nep-rmg New Economics Papers
on Risk Management
Issue of 2016‒08‒07
fifteen papers chosen by

  1. Credit Risk and Collateral Demand in a Retail Payment System By Héctor Pérez Saiz; Gabriel Xerri
  2. Efficient exposure computation by risk factor decomposition By Cornelis S. L. de Graaf; Drona Kandhai; Christoph Reisinger
  3. The effect of heterogeneity on flocking behavior and systemic risk By Fei Fang; Yiwei Sun; Konstantinos Spiliopoulos
  4. Comments on: Nonparametric Tail Risk, Stock Returns and the Macroeconomy By Lorenzo CAMPONOVO; Olivier SCAILLET; Fabio TROJANI
  5. Moral hazard and strategic default: evidence from Greek corporate loans By Ioannis Asimakopoulos; Panagiotis K. Avramidis; Dimitris Malliaropulos; Nickolaos G. Travlos
  6. Liquidity Management in Banking: What is the Role of Leverage? By Quynh Anh VO
  7. Linear Credit Risk Models By Damien Ackerer; Damir Filipović
  8. Functional Systemic Risk, Complementarities and Early Warnings By Cañón Salazar Carlos Iván;Gallón Santiago;Olivar Santiago
  9. A Theory of Operational Risk By Andrea M. Buffa; Suleyman Basak
  10. Replicating Portfolio Approach to Capital Calculation By Mathieu Cambou; Damir Filipović
  11. Are banks’ below-par own debt repurchases a cause for prudential concern? By Lubberink, Martien; Renders, Annelies
  12. Large dynamic covariance matrices By Robert F. Engle; Olivier Ledoit; Michael Wolf
  13. A Conceptual Design of “What and How Should a Proper Macro-Prudential Policy Framework Be?” A Globalistic Approach to Systemic Risk and Procuring the Data Needed By Cakir, Murat
  14. Time-Varying Crash Risk: The Role of Stock Market Liquidity By Peter Christoffersen; Bruno Feunou; Yoontae Jeon; Chayawat Ornthanalai
  15. Understanding the sources of macroeconomic uncertainty By Barbara Rossi; Tatevik Sekhposyan; Matthieu Soupre

  1. By: Héctor Pérez Saiz; Gabriel Xerri
    Abstract: The recent financial crisis has led to the development of new regulations to control risk in designated payment systems, and the implementation of new credit risk management standards is one of the key issues. In this paper, we study various credit risk management schemes for the Canadian retail payment system (ACSS) that are designed to cover the exposure of a defaulting member. We consider schemes that use a collateral pool calculated using a rolling time window. Our simulations show that the size of the window has a very significant effect on the average level of collateral and its variability day to day, creating an interesting trade-off. Collateral levels and variability may be important for ACSS participants because they could affect the opportunity costs of pledging collateral, and also the costs of managing it over time. Our results contribute to understanding the practical implementation of risk management schemes in the current and future generations of payment systems in Canada.
    Keywords: Econometric and statistical methods, Financial stability, Payment clearing and settlement systems
    JEL: G21 G23 C58
    Date: 2016
  2. By: Cornelis S. L. de Graaf; Drona Kandhai; Christoph Reisinger
    Abstract: The focus of this paper is the efficient computation of counterparty credit risk exposure on portfolio level. Here, the large number of risk factors rules out traditional PDE-based techniques and allows only a relatively small number of paths for nested Monte Carlo simulations, resulting in large variances of estimators in practice. We propose a novel approach based on Kolmogorov forward and backward PDEs, where we counter the high dimensionality by a generalisation of anchored-ANOVA decompositions. By computing only the most significant term in the decomposition, the dimensionality is reduced effectively, such that a significant computational speed-up arises from the high accuracy of PDE schemes in low dimensions compared to Monte Carlo estimation. Moreover, we show how this truncated decomposition can be used as control variate for the full high-dimensional model, such that any approximation errors can be corrected while a substantial variance reduction is achieved compared to the standard simulation approach. We investigate the accuracy for a realistic portfolio of exchange options, interest rate and cross-currency swaps under a fully calibrated seven-factor model.
    Date: 2016–08
  3. By: Fei Fang; Yiwei Sun; Konstantinos Spiliopoulos
    Abstract: The goal of this paper is to study organized flocking behavior and systemic risk in heterogeneous mean-field interacting diffusions. We illustrate in a number of case studies the effect of heterogeneity in the behavior of systemic risk in the system. We also investigate the effect of heterogeneity on the "flocking behavior" of different agents, i.e., when agents with different dynamics end up behaving the same way in path space and follow closely the mean behavior of the system. Using Laplace asymptotics, we derive an asymptotic formula for the tail of the loss distribution as the number of agents grows to infinity. This characterizes the tail of the loss distribution and the effect of the heterogeneity of the network on the tail loss probability.
    Date: 2016–07
  4. By: Lorenzo CAMPONOVO (University of St. Gallen); Olivier SCAILLET (University of Geneva and Swiss Finance Institute); Fabio TROJANI (University of Geneva and Swiss Finance Institute)
    Abstract: This paper contains comments on Nonparametric Tail Risk, Stock Returns and the Macroeconomy.
    Keywords: Tail Risk, Risk Factor, Risk-Neutral Probability, Prediction of Market Returns, Economic Predictability
    JEL: G12 G13 G17
  5. By: Ioannis Asimakopoulos (Bank of Greece); Panagiotis K. Avramidis (ALBA Graduate Business School at the American College of Greece); Dimitris Malliaropulos (Bank of Greece, University of Piraeus); Nickolaos G. Travlos
    Abstract: Using a unique dataset of corporate loans of 13,070 Greek firms for the period 2008-2015 and an identification strategy based on the internal credit ratings of banks, we provide evidence that one out of six firms with non-performing loans are strategic defaulters. Furthermore, we investigate potential determinants of firms’ behavior by relating the probability of strategic default to a number of firm characteristics such as size, age, liquidity, profitability and collateral value. We provide evidence of a positive relationship of strategic default with outstanding debt and economic uncertainty and a negative relationship with the value of collateral. Also, profitability and collateral can be used to distinguish the strategic defaulters from the financially distressed defaulters. Finally, we find evidence that the relationship of strategic default risk with firm size and age has an inverse U-shape, i.e. strategic default is more likely among medium-sized firms compared to small and large firms and it is also more likely among middle-aged firms compared to new-founded and established firms.
    Keywords: Strategic default; Non-performing loans; Corporate loans; Leverage
    JEL: G01 G21 G32 C23
  6. By: Quynh Anh VO (University of Zurich)
    Abstract: This paper examines potential impacts of banks' leverage on their incentives to manage their liquidity. We analyse a model where banks control their liquidity risk by managing their liquid asset positions. In the basic framework, a model with a single bank, where the possibility of selling long-term assets when in need of liquidity is not taken into account, we find that the bank chooses to prudently manage its liquidity risk only when its leverage is low. In a model with multiple banks and a secondary market for long-term assets, we find that a banking system where banks are highly leveraged can be prone to liquidity crises. Our model predicts a typical pattern of liquidity crises that is consistent with what was observed during the 2007-2009 crisis.
    Keywords: Leverage, Liquidity Risk, Moral Harzard, Cash-In-The-Market Pricing
    JEL: G21 D82
  7. By: Damien Ackerer (Ecole Polytechnique Fédérale de Lausanne; Ecole Polytechnique Fédérale de Lausanne - Swiss Finance Institute); Damir Filipović (Ecole Polytechnique Fédérale de Lausanne; Ecole Polytechnique Fédérale de Lausanne - Swiss Finance Institute)
    Abstract: We introduce a novel class of credit risk models in which the drift of the survival process of a firm is a linear function of the factors. These models outperform the standard affine default intensity models in terms of analytical tractability. The prices of defaultable bonds and credit default swaps (CDS) are linear in the factors. The price of a CDS option can be uniformly approximated by polynomials in the factors. An empirical study illustrates the versatility of these models by fitting CDS spread time series.
    Keywords: Credit Default Swap, Credit Default Swap Option, Credit Risk, Credit Valuation Adjustment, Survival Process
    JEL: G12 G13
  8. By: Cañón Salazar Carlos Iván;Gallón Santiago;Olivar Santiago
    Abstract: This paper proposes a systemic risk index based on Functional Data Analysis (FDA), overcoming salient shortcomings of standard methodologies related to data usage, data sparseness, and high dimensionality issues. Using Mexican data, a set of systemic risk indexes are constructed and we show that the proposed functional index captures new information, and through simulations, that it outperforms previous methods when the indicators become increasingly nonlinear. Finally, we show which indexes serve as complements, and which are the best early warning indicators.
    Keywords: Systemic Risk; Functional Data Analysis; Dimensionality Reduction; Signal Informativeness
    JEL: G01 G10 G17 G18
    Date: 2016–07
  9. By: Andrea M. Buffa (Boston University); Suleyman Basak (London Business School)
    Abstract: We study the dynamic decision making of a financial institution in the presence of a novel implementation friction that gives rise to operational risk. We distinguish between internal and external operational risks depending on whether the institution has control over them. Internal operational risk naturally arises in the context of model risk, as the institution exposes itself to operational errors whenever it updates and improves its investment model. In this case, it is no longer optimal to implement the best model available, thus leaving scope for endogenous deviation from it, and hence model sophistication. We show that the optimal exposure to operational risk may well become decreasing in the level of internal operational risk, which in turn makes the exposure to market risk less volatile. We uncover that financial constraints interact with operational risk, whether internal or external, and prompt the institution to always adopt a more sophisticated model. While such constraints are always detrimental when operational risk is internal, they may be beneficial, despite inducing an excessive level of sophistication, when it is external.
    Date: 2016
  10. By: Mathieu Cambou (Ecole Polytechnique Fédérale de Lausanne); Damir Filipović (Ecole Polytechnique Fédérale de Lausanne; Ecole Polytechnique Fédérale de Lausanne - Swiss Finance Institute)
    Abstract: The replicating portfolio (RP) approach to the calculation of capital for life insurance portfolios is an industry standard. The RP is obtained from projecting the terminal loss of discounted asset liability cash flows on a set of factors generated by a family of financial instruments that can be efficiently simulated. We provide the mathematical foundations and a novel dynamic and path-dependent RP approach for real-world and risk-neutral sampling. We show that the RP approach yields asymptotically consistent capital estimators. We illustrate the tractability of the RP approach by two numerical examples.
    Keywords: asset-liability portfolio, chaos expansion, replicating portfolio, solvency capital
    JEL: C61 C63 D81 G22
  11. By: Lubberink, Martien; Renders, Annelies
    Abstract: Leading up to the implementation of Basel III, European banks repurchased below-par debt securities. Banks are subjected to a prudential filter that excludes unrealized gains on liabilities from changes in own credit standing from the calculation of capital ratios. By repurchasing securities, unrealized gains become realized and increase Core Tier 1 capital. We show that poorly capitalized banks repurchased securities and lost about e9.1bn in premiums to compensate debt holders. Banks also repurchased the most loss-absorbing securities, for which they paid the highest premiums. These premiums increase with leverage and in times of stress. Hence debt repurchases are a cause for prudential concern.
    Keywords: Banking, repurchases, subordinated debt.
    JEL: E58 G21 G28 G32 G35 M41
    Date: 2016–06–15
  12. By: Robert F. Engle; Olivier Ledoit; Michael Wolf
    Abstract: Second moments of asset returns are important for risk management and portfolio selection. The problem of estimating second moments can be approached from two angles: time series and the cross-section. In time series, the key is to account for conditional heteroskedasticity; a favored model is Dynamic Conditional Correlation (DCC), derived from the ARCH/GARCH family started by Engle (1982). In the cross-section, the key is to correct in-sample biases of sample covariance matrix eigenvalues; a favored model is nonlinear shrinkage, derived from Random Matrix Theory (RMT). The present paper aims to marry these two strands of literature in order to deliver improved estimation of large dynamic covariance matrices.
    Keywords: Composite likelihood, dynamic conditional correlations, GARCH, Markowitz portfolio selection, nonlinear shrinkage.
    JEL: C13 C58 G11
    Date: 2016–07
  13. By: Cakir, Murat
    Abstract: During the last half-decade, the 2007 global crisis has kept all interested parties busy and urged them to focus on the causes of this crisis, to find solutions for recovery, and to contrive to be capable of projecting potential ones that may happen in the future. As one of the precautionary tool-sets devised for the authorities among others the classical macro-prudential and systemic risk models focused on banks and sought for the systemically important ones (SIFIs). It had been argued by a handful of interest groups that this sort of approach to risk embedded in a network structure was both unbalanced condoning potential plausible sources of risk to monitor passively as well as take policy actions pro-actively and further was undue in remedying possible causes if, when and where seen indispensable. Therefore, a more macro stance towards the conventional macro-prudential paradigms considering micro elements of the system was seen as vital. This work attempts to draw an extended framework that would span all potential incumbents forming part of the Circular Flow of Income (CFI), which is treated as a network or a bijective counter-party mapping of incumbent groups of different sources that each have claims against the funds granted to other groups or to members of the same group. Availability of data would be a focal point for the operability of a model as such. Though the significance of data availability being a central question is inarguable and the necessary data is really scarce, that doesn’t abstain one from devising usable designs, nor does it from standing in a proper position in such design efforts for public welfare. In reality, the data is available for a different variety of incumbent groups at different levels of congruity, but unfortunately sparsely distributed among different collectors and users . Still, there is data that can be used for empirical analysis purposes but needs a considerable extent of effort to collect and make use of. We propose a simple methodology on how to use the data on the extended framework, -tipping on another study- a data procural system shortly, and provide an in-exhaustive list of potential features that can be used for our extended model at the end. There will be no issue of identification neither of risks from a particular source, nor of policy recommendations since they are a subject of another work and out of the scope of the current one. Still, one should bear in mind that though this other stream of work of ours employs any kind of analytical methodology that’d fit a particular context a general balance sheet, and the valuation of sub-portfolios at risk are the main architectural frame that shapes our analytical basis .
    Keywords: Systemic Risk, Macro Prudential Policy, Circular Flow of Income
    JEL: E58 G28
    Date: 2016–07–29
  14. By: Peter Christoffersen; Bruno Feunou; Yoontae Jeon; Chayawat Ornthanalai
    Abstract: We estimate a continuous-time model with stochastic volatility and dynamic crash probability for the S&P 500 index and find that market illiquidity dominates other factors in explaining the stock market crash risk. While the crash probability is time-varying, its dynamic depends only weakly on return variance once we include market illiquidity as an economic variable in the model. This finding suggests that the relationship between variance and jump risk found in the literature is largely due to their common exposure to market liquidity risk. Our study highlights the importance of equity market frictions in index return dynamics and explains why prior studies find that crash risk increases with market uncertainty level.
    Keywords: Asset Pricing, Econometric and statistical methods, Financial stability
    JEL: G01 G12
    Date: 2016
  15. By: Barbara Rossi; Tatevik Sekhposyan; Matthieu Soupre
    Abstract: We propose a decomposition to distinguish between Knightian uncertainty (ambiguity) and risk, where the ?rst measures the uncertainty about the probability distribution generating the data, while the second measures uncertainty about the odds of the outcomes when the probability distribution is known. We use the Survey of Professional Forecasters (SPF) density forecasts to quantify overall uncertainty as well as the evolution of the di¤erent components of uncertainty over time and investigate their importance for macroeconomic ?uctuations. We also study the behavior and evolution of the various components of our decomposition in a model that features ambiguity and risk.
    Keywords: Uncertainty, Risk, Ambiguity, Knightian Uncertainty, Survey of Professional Forecasters, Predictive Densities.
    JEL: C22 C52 C53
    Date: 2016–05

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