New Economics Papers
on Risk Management
Issue of 2011‒06‒11
seven papers chosen by

  1. Uncovering Long Memory in High Frequency UK Futures By John Cotter
  2. Alleviating Coordination Problems and Regulatory Constraints through Financial Risk Management By Marcel Boyer; M. Martin Boyer; René Garcia
  3. Understanding Liquidity and Credit Risks in the Financial Crisis* By Deborah Gefang; Gary Koop; Simon Potter
  4. On finite-time ruin probabilities with reinsurance cycles influenced by large claims By Mathieu Bargès; Stéphane Loisel; Xavier Venel
  5. Forecasting Financial Stress By Jan Willem Slingenberg; Jakob de Haan
  6. The near-extreme density of intraday log-returns By Mauro Politi; Nicolas Millot; Anirban Chakraborti
  7. Absolute Return Volatility By John Cotter

  1. By: John Cotter (University College Dublin)
    Abstract: Accurate volatility modelling is paramount for optimal risk management practices. One stylized feature of financial volatility that impacts the modelling process is long memory explored in this paper for alternative risk measures, observed absolute and squared returns for high frequency intraday UK futures. Volatility series for three different asset types, using stock index, interest rate and bond futures are analysed. Long memory is strongest for the bond contract. Long memory is always strongest for the absolute returns series and at a power transformation of k < 1. The long memory findings generally incorporate intraday periodicity. The APARCH model incorporating seven related GARCH processes generally models the futures series adequately documenting ARCH, GARCH and leverage effects.
    Keywords: Long Memory, APARCH, High Frequency Futures
    Date: 2011–05–30
  2. By: Marcel Boyer; M. Martin Boyer; René Garcia
    Abstract: We characterize a firm as a nexus of activities and projects with their associated cash flow distributions across states of the world and time periods. We propose a characterization of the firm where variations in the market price of risk induce adjustments in the value-maximizing combination of projects. Changing the portfolio of projects generates coordination costs. We propose a new role for financial risk management based on the idea that the use of financial derivatives may reduce coordination costs. We find empirical support for this new rationale for the use of financial derivatives, after controlling for the traditional variables explaining the need for financial risk management. <P>Nous caractérisons une entreprise comme un ensemble d'activités et de projets avec leurs flux financiers par état et période. Nous proposons une caractérisation de l'entreprise où les variations dans le prix de marché du risque induisent des ajustements dans la combinaison optimale d’activités ou de projets. Les modifications du portefeuille de projets génèrent des coûts de coordination. Nous proposons un nouveau rôle pour la gestion financière des risques en proposant que l'utilisation de titres financiers puisse réduire les coûts de coordination. Ce nouveau rôle de la gestion financière des risques est vérifié empiriquement, une fois pris en compte les facteurs explicatifs traditionnels de la gestion financière des risques.
    Keywords: Risk Management, firm value, coordination problems, hedging, value at risk., Gestion des risques, valeur d’entreprise, problèmes de coordination, hedging, valeur à risque.
    Date: 2011–05–01
  3. By: Deborah Gefang (Department of Economics, University of Lan~~#badcaster); Gary Koop (Department of Economics, University of Strathclyde); Simon Potter (Research and Statistics Group, Federal Reserve Bank of New York)
    Abstract: This paper develops a structured dynamic factor model for the spreads between London Interbank O¤ered Rate (LIBOR) and overnight index swap (OIS) rates for a panel of banks. Our model involves latent factors which relect liquidity and credit risk. Our empirical results show that surges in the short term LIBOR-OIS spreads during the 2007-2009 financial crisis were largely driven by liquidity risk. However, credit risk played a more significant role in the longer term (twelve-month) LIBOR-OIS spread. The liquidity risk factors are more volatile than the credit risk factor. Most of the familiar events in the financial crisis are linked more to movements in liquidity risk than credit risk.
    Keywords: LIBOR-OIS spread, factor model, credit default swap, Bayesian
    JEL: C11 C22 G21
    Date: 2011–04
  4. By: Mathieu Bargès (SAF - Laboratoire de Sciences Actuarielle et Financière - Université Claude Bernard - Lyon I : EA2429, Ecole d'Actuariat - Université Laval); Stéphane Loisel (SAF - Laboratoire de Sciences Actuarielle et Financière - Université Claude Bernard - Lyon I : EA2429); Xavier Venel (SAF - Laboratoire de Sciences Actuarielle et Financière - Université Claude Bernard - Lyon I : EA2429, C&O - Equipe combinatoire et optimisation - Université Pierre et Marie Curie - Paris VI - CNRS : FRE3232, IMJ - Institut de Mathématiques de Jussieu - CNRS : UMR7586 - Université Pierre et Marie Curie - Paris VI - Université Paris-Diderot - Paris VII)
    Abstract: Market cycles play a great role in reinsurance. Cycle transitions are not independent from the claim arrival process : a large claim or a high number of claims may accelerate cycle transitions. To take this into account, a semi-Markovian risk model is proposed and analyzed. A refined Erlangization method is developed to compute the finite-time ruin probability of a reinsurance company. As this model needs the claim amounts to be Phase-type distributed, we explain how to fit mixtures of Erlang distributions to long-tailed distributions. Numerical applications and comparisons to results obtained from simulation methods are given. The impact of dependency between claim amounts and phase changes is studied.
    Date: 2011
  5. By: Jan Willem Slingenberg; Jakob de Haan
    Abstract: This paper uses a Financial Stress Index (FSI) for 13 OECD countries to examine which variables can help predicting financial stress. A stress index measures the current state of stress in the financial system and summarizes it in a single statistic. We employ three criteria for indicators to be used in constructing a multi-country FSI (the index covers the entire financial system, indicators used are available at a high frequency for many countries for a long period, and are comparable) to come up with our FSI. Our results suggest that financial stress is hard to predict. Only credit growth has predictive power for most countries. Several other variables have predictive power for some countries, but not for others.
    Keywords: financial stress index; predicting financial stress
    JEL: E5 G10
    Date: 2011–04
  6. By: Mauro Politi; Nicolas Millot; Anirban Chakraborti
    Abstract: The extreme event statistics plays a very important role in the theory and practice of time series analysis. The reassembly of classical theoretical results is often undermined by non-stationarity and dependence between increments. Furthermore, the convergence to the limit distributions can be slow, requiring a huge amount of records to obtain significant statistics, and thus limiting its practical applications. Focussing, instead, on the closely related density of "near-extremes" -- the distance between a record and the maximal value -- can render the statistical methods to be more suitable in the practical applications and/or validations of models. We apply this recently proposed method in the empirical validation of an adapted financial market model of the intraday market fluctuations.
    Date: 2011–05
  7. By: John Cotter (University College Dublin)
    Date: 2011–05–30

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