nep-rmg New Economics Papers
on Risk Management
Issue of 2012‒05‒22
ten papers chosen by
Stan Miles
Thompson Rivers University

  1. Shock on Variable or Shock on Distribution with Application to Stress-Tests By Simon Dubecq; Christian Gouriéroux
  2. Bank regulation and stability: An examination of the Basel market risk framework By Alexander, Gordon J.; Baptista, Alexandre M.; Yan, Shu
  3. Credit portfolio modelling and its effect on capital requirements By Bülbül, Dilek; Lambert, Claudia
  4. Risk management in Islamic banks By Helmy, Mohamed
  5. Examining what best explains corporate credit risk: accounting-based versus market-based models By Antonio Trujillo-Ponce; Reyes Samaniego-Medina; Clara Cardone-Riportella
  6. A hierarchical model of tail dependent asset returns for assessing portfolio credit risk By Puzanova, Natalia
  7. Optimal starting times, stopping times and risk measures for algorithmic trading By Mauricio Labadie; Charles-Albert Lehalle
  8. Macroprudential banking regulation: Does one size fit all? By Doris Neuberger; Roger Rissi
  9. Semi-parametric forecasting of Spikes in Electricity Prices By Adam E Clements; Joanne Fuller; Stan Hurn
  10. Estimating the Marginal Law of a Time Series with Applications to Heavy Tailed Distributions By Christian Francq; Jean-Michel Zakoïan

  1. By: Simon Dubecq (Banque de France); Christian Gouriéroux (CREST, University of Toronto)
    Abstract: The shocks on a stochastic system can be defined by means of either distribution, or variable. We relate these approaches and provide the link between the global and local effects of both types of shocks. These methodologies are used to perform stress-tests on the portfolio of financial institutions by means of shocks on systematic factors, for which we distinguish the cases of crystallized and optimally updated portfolios. The approach is illustrated by an analysis of the risk of sovereign bonds of the Eurozone.
    Keywords: Shock, Copula, Extreme Risk, Stress-Test, Factor Model, Systemic Risk, Portfolio Management, Sovereign Bonds
    Date: 2012–02
  2. By: Alexander, Gordon J.; Baptista, Alexandre M.; Yan, Shu
    Abstract: In attempting to promote bank stability, the Basel Committee on Banking Supervision (2006) provides a framework that seeks to control the amount of tail risk that large banks take in their trading books. However, banks around the world suffered sizeable trading losses during the recent crisis. Due to the size and prevalence of losses, a formal examination of whether the Basel framework allows banks to take substantive tail risk in their trading books without a capital requirement penalty is of particular interest. In this paper, we provide such an examination and show that the Basel framework indeed allows banks to do so. Hence, our paper supports the view that the Basel framework leaves room for considerable improvements regarding the treatment of tail risk. --
    Keywords: Bank regulation,bank stability,Basel framework,crisis,tail risk
    JEL: G11 G21 G28 D81
    Date: 2012
  3. By: Bülbül, Dilek; Lambert, Claudia
    Abstract: The subprime crisis revealed that the adoption of suitable systems for the management of credit risk is of utmost concern. The Basel Committee on Banking Supervision (2009) advises banks to use credit portfolio models with caution when assessing the capital adequacy. This paper investigates whether decisions on total risk-based capital ratios are channeled through credit portfolio models. In other words, do credit portfolio models serve as a relevant determinant for banks to adjust their capital allocation? To empirically test the relationship we measure the average treatment effect by conducting a quasi-natural experiment in which we employ a propensity-matching approach to panel data. We find that the adoption of credit portfolio models positively and significantly affects regulatory capital decisions of banks both directly following the introduction as well as over a longer time horizon. By now it is commonly accepted that overreliance on credit portfolio models composes a fundamental cause of the current financial crisis. Our results put the debate about overreliance on quantitative models in a new perspective. This knowledge may prove valuable for regulators who aim to understand bank behaviour and thus advance regulation. --
    Keywords: Risk management,regulation,capital requirement,credit portfolio model,propensity score
    JEL: G21 G28 G32
    Date: 2012
  4. By: Helmy, Mohamed
    Abstract: The use of financial services and products that comply with the Shariah principles cause special issues for supervision and risk management. Efficient risk management in Islamic banking has assumed particular importance as they try to cope with the challenges of globalization. This paper highlights the special and general risks surrounding Islamic banking. It also explains the key challenges ahead to promote further development of Islamic banking in the global financial system. As The developing of managing risks tool becomes very essential especially in Islamic banking as most of the products is depending on PLS principle , so identifying and measuring each type of risk is highly important and critical in any Islamic financial based system . Another approach on the recommendation is showing how the Islamic banking can be an ideal alternative than the current conventional banking system . emphasizing the role of Islamic banking on hedging against the economic crisis and the how it can be an add value to the nationals economics in terms of making the society more productive .
    Keywords: Risk Management in Islamic Banks
    JEL: G32
    Date: 2012–04–20
  5. By: Antonio Trujillo-Ponce (Department of Finance and Accounting, Universidad Pablo de Olavide); Reyes Samaniego-Medina (Department of Finance and Accounting, Universidad Pablo de Olavide); Clara Cardone-Riportella (Department of Business Administration, Universidad Carlos III de Madrid)
    Abstract: Using a sample of 2,186 credit default swap (CDS) spreads quoted in the European market during the period 2002-2009, this paper empirically analyzes which model – accounting- or market-based – better explains corporate credit risk. We find that there is little difference in the explanatory power of the two approaches. Our results suggest that both accounting and market data complement one other and thus that a comprehensive model that includes both types of variables appears to be the best option for explaining credit risk. We also show that the explanatory power of accounting- and market-based variables for measuring credit risk is particularly strong during periods of high uncertainty, as experienced in the recent financial crisis, and that it decreases as the CDS contract matures. Finally, the comprehensive model continues to show the best results when using the credit rating as the proxy for credit risk, but accounting variables currently appear to have a more important role than the market variables
    Keywords: Bankruptcy; credit default swaps; credit risk; distance-to-default
    Date: 2012–05
  6. By: Puzanova, Natalia
    Abstract: This paper introduces a multivariate pure-jump Lévy process which allows for skewness and excess kurtosis of single asset returns and for asymptotic tail dependence in the multivariate setting. It is termed Variance Compound Gamma (VCG). The novelty of my approach is that, by applying a two-stage stochastic time change to Brownian motions, I derive a hierarchical structure with different properties of inter- and intra-sector dependence. I investigate the properties of the implied static copula families and come to the conclusion that they are ordered with respect to their parameters and that the lower-tail dependence of the intra-sector copula is increasing in the absolute values of skewness parameters. Furthermore, I show that the joint characteristic function of the VCG asset returns can be explicitly given as a nested Archimedean copula of their marginal characteristic functions. Applied to credit portfolio modelling, the framework introduced results in a more conservative tail risk assessment than a Gaussian framework with the same linear correlation structure, as I show in a simulation study. To foster the simulation efficiency, I provide an Importance Sampling algorithm for the VCG portfolio setting. --
    Keywords: Portfolio Credit Risk,Stochastic Time Change,Brownian Subordination,Jumps,Tail Dependence,Hierarchical Dependence Structure
    JEL: C46 C63 G12 G21
    Date: 2011
  7. By: Mauricio Labadie; Charles-Albert Lehalle
    Abstract: We derive explicit recursive formulas for Target Close (TC) and Implementation Shortfall (IS) in the Almgren-Chriss framework. We explain how to compute the optimal starting and stopping times for IS and TC, respectively, given a minimum trading size. We also show how to add a minimum participation rate constraint (Percentage of Volume, PVol) for both TC and IS. We also study an alternative set of risk measures for the optimisation of algorithmic trading curves. We assume a self-similar process (e.g. L\'evy process, fractional Brownian motion or fractal process) and define a new risk measure, the $p$-variation, which reduces to the variance if the process is a Brownian motion. We deduce the explicit formula for the TC and IS algorithms under a self-similar process. We show that there is an equivalence between self-similar models and a family of risk measures called $p$-variations: assuming a self-similar process and calibrating empirically the parameter $p$ for the $p$-variation yields the same result as assuming a Brownian motion and using the $p$-variation as risk measure instead of the variance. We also show that $p$ can be seen as a measure of the aggressiveness: $p$ increases if and only if the TC algorithm starts later and executes faster. From the explicit expression of the TC algorithm one can compute the sensitivities of the curve with respect to the parameters up to any order. As an example, we compute the first order sensitivity with respect to both a local and a global surge of volatility. Finally, we show how the parameter $p$ of the $p$-variation can be implied from the optimal starting time of TC, and that under this framework $p$ can be viewed as a measure of the joint impact of market impact (i.e. liquidity) and volatility.
    Date: 2012–05
  8. By: Doris Neuberger (University of Rostock); Roger Rissi (Lucerne University of Applied Sciences and Arts)
    Abstract: The macroprudential regulatory framework of Basel III imposes the same capital and liquidity requirements on all banks around the world to ensure global competitiveness of banks. Using an agent-based model of the financial system, we find that this is not a robust framework to achieve (inter)national financial stability, because efficient regulation has to embrace the economic structure and behaviour of financial market participants, which differ from country to country. Market-based financial systems do not profit from capital and liquidity regulations, but from a ban on proprietary trading (Volcker rule). In homogeneous or bank-based financial systems, the most effective regulatory policy to ensure financial stability depends on the stability measure used. Irrespective of financial system architecture, direct restrictions of banks’ investment portfolios are more effective than indirect restrictions through capital, leverage and liquidity regulations.
    Keywords: financial stability, systemic risk, financial system, banking regulation, agent-based model
    JEL: C63 G01 G11 G21 G28
    Date: 2012
  9. By: Adam E Clements (QUT); Joanne Fuller (QUT); Stan Hurn (QUT)
    Abstract: The occurrence of extreme movements in the spot price of electricity represent a significant source of risk to retailers. Electricity markets are often structured so as to allow retailers to purchase at an unregulated spot price but then sell to consumers at a heavily regulated price. As such, the ability to forecast price spikes is an important aspect of effective risk management. A range of approaches have been considered with respect to modelling electricity prices, including predicting the trajectory of spot prices, as well as more recently, focusing of the prediction of spikes specifically. These models however, have relied on time series approaches which typically use restrictive decay schemes placing greater weight on more recent observations. This paper develops an alternative, semi-parametric method for forecasting that does not rely on this convention. In this approach, a forecast is a weighted average of historical price data, with the greatest weight given to periods that exhibit similar market conditions to the time at which the forecast is being formed. Weighting is determined by comparing short-term trends in electricity price spike occurrences across time, including other relevant factors such as load, by means of a multivariate kernel scheme. It is found that the semi-parametric method produces forecasts that are more accurate than the previously identified best approach for a short forecast horizon.
    Keywords: Electricity Prices, Prices Spikes, Semi-parametric, Multivariate Kernel
    JEL: C14 C53
    Date: 2012–05–16
  10. By: Christian Francq (CREST); Jean-Michel Zakoïan (CREST)
    Keywords: alpha-stable distribution, composite likelihood, GEV distribution, GPD, pseudo-likelihood, quasi-marginal maximum likelihood, stock returns distributions
    Date: 2011

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