. Hurlin, "Is Public Capital Really Productive? A Methodological Reappraisal", University of Orleans.
          Authors: Minea
          Hurlin
          Coders: Minea
          Hurlin
          Last update
          09/10/2012
          Ranking
          43
          Runs
          3
          Visits
          42
          Are Public Investment Efficient in Creating Capital Stocks in Developing Countries? Estimates of Government Net Capital Stocks for 26 Developing Countries, 1970-2002
          Abstract
          In many poor countries, the problem is not that governments do not invest, but that these investments do not create productive capital. So, the cost of public investments does not correspond to the value of the capital stocks. In this paper, we propose an original non parametric approach to evaluate the efficiency function that links variations (net of depreciation) of stocks to public investments. We consider four sectors (electricity, telecommunications, roads and railways) of two Latin American countries (Mexico and Colombia). We show that there is a large discrepancy between the amount of investments and the value of increases in stocks.
          Arestoff, F., and C. Hurlin, "Are Public Investment Efficient in Creating Capital Stocks in Developing Countries? Estimates of Government Net Capital Stocks for 26 Developing Countries, 1970-2002 ", Economics Bulletin, 30, 1515-1531.
          Authors: Arestoff
          Hurlin
          Coders: Arestoff
          Hurlin
          Last update
          10/08/2012
          Ranking
          11
          Runs
          N.A.
          Visits
          26
          Testing for Granger Non-causality in Heterogeneous Panels
          Abstract
          This paper proposes a very simple test of Granger (1969) non-causality for hetero- geneous panel data models. Our test statistic is based on the individual Wald statistics of Granger non causality averaged across the cross-section units. First, this statistic is shown to converge sequentially to a standard normal distribution. Second, the semi- asymptotic distribution of the average statistic is characterized for a fixed T sample. A standardized statistic based on an approximation of the moments of Wald statistics is hence proposed. Third, Monte Carlo experiments show that our standardized panel statistics have very good small sample properties, even in the presence of cross-sectional dependence.
          Dumitrescu, E., and C. Hurlin, "Testing for Granger Non-causality in Heterogeneous Panels", Economic Modelling, Forthcoming.
          Authors: Dumitrescu
          Hurlin
          Coders: Dumitrescu
          Hurlin
          Last update
          07/12/2017
          Ranking
          40
          Runs
          451
          Visits
          502
          Monotonicity in Asset Returns: New Tests with Applications to the Term Structure, the CAPM, and Portfolio Sorts
          Abstract
          Many theories in finance imply monotonic patterns in expected returns and other financial variables. The liquidity preference hypothesis predicts higher expected returns for bonds with longer times to maturity; the Capital Asset Pricing Model(CAPM)implies higher expected returns for stocks with higher betas; and standard asset pricing models imply that the pricing kernel is declining in market returns. The full set of implications of monotonicity is generally not exploited in empirical work, however. This paper proposes new and simple ways to test for monotonicity in financial variables and compares the proposed tests with extant alternatives such as t-tests, Bonferroni bounds, and multivariate inequality tests through empirical applications and simulations.
          Patton, J. A., and A. Timmermann, "Monotonicity in Asset Returns: New Tests with Applications to the Term Structure, the CAPM, and Portfolio Sorts", Journal of Financial Economics, 98, 605-625.
          Authors: Patton
          Timmermann
          Coders: Patton
          Timmermann
          Last update
          11/17/2012
          Ranking
          63
          Runs
          19
          Visits
          116
          Maximum Likelihood Estimation of Discretely Sampled Diffusions: A Closed-Form Approximation Approach
          Abstract
          When a continuous-time diffusion is observed only at discrete dates, in most cases the transition distribution and hence the likelihood function of the observation is not explicitely computable. Using Hermite polynomials, I construct an explicit sequences of closed-form functions and show that it converges to the true (but unknown) likelihood function. I document that the approximation is very accurate and prove that maximizing the sequence results in an estimator that converges to the true maximum likelihood estimator and shares its asymptotic properties. Monte Carlo evidence reveals that this method outperforms other approximation schemes in situations relevant for financial models.
          Aït-Sahalia, Y., "Maximum Likelihood Estimation of Discretely Sampled Diffusions: A Closed-Form Approximation Approach", Econometrica, 70, 223-262.
          Authors: Aït-Sahalia
          Coders: Aït-Sahalia
          Last update
          10/29/2014
          Ranking
          2
          Runs
          119
          Visits
          621
          Adaptive Estimation of Vector Autoregressive Models with Time-Varying Variance: Application to Testing Linear Causality in Mean
          Abstract
          Linear Vector AutoRegressive (VAR) models where the innovations could be unconditionally heteroscedastic and serially dependent are considered. The volatility structure is deterministic and quite general, including breaks or trending variances as special cases. In this framework we propose Ordinary Least Squares (OLS), Generalized Least Squares (GLS) and Adaptive Least Squares (ALS) procedures. The GLS estimator requires the knowledge of the time-varying variance structure while in the ALS approach the unknown variance is estimated by kernel smoothing with the outer product of the OLS residuals vectors. Different bandwidths for the different cells of the time-varying variance matrix are also allowed. We derive the asymptotic distribution of the proposed estimators for the VAR model coefficients and compare their properties. In particular we show that the ALS estimator is asymptotically equivalent to the infeasible GLS estimator. This asymptotic equivalence is obtained uniformly with respect to the bandwidth(s) in a given range and hence justifies data-driven bandwidth rules. Using these results we build Wald tests for the linear Granger causality in mean which are adapted to VAR processes driven by errors with a non stationary volatility. It is also shown that the commonly used standard Wald test for the linear Granger causality in mean is potentially unreliable in our framework (incorrect level and lower asymptotic power). Monte Carlo and real-data experiments illustrate the use of the different estimation approaches for the analysis of VAR models with time-varying variance innovations.
          Raïssi, H., "Adaptive Estimation of Vector Autoregressive Models with Time-Varying Variance: Application to Testing Linear Causality in Mean", IRMAR-INSA and CREST ENSAI.
          Authors: Patilea
          Coders: Raïssi
          Last update
          10/08/2012
          Ranking
          58
          Runs
          9
          Visits
          169
          Copula-Based Models for Financial Time Series
          Abstract
          This paper presents an overview of the literature on applications of copulas in the modelling of financial time series. Copulas have been used both in multivariate time series analysis, where they are used to charaterise the (conditional) cross-sectional dependence between individual time series, and in univariate time series analysis, where they are used to characterise the dependence between a sequence of observations of a scalar time series process. The paper includes a broad, brief, review of the many applications of copulas in finance and economics.
          Patton, J. A., "Copula-Based Models for Financial Time Series", Handbook of Financial Time Series, Springer Verlag, -.
          Authors: Patton
          Coders: Patton
          Last update
          10/08/2012
          Ranking
          3
          Runs
          38
          Visits
          572
          Mixed Logit with Repeated Choices: Households' Choices of Appliance Efficiency Level
          Abstract
          Mixed logit models, also called random-parameters or error-components logit, are a generalization of standard logit that do not exhibit the restrictive "independence from irrelevant alternatives" property and explicitly account for correlations in unobserved utility over repeated choices by each customer. Mixed logits are estimated for households’ choices of appliances under utility-sponsored programs that offer rebates or loans on high-efficiency appliances.
          Train, K., "Mixed Logit with Repeated Choices: Households' Choices of Appliance Efficiency Level", The Review of Economics and Statistics, 80, 647-657.
          Authors: Revelt
          Train
          Coders: Train
          Last update
          06/05/2012
          Ranking
          7
          Runs
          6
          Visits
          243
          Network Effects and Infrastructure Productivity in Developing Countries
          Abstract
          This paper proposes to investigate the threshold effects of the productivity of infrastructure investment in developing countries within a panel data framework. Various speci.cations of an augmented production function that allow for endogenous thresholds are considered. The overwhelming outcome is the presence of strong threshold effects in the relationship between output and private and public inputs. Whatever the transition mechanism used, the testing procedures lead to strong rejection of the linearity of this relationship. In particular, the productivity of infrastructure investment generally exhibits some network effects. When the available stock of infrastructure is very low, investment in this sector has the same productivity as non-infrastructure investment. On the contrary, when a minimumnetwork is available, the marginal productivity of infrastructure investment is generally largely greater than the productivity of other investments. Finally, when the main network is achieved, its marginal productivity becomes similar to the productivity of other investment.
          Candelon, B., G. Colletaz, and C. Hurlin, "Network Effects and Infrastructure Productivity in Developing Countries", Maastricht University.
          Authors: Candelon
          Colletaz
          Hurlin
          Coders: Candelon
          Colletaz
          Hurlin
          Last update
          03/14/2013
          Ranking
          35
          Runs
          414
          Visits
          431
          Threshold Effects of the Public Capital Productivity : An International Panel Smooth Transition Approach
          Abstract
          Using a non linear panel data model we examine the threshold effects in the productivity of the public capital stocks for a panel of 21 OECD countries observed over 1965-2001. Using the so-called "augmented production function" approach, we estimate various specifications of a Panel Smooth Threshold Regression (PSTR) model recently developed by Gonzalez, Teräsvirta and Van Dijk (2004). One of our main results is the existence of strong threshold effects in the relationship between output and private and public inputs : whatever the transition mechanism specified, tests strongly reject the linearity assumption. Moreover this model allows cross-country heterogeneity and time instability of the productivity without specification of an ex-ante classification over individuals. Consequently it is posible to give estimates of productivity coefficients for both private and public capital stocks at any time and for each countries in the sample. Finally we proposed estimates of individual time varying elasticities that are much more reasonable than those previously published.
          Hurlin, C., "Threshold Effects of the Public Capital Productivity : An International Panel Smooth Transition Approach", University of Orléans.
          Authors: Colletaz
          Hurlin
          Coders: Hurlin
          Last update
          07/22/2014
          Ranking
          31
          Runs
          2290
          Visits
          677
          Evaluating Interval Forecasts
          Abstract
          A complete theory for evaluating interval forecasts has not been worked out to date. Most of the literature implicitly assumes homoskedastic errors even when this is clearly violated and proceed by merely testing for correct unconditional coverage. Consequently, the author sets out to build a consistent framework for conditional interval forecast evaluation, which is crucial when higher-order moment dynamics are present. The new methodology is demonstrated in an application to the exchange rate forecasting procedures advocated in risk management.
          Hurlin, C., C. Perignon, "Evaluating Interval Forecasts", International Economic Review, 39, 841-862.
          Authors: Christoffersen
          Coders: Hurlin
          Perignon
          Last update
          03/09/2012
          Ranking
          32
          Runs
          57
          Visits
          167
          Backtesting Value-at-Risk: A Duration-Based Approach
          Abstract
          Financial risk model evaluation or backtesting is a key part of the internal model’s approach to market risk management as laid out by the Basle Committee on Banking Supervision. However, existing backtesting methods have relatively low power in realistic small sample settings. Our contribution is the exploration of new tools for backtesting based on the duration of days between the violations of the Value-at-Risk. Our Monte Carlo results show that in realistic situations, the new duration-based tests have considerably better power properties than the previously suggested tests.
          Hurlin, C., and C. Perignon, "Backtesting Value-at-Risk: A Duration-Based Approach", Journal of Financial Econometrics, 2, 84-108.
          Authors: Pelletier
          Christoffersen
          Coders: Hurlin
          Perignon
          Last update
          07/23/2012
          Ranking
          26
          Runs
          17
          Visits
          207
          Backtesting Value-at-Risk Accuracy: A Simple New Test
          Abstract
          This paper proposes a new test of value-at-risk (VAR) validation. Our test exploits the idea that the sequence of VAR violations (hit function) – taking value 1 - α if there is a violation, and -α otherwise – for a nominal coverage rate α verifies the properties of a martingale difference if the model used to quantify risk is adequate (Berkowitz et al., 2005). More precisely, we use the multivariate portmanteau statistic of Li and McLeod (1981), an extension to the multivariate framework of the test of Box and Pierce (1970), to jointly test the absence of autocorrelation in the vector of hit sequences for various coverage rates considered relevant for the management of extreme risks. We show that this shift to a multivariate dimension appreciably improves the power properties of the VAR validation test for reasonable sample sizes.
          Hurlin, C., and S. Tokpavi, "Backtesting Value-at-Risk Accuracy: A Simple New Test", Journal of Risk, 9, 19-37.
          Authors: Hurlin
          Tokpavi
          Coders: Hurlin
          Tokpavi
          Last update
          03/13/2012
          Ranking
          49
          Runs
          2
          Visits
          240
          How To Evaluate an Early Warning System? Towards a unified Statistical Framework for Assessing Financial Crises Forecasting Methods
          Abstract
          This paper proposes an original and unified toolbox to evaluate financial crisis Early Warning Systems (EWS). It presents four main advantages. First, it is a model-free method which can be used to asses the forecasts issued from different EWS (probit, logit, markov switching models, or combinations of models). Second, this toolbox can be applied to any type of crisis EWS (currency, banking, sovereign debt, etc.). Third, it does not only provide various criteria to evaluate the (absolute) validity of EWS forecasts but also proposes some tests to compare the relative performance of alternative EWS. Fourth, our toolbox can be used to evaluate both in-sample and out-of-sample forecasts. Applied to a logit model for twelve emerging countries we show that the yield spread is a key variable for predicting currency crises exclusively for South-Asian countries. Besides, the optimal cut-off correctly allows us to identify now on average more than 2/3 of the crisis and calm periods.
          Candelon, B., E. Dumitrescu, and C. Hurlin, "How To Evaluate an Early Warning System? Towards a unified Statistical Framework for Assessing Financial Crises Forecasting Methods", IMF Economic Review, 60.
          Authors: Candelon
          Dumitrescu
          Hurlin
          Coders: Candelon
          Dumitrescu
          Hurlin
          Last update
          07/23/2012
          Ranking
          34
          Runs
          24
          Visits
          269
          Forecasting Realized Volatility Using a Nonnegative Semiparametric Model
          Abstract
          This paper introduces a parsimonious and yet exible nonnegative semi-parametric model to forecast financial volatility. The new model extends the linear nonnegative autoregressive model of Barndor-Nielsen & Shephard (2001) and Nielsen & Shephard (2003) by way of a power transformation. It is semiparametric in the sense that the distributional form of its error component is left unspecified. The statistical properties of the model are discussed and a novel estimation method is proposed. Asymptotic properties are established for the new estimation method. Simulation studies validate the new estimation method. The out-of-sample performance of the proposed model is evaluated against a number of standard methods, using data on S&P 500 monthly realized volatilities. The competing models include the exponential smoothing method, a linear AR(1) model, a log-linear AR(1) model, and two long-memory ARFIMA models. Various loss functions are utilized to evaluate the predictive accuracy of the alternative methods. It is found that the new model generally produces highly competitive forecasts.
          Preve, D., J. Yu, "Forecasting Realized Volatility Using a Nonnegative Semiparametric Model", Uppsala University.
          Authors: Eriksson
          Preve
          Yu
          Coders: Preve
          Yu
          Last update
          06/06/2012
          Ranking
          64
          Runs
          19
          Visits
          114
          Mixed Logit with Bounded Distributions of Correlated Partworths
          Abstract
          The use of a joint normal distribution for partworths is computationally attractive, particularly with Bayesian MCMC procedures, and yet is unrealistic for any attribute whose partworth is logically bounded (e.g., is necessarily positive or cannot be unboundedly large). A mixed logit is specified with partworths that are transformations of normally distributed terms, where the transformation induces bounds; examples include censored normals, log-normals, and SB distributions which are bounded on both sides. The model retains the computational advantages of joint normals while providing greater flexibility for the distributions of correlated partworths. The method is applied to data on customers’ choice among vehicles in stated choice experiments. The flexibility that the transformations allow is found to greatly improve the model, both in terms of fit and plausibility, without appreciably increasing the computational burden.
          Train, K., "Mixed Logit with Bounded Distributions of Correlated Partworths ", Applications of Simulation Methods in Environmental Resource Economics , Chapter 7.
          Authors: Sonnier
          Train
          Coders: Train
          Last update
          07/10/2012
          Ranking
          4
          Runs
          9
          Visits
          268
          Value-at-Risk (Chapter 7: Portfolio Risk - Analytical Methods)
          Abstract
          Book description: To accommodate sweeping global economic changes, the risk management field has evolved substantially since the first edition of Value at Risk, making this revised edition a must. Updates include a new chapter on liquidity risk, information on the latest risk instruments and the expanded derivatives market, recent developments in Monte Carlo methods, and more. Value at Risk, Second Edition, will help professional risk managers understand, and operate within, today’s dynamic new risk environment.
          Hurlin, C., C. Perignon, "Value-at-Risk (Chapter 7: Portfolio Risk - Analytical Methods)", McGraw-Hill, Second edition.
          Authors: Jorion
          Coders: Hurlin
          Perignon
          Last update
          03/16/2012
          Ranking
          33
          Runs
          9
          Visits
          303
          Value-at-Risk (Chapter 5: Computing VaR)
          Abstract
          Book description: To accommodate sweeping global economic changes, the risk management field has evolved substantially since the first edition of Value at Risk, making this revised edition a must. Updates include a new chapter on liquidity risk, information on the latest risk instruments and the expanded derivatives market, recent developments in Monte Carlo methods, and more. Value at Risk will help professional risk managers understand, and operate within, today’s dynamic new risk environment.
          Hurlin, C., C. Perignon, "Value-at-Risk (Chapter 5: Computing VaR)", MacGraw-Hill, Third Edition.
          Authors: Jorion
          Coders: Hurlin
          Perignon
          Last update
          03/19/2012
          Ranking
          44
          Runs
          63
          Visits
          328
          The pernicious effects of contaminated data in risk management
          Abstract
          Banks hold capital to guard against unexpected surges in losses and long freezes in financial markets. The minimum level of capital is set by banking regulators as a function of the banks’ own estimates of their risk exposures. As a result, a great challenge for both banks and regulators is to validate internal risk models. We show that a large fraction of US and international banks uses contaminated data when testing their models. In particular, most banks validate their market risk model using profit-and-loss (P/L) data that include fees and commissions and intraday trading revenues. This practice is inconsistent with the definition of the employed market risk measure. Using both bank data and simulations, we find that data contamination has dramatic implications for model validation and can lead to the acceptance of misspecified risk models. Moreover, our estimates suggest that the use of contaminated data can significantly reduce (market-risk induced) regulatory capital.
          Fresard, L., C. Perignon, and A. Wilhelmsson, "The pernicious effects of contaminated data in risk management", Journal of Banking and Finance, 35.
          Authors: Fresard
          Perignon
          Wilhelmsson
          Coders: Fresard
          Perignon
          Wilhelmsson
          Last update
          11/23/2012
          Ranking
          9999
          Runs
          N.A.
          Visits
          42
          Techniques for Verifying the Accuracy of Risk Management Models
          Abstract
          Risk exposures are typically quantified in terms of a "Value at Risk" (VaR) estimate. A VaR estimate corresponds to a specific critical value of a portfolio's potential one-day profit and loss probability distribution. Given their function both as internal risk management tools and as potential regulatory measures of risk exposure, it is important to quantify the accuracy of an institution's VaR estimates. This study shows that the formal statistical procedures that would typically be used in performance-based VaR verification tests require large samples to produce a reliable assessment of a model's accuracy in predicting the size and likelihood of very low probability events. Verification test statistics based on historical trading profits and losses have very poor power in small samples, so it does not appear possible for a bank or its supervisor to verify the accuracy of a VaR estimate unless many years of performance data are available. Historical simulation-based verification test statistics also require long samples to generate accurate results: Estimates of 0.01 critical values exhibit substantial errors even in samples as large as ten years of daily data.
          Hurlin, C., C. Perignon, "Techniques for Verifying the Accuracy of Risk Management Models", Journal of Derivatives, 3, 73-84.
          Authors: Kupiec
          Coders: Hurlin
          Perignon
          Last update
          04/17/2012
          Ranking
          57
          Runs
          26
          Visits
          339
          Diversification and Value-at-Risk
          Abstract
          A pervasive and puzzling feature of banks’ Value-at-Risk (VaR) is its abnormally high level, which leads to excessive regulatory capital. A possible explanation for the tendency of commercial banks to overstate their VaR is that they incompletely account for the diversification effect among broad risk categories (e.g., equity, interest rate, commodity, credit spread, and foreign exchange). By underestimating the diversification effect, bank’s proprietary VaR models produce overly prudent market risk assessments. In this paper, we examine empirically the validity of this hypothesis using actual VaR data from major US commercial banks. In contrast to the VaR diversification hypothesis, we find that US banks show no sign of systematic underestimation of the diversification effect. In particular, diversification effects used by banks is very close to (and quite often larger than) our empirical diversification estimates. A direct implication of this finding is that individual VaRs for each broad risk category, just like aggregate VaRs, are biased risk assessments.
          Perignon, C., and D. Smith, "Diversification and Value-at-Risk", Journal of Banking and Finance, 34.
          Authors: Perignon
          Smith
          Coders: Perignon
          Smith
          Last update
          11/23/2012
          Ranking
          9999
          Runs
          N.A.
          Visits
          45
          Outliers and GARCH Models in Financial Data
          Abstract
          We propose to extend the additive outlier (AO) identification procedure developed by Franses and Ghijsels(Franses, P.H., Ghijsels, H., 1999. Additive outliers, GARCH and forecasting volatility. International Journal of Forecasting, 15, 1–9) to take into account the innovative outliers (IOs) in a GARCH model. We apply it to three daily stock market indexes and examine the effects of outliers on the diagnostics of normality.
          Charles, A., and O. Darné, D. Banulescu, E. Dumitrescu, "Outliers and GARCH Models in Financial Data", Economics Letters, 86, 347-352.
          Authors: Charles
          Darné
          Coders: Charles
          Darné
          Banulescu
          Dumitrescu
          Last update
          06/22/2012
          Ranking
          15
          Runs
          61
          Visits
          238
          The level and quality of Value-at-Risk disclosure by commercial banks
          Abstract
          In this paper we study both the level of Value-at-Risk (VaR) disclosure and the accuracy of the disclosed VaR figures for a sample of US and international commercial banks. To measure the level of VaR disclosures, we develop a VaR Disclosure Index that captures many different facets of market risk disclosure. Using panel data over the period 1996–2005, we find an overall upward trend in the quantity of information released to the public. We also find that Historical Simulation is by far the most popular VaR method. We assess the accuracy of VaR figures by studying the number of VaR exceedances and whether actual daily VaRs contain information about the volatility of subsequent trading revenues. Unlike the level of VaR disclosure, the quality of VaR disclosure shows no sign of improvement over time. We find that VaR computed using Historical Simulation contains very little information about future volatility.
          Perignon, C., and D. Smith, "The level and quality of Value-at-Risk disclosure by commercial banks", Journal of Banking and Finance, 34.
          Authors: Perignon
          Smith
          Coders: Perignon
          Smith
          Last update
          11/23/2012
          Ranking
          9999
          Runs
          N.A.
          Visits
          25
          Extracting Factors from Heteroskedastic Asset Returns
          Abstract
          This paper proposes an alternative to the asymptotic principal components procedure of Connor and Korajczyk (Journal of Financial Economics, 1986) that is robust to time series heteroskedasticity in the factor model residuals. The new method is simple to use and requires no assumptions stronger than those made by Connor and Korajczyk. It is demonstrated through simulations and analysis of actual stock market data that allowing heteroskedasticity sometimes improves the quality of the extracted factors quite dramatically. Over the period from 1989 to 1993, for example, a single factor extracted using the Connor and Korajczyk method explains only 8.2% of the variation of the CRSP value-weighted index, while the factor extracted allowing heteroskedasticity explains 57.3%. Accounting for heteroskedasticity is also important for tests of the APT, with p-values sometimes depending strongly on the factor extraction method used.
          Jones, S. C., "Extracting Factors from Heteroskedastic Asset Returns", Journal of Financial Economics, 62, 293-325.
          Authors: Jones
          Coders: Jones
          Last update
          11/17/2012
          Ranking
          30
          Runs
          17
          Visits
          81
          A New Approach to Comparing VaR Estimation Methods
          Abstract
          We develop a novel backtesting framework based on multidimensional Value-at-Risk (VaR) that focuses on the left tail of the distribution of the bank trading revenues. Our coverage test is a multivariate generalization of the unconditional test of Kupiec (Journal of Derivatives, 1995). Applying our method to actual daily bank trading revenues, we find that non-parametric VaR methods, such as GARCH-based methods or filtered Historical Simulation, work best for bank trading revenues.
          Perignon, C., and D. Smith, "A New Approach to Comparing VaR Estimation Methods", Journal of Derivatives, Winter.
          Authors: Smith
          Perignon
          Coders: Perignon
          Smith
          Last update
          11/23/2012
          Ranking
          9999
          Runs
          N.A.
          Visits
          43
          Currency Crises Early Warning Systems: why they should be Dynamic
          Abstract
          This paper introduces a new generation of Early Warning Systems (EWS) which takes into account the dynamics, i.e. the persistence in the binary crisis indicator. We elaborate on Kauppi and Saikonnen (2008), which allows to consider several dynamic specifications by re- lying on an exact maximum likelihood estimation method. Applied so as to predict currency crises for fifteen countries, this new EWS turns out to exhibit significantly better predic- tive abilities than the existing models both within and out of the sample, thus vindicating dynamic models in the quest for optimal EWS.
          Candelon, B., E. Dumitrescu, and C. Hurlin, "Currency Crises Early Warning Systems: why they should be Dynamic", Maastricht University.
          Authors: Candelon
          Dumitrescu
          Hurlin
          Coders: Candelon
          Dumitrescu
          Hurlin
          Last update
          06/04/2012
          Ranking
          45
          Runs
          64
          Visits
          112
          Modeling State Credit Risks in Illinois and Indiana
          Abstract
          I use an open-source budget-simulation model to evaluate Illinois’s credit risk and to compare it to that of Indiana, a neighboring state generally believed to have better fiscal management. Based on a review of the history and theory of state credit performance, I assume that a state will default if the aggregate of its interest and pension costs reaches 30 percent of total revenues. In Illinois, this ratio is currently 10 percent, compared to 4 percent in Indiana. My analysis finds that neither state will reach the critical threshold in the next few years under any reasonable economic scenario, suggesting no material default risk. Over the longer term, Illinois has some chance of reaching the default threshold, but it would likely be able to take policy actions to lower the ratio before then. If market participants accept my finding that Illinois does not have material default risk, Illinois’s bond yields willfall, yielding cost savings for taxpayers as the state rolls over its debt.
          Joffe, D. M., "Modeling State Credit Risks in Illinois and Indiana", Mercatus Center.
          Authors: Joffe
          Coders: Joffe
          Last update
          08/01/2013
          Ranking
          9999
          Runs
          N.A.
          Visits
          N.A.
          Pitfalls in backtesting Historical Simulation VaR models
          Abstract
          Abstract Historical Simulation (HS) and its variant, the Filtered Historical Simulation (FHS), are the most popular Value-at-Risk forecast methods at commercial banks. These forecast methods are traditionally evaluated by means of the unconditional backtest. This paper formally shows that the unconditional backtest is always inconsistent for backtesting HS and FHS models, with a power function that can be even smaller than the nominal level in large samples. Our findings have fundamental implications in the determination of market risk capital requirements, and also explain Monte Carlo and empirical findings in previous studies. We also propose a data-driven weighted backtest with good power properties to evaluate HS and FHS forecasts. A Monte Carlo study and an empirical application with three US stocks confirm our theoretical findings. The empirical application shows that multiplication factors computed under the current regulatory framework are downward biased, as they inherit the inconsistency of the unconditional backtest.
          Escanciano, J., and P. Pei, "Pitfalls in backtesting Historical Simulation VaR models", Journal of Banking and Finance, 36, 2233-2244.
          Authors: Escanciano
          Pei
          Coders: Escanciano
          Pei
          Last update
          02/22/2013
          Ranking
          9999
          Runs
          N.A.
          Visits
          32
          A Generalized Asymmetric Student-t Distribution with Application to Financial Econometrics
          Abstract
          This paper proposes a new class of asymmetric Student-t (AST) distributions, and investigates its properties, gives procedures for estimation, and indicates applications in financial econometrics. We derive analytical expressions for the cdf, quantile function, moments, and quantities useful in financial econometric applications such as the Expected Shortfall. A stochastic representation of the distribution is also given. Although the AST density does not satisfy the usual regularity conditions for maximum likelihood estimation, we establish consistency, asymptotic normality and efficiency of ML estimators and derive an explicit analytical expression for the asymptotic covariance matrix. A Monte Carlo study indicates generally good finite-sample conformity with these asymptotic properties.
          Colletaz, G., "A Generalized Asymmetric Student-t Distribution with Application to Financial Econometrics", Journal of Econometrics, 157, 297-305.
          Authors: Zhu
          Galbraith
          Coders: Colletaz
          Last update
          05/05/2012
          Ranking
          38
          Runs
          6
          Visits
          95
          Determining the Number of Factors in Approximate Factors Models
          Abstract
          In this paper we develop some econometric theory for factor models of large dimensions. The focus is the determination of the number of factors (r), which is an unresolved issue in the rapidly growing literature on multifactor models. We first establish the convergence rate for the factor estimates that will allow for consistent estimation of r. We then propose some panel criteria and show that the number of factors can be consistently estimated using the criteria. The theory is developed under the framework of large cross-sections (N) and large time dimensions (T). No restriction is imposed on the relation between N and T. Simulations show that the proposed criteria have good finite sample properties in many configurations of the panel data encountered in practice.
          Hurlin, C., "Determining the Number of Factors in Approximate Factors Models", Econometrica, 70, 191-221.
          Authors: Bai
          Ng
          Coders: Hurlin
          Last update
          01/29/2013
          Ranking
          39
          Runs
          66
          Visits
          230
          Unit Root Tests in Panel Data: Asymptotic and Finite-Sample Properties
          Abstract
          We consider pooling cross-section time series data for testing the unit root hypothesis. The degree of persistence in individual regression error, the intercept and trend coefficient are allowed to vary freely across individuals. As both the cross-section and time series dimensions of the panel grow large, the pooled t-statistic has a limiting normal distribution that depends on the regression specification but is free from nuisance parameters. Monte Carlo simulations indicate that the asymptotic results provide a good approximation to the test statistics in panels of moderate size, and that the power of the panel-based unit root test is dramatically higher, compared to performing a separate unitroottest for each individual time series.
          Hurlin, C., "Unit Root Tests in Panel Data: Asymptotic and Finite-Sample Properties", Journal of Econometrics, 108, 1-24.
          Authors: Levin
          Lin
          Chu
          Coders: Hurlin
          Last update
          06/28/2012
          Ranking
          37
          Runs
          220
          Visits
          322
          Maximum Likelihood Methods for Models of Markets in Disequilibrium
          Abstract
          For the abstract, please click on: http://www.jstor.org/discover/10.2307/1914215?uid=3738016&uid=2&uid=4&sid=56146953873
          Hurlin, C., "Maximum Likelihood Methods for Models of Markets in Disequilibrium", Econometrica, 42, 1013-1030.
          Authors: Maddala
          Nelson
          Coders: Hurlin
          Last update
          02/15/2013
          Ranking
          50
          Runs
          85
          Visits
          391
          A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test
          Abstract
          The panel data unit root test suggested by Levin and Lin (LL) has been widely used in several applications, notably in papers on tests of the purchasing power parity hypothesis. This test is based on a very restrictive hypothesis which is rarely ever of interest in practice. The Im–Pesaran–Shin (IPS) test relaxes the restrictive assumption of the LL test. This paper argues that although the IPS test has been offered as a generalization of the LL test, it is best viewed as a test for summarizing the evidence from a number of independent tests of the sample hypothesis. This problem has a long statistical history going back to R. A. Fisher. This paper suggests the Fisher test as a panel data unit root test, compares it with the LL and IPS tests, and the Bonferroni bounds test which is valid for correlated tests. Overall, the evidence points to the Fisher test with bootstrap-based critical values as the preferred choice. We also suggest the use of the Fisher test for testing stationarity as the null and also in testing for cointegration in panel data.
          Hurlin, C., "A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test", Oxford Bulletin of Economics and Statistics, 61, 631-652.
          Authors: Maddala
          Wu
          Coders: Hurlin
          Last update
          10/08/2012
          Ranking
          59
          Runs
          217
          Visits
          129
          Unit Root Tests for Panel Data
          Abstract
          This paper develops unit root tests for panel data. These tests are devised under more general assumptions than the tests previously proposed. First, the number of groups in the panel data is assumed to be either finite or infinite. Second, each group is assumed to have different types of nonstochastic and stochastic components. Third, the time series spans for the groups are assumed to be all different. Fourth, the alternative where some groups have a unit root and others do not can be dealt with by the tests. The tests can also be used for the null of stationarity and for cointegration, once relevant changes are made in the model, hypotheses, assumptions and underlying tests. The main idea for our unit root tests is to combine p-values from a unit root test applied to each group in the panel data. Combining p-values to formulate tests is a common practice in meta-analysis. This paper also reports the finite sample performance of our combination unit root tests and Im et al.'s [Mimeo (1995)] t-bar test. The results show that most of the combination tests are more powerful than the t-bar test in finite samples. Application of the combination unit root tests to the post-Bretton Woods US real exchange rate data provides some evidence in favor of the PPP hypothesis.
          Hurlin, C., "Unit Root Tests for Panel Data", Journal of International Money and Finance, 20, 249-272.
          Authors: Choi
          Coders: Hurlin
          Last update
          10/08/2012
          Ranking
          60
          Runs
          62
          Visits
          261
          Testing for Unit Roots in Heterogeneous Panels
          Abstract
          This paper proposes unit root tests for dynamic heterogeneous panels based on the mean of individual unit root statistics. In particular it proposes a standardized t-bar test statistic based on the (augmented) Dickey–Fuller statistics averaged across the groups. Under a general setting this statistic is shown to converge in probability to a standard normal variate sequentially with T (the time series dimension) →∞, followed by N (the cross sectional dimension) →∞. A diagonal convergence result with T and N→∞ while N/T→k,k being a finite non-negative constant, is also conjectured. In the special case where errors in individual Dickey–Fuller (DF) regressions are serially uncorrelated a modified version of the standardized t-bar statistic is shown to be distributed as standard normal as N→∞ for a fixed T, so long as T>5 in the case of DF regressions with intercepts and T>6 in the case of DF regressions with intercepts and linear time trends. An exact fixed N and T test is also developed using the simple average of the DF statistics. Monte Carlo results show that if a large enough lag order is selected for the underlying ADF regressions, then the small sample performances of the t-bar test is reasonably satisfactory and generally better than the test proposed by Levin and Lin (Unpublished manuscript, University of California, San Diego, 1993).
          Hurlin, C., "Testing for Unit Roots in Heterogeneous Panels ", Journal of Econometrics, 115, 53-74.
          Authors: Im
          Pesaran
          Shin
          Coders: Hurlin
          Last update
          10/08/2012
          Ranking
          61
          Runs
          57
          Visits
          106
          Testing for a Unit Root in Panels with Dynamic Factors
          Abstract
          This paper studies testing for a unit root for large n and T panels in which the cross-sectional units are correlated. To model this cross-sectional correlation, we assume that the data are generated by an unknown number of unobservable common factors. We propose unit root tests in this environment and derive their (Gaussian) asymptotic distribution under the null hypothesis of a unit root and local alternatives. We show that these tests have significant asymptotic power when the model has no incidental trends. However, when there are incidental trends in the model and it is necessary to remove heterogeneous deterministic components, we show that these tests have no power against the same local alternatives. Through Monte Carlo simulations, we provide evidence on the finite sample properties of these new tests.
          Hurlin, C., "Testing for a Unit Root in Panels with Dynamic Factors", Journal of Econometrics, 122, 81-126.
          Authors: Moon
          Perron
          Coders: Hurlin
          Last update
          10/08/2012
          Ranking
          62
          Runs
          399
          Visits
          124
          Tests of Conditional Predictive Ability
          Abstract
          We propose a framework for out-of-sample predictive ability testing and forecast selection designed for use in the realistic situation in which the forecasting model is possibly misspecified, due to unmodeled dynamics, unmodeled heterogeneity, incorrect functional form, or any combination of these. Relative to the existing literature (Diebold and Mariano (1995) and West (1996)), we introduce two main innovations: (i) We derive our tests in an environment where the finite sample properties of the estimators on which the forecasts may depend are preserved asymptotically. (ii) We accommodate conditional evaluation objectives (can we predict which forecast will be more accurate at a future date?), which nest unconditional objectives (which forecast was more accurate on average?), that have been the sole focus of previous literature. As a result of (i), our tests have several advantages: they capture the effect of estimation uncertainty on relative forecast performance, they can handle forecasts based on both nested and nonnested models, they allow the forecasts to be produced by general estimation methods, and they are easy to compute. Although both unconditional and conditional approaches are informative, conditioning can help fine-tune the forecast selection to current economic conditions. To this end, we propose a two-step decision rule that uses current information to select the best forecast for the future date of interest. We illustrate the usefulness of our approach by comparing forecasts from leading parameter-reduction methods for macroeconomic forecasting using a large number of predictors.
          Giacomini, R., "Tests of Conditional Predictive Ability ", Econometrica, 74, 1545-1578.
          Authors: White
          Giacomini
          Coders: Giacomini
          Last update
          07/04/2012
          Ranking
          25
          Runs
          17
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