New Economics Papers
on Risk Management
Issue of 2011‒07‒02
seventeen papers chosen by



  1. Extreme Spectral Risk Measures: An Application to Futures Clearinghouse Margin Requirements By John Cotter; Kevin Dowd
  2. Re-evaluating Hedging Performance By John Cotter; Jim Hanly
  3. Estimating Financial Risk Measures for Futures Positions:A Non-Parametric Approach By John Cotter; Kevin Dowd
  4. Spectral Risk Measures with an Application to Futures Clearinghouse Variation Margin Requirements By John Cotter; Kevin Dowd
  5. On downside risk predictability through liquidity and trading activity: a quantile regression approach By Lidia Sanchis-Marco; Antonio Rubia Serrano
  6. Modelling Catastrophic Risk in International Equity Markets: An Extreme Value Approach By John Cotter
  7. Fast remote but not extreme quantiles with multiple factors. Applications to Solvency II and Enterprise Risk Management By Matthieu Chauvigny; Laurent Devineau; Stéphane Loisel; Véronique Maume-Deschamps
  8. Margin Requirements with Intraday Dynamics By John Cotter; Francois Longin
  9. Intra-Day Seasonality in Foreign Market Transactions By Kevin Dowd; John Cotter
  10. Evaluating the Precision of Estimators of Quantile-Based Risk Measures By John Cotter; Kevin Dowd
  11. Measuring and testing for the systemically important financial institutions By Carlos Castro; Stijn Ferrari
  12. Modelling Long Memory in REITs By John Cotter
  13. Studio di un indicatore per la valutazione del rischio delprogetto nella metodologia dell’analisi costi benefici - Proposed risk indicators in the cost-benefit analisys methodology By Mario Genco
  14. Multivariate Modelling of Daily REIT Volatility By John Cotter; Simon Stevenson
  15. Identifying Vulnerabilities in Systemically-Important Financial Institutions in a Macro-financial Linkages Framework By Tao Sun
  16. Successfully implementing major financial stability regulatory reforms: the risk weighting based controversy (Basel v Dodd Frank) and the role of national supervisors By Ojo, Marianne
  17. Financial Risks and the Pension Protection Fund:Can It Survive Them? By David Blake; John Cotter; Kevin Dowd

  1. By: John Cotter (University College Dublin, Ireland); Kevin Dowd (The University of Nottingham, UK)
    Abstract: This paper applies the Extreme-Value (EV) Generalised Pareto distribution to the extreme tails of the return distributions for the S&P500, FT100, DAX, Hang Seng, and Nikkei225 futures contracts. It then uses tail estimators from these contracts to estimate spectral risk measures, which are coherent risk measures that reflect a user’s risk-aversion function. It compares these to VaR and Expected Shortfall (ES) risk measures, and compares the precision of their estimators. It also discusses the usefulness of these risk measures in the context of clearinghouses setting initial margin requirements, and compares these to the SPAN measures typically used.
    Keywords: Spectral risk measures, Expected Shortfall, Value at Risk, Extreme Value, clearinghouse
    JEL: G15
    Date: 2011–06–24
    URL: http://d.repec.org/n?u=RePEc:ucd:wpaper:2005/16&r=rmg
  2. By: John Cotter (University College Dublin, Ireland); Jim Hanly (Dublin Institute of Technology)
    Abstract: Mixed results have been documented for the performance of hedging strategies using futures. This paper reinvestigates this issue using an extensive set of performance evaluation metrics across seven international markets. We compare the hedging performance of short and long hedgers using traditional variance based approaches together with modern risk management techniques including Value at Risk, Conditional Value at Risk and approaches based on Downside Risk. Our findings indicate that using these metrics to evaluate hedging performance, yields differences in terms of best hedging strategy as compared with the traditional variance measure. We also find significant differences in performance between short and long hedgers. These results are observed both in-sample and out-of-sample.
    Keywords: Hedging Performance; Lower Partial Moments; Downside Risk; Variance; Semi- Variance; Value at Risk, Conditional Value at Risk
    JEL: G10 G12 G15
    Date: 2011–06–24
    URL: http://d.repec.org/n?u=RePEc:ucd:wpaper:2005/18&r=rmg
  3. By: John Cotter (University College Dublin, Ireland); Kevin Dowd (The University of Nottingham)
    Abstract: This paper presents non-parametric estimates of spectral risk measures applied to long and short positions in 5 prominent equity futures contracts. It also compares these to estimates of two popular alternative measures, the Value-at-Risk (VaR) and Expected Shortfall (ES). The spectral risk measures are conditioned on the coefficient of absolute risk aversion, and the latter two are conditioned on the confidence level. Our findings indicate that all risk measures increase dramatically and their estimators deteriorate in precision when their respective conditioning parameter increases. Results also suggest that estimates of spectral risk measures and their precision levels are of comparable orders of magnitude as those of more conventional risk measures. Running head: financial risk measures for futures positions.
    JEL: G15
    Date: 2011–06–24
    URL: http://d.repec.org/n?u=RePEc:ucd:wpaper:2006/13&r=rmg
  4. By: John Cotter (University College Dublin, Ireland); Kevin Dowd (The University of Nottingham, UK)
    Abstract: This paper applies an AR(1)-GARCH (1, 1) process to detail the conditional distributions of the return distributions for the S&P500, FT100, DAX, Hang Seng, and Nikkei225 futures contracts. It then uses the conditional distribution for these contracts to estimate spectral risk measures, which are coherent risk measures that reflect a user’s risk-aversion function. It compares these to more familiar VaR and Expected Shortfall (ES) measures of risk, and also compares the precision and discusses the relative usefulness of each of these risk measures in setting variation margins that incorporate time-varying market conditions. The goodness of fit of the model is confirmed by a variety of backtests.
    Keywords: Spectral risk measures, Expected Shortfall, Value at Risk, GARCH, clearinghouse.
    JEL: G15
    Date: 2011–06–24
    URL: http://d.repec.org/n?u=RePEc:ucd:wpaper:2006/16&r=rmg
  5. By: Lidia Sanchis-Marco (Dpto. Análisis Económico y Finanzas); Antonio Rubia Serrano (Universidad de Alicante)
    Abstract: Most downside risk models implicitly assume that returns are a sufficient statistic with which to forecast the daily conditional distribution of a portfolio. In this paper, we address this question empirically and analyze if the variables that proxy for market liquidity and trading conditions convey valid information to forecast the quantiles of the conditional distribution of several representative market portfolios. Using quantile regression techniques, we report evidence of predictability that can be exploited to improve Value at Risk forecasts. Including trading- and spread-related variables improves considerably the forecasting performance.
    Keywords: Value at Risk, Basel, Liquidity, Trading Activity.
    Date: 2011–06
    URL: http://d.repec.org/n?u=RePEc:ivi:wpasad:2011-14&r=rmg
  6. By: John Cotter (University College Dublin, Ireland)
    Abstract: This letter uses the Block Maxima Extreme Value approach to quantify catastrophic risk in international equity markets. Risk measures are generated from a set threshold of the distribution of returns that avoids the pitfall of using absolute returns for markets exhibiting diverging levels of risk. From an application to leading markets, the letter finds that the Nikkei is more prone to catastrophic risk than the FTSE and Dow Jones Indexes.
    Date: 2011–06–24
    URL: http://d.repec.org/n?u=RePEc:ucd:wpaper:2005/15&r=rmg
  7. By: Matthieu Chauvigny (R&D Milliman - Milliman); Laurent Devineau (R&D Milliman - Milliman, SAF - Laboratoire de Sciences Actuarielle et Financière - Université Claude Bernard - Lyon I : EA2429); Stéphane Loisel (SAF - Laboratoire de Sciences Actuarielle et Financière - Université Claude Bernard - Lyon I : EA2429); Véronique Maume-Deschamps (SAF - Laboratoire de Sciences Actuarielle et Financière - Université Claude Bernard - Lyon I : EA2429)
    Abstract: For operational purposes, in Enterprise Risk Management or in insurance for example, it may be important to estimate remote (but not extreme) quantiles of some function ƒ of some random vector. The call to ƒ may be time- and resource-consuming so that one aims at reducing as much as possible the number of calls to ƒ. In this paper, we propose some ways to address this problem of general interest. We then numerically analyze the performance of the method on insurance and Enterprise Risk Management real-world case studies.
    Date: 2011
    URL: http://d.repec.org/n?u=RePEc:hal:journl:hal-00517766&r=rmg
  8. By: John Cotter (University College Dublin, Ireland); Francois Longin (ESSEC Graduate Business School, France)
    Abstract: Both in practice and in the academic literature, models for setting margin requirements in futures markets use daily closing price changes. However, financial markets have recently shown high intraday volatility, which could bring more risk than expected. Such a phenomenon is well documented in the literature on high-frequency data and has prompted some exchanges to set intraday margin requirements and ask intraday margin calls. This article proposes to set margin requirements by taking into account the intraday dynamics of market prices. Daily margin levels are obtained in two ways: first, by using daily price changes defined with different time-intervals (say from 3 pm to 3 pm on the following trading day instead of traditional closing times); second, by using 5-minute and 1-hour price changes and scaling the results to one day. An application to the FTSE 100 futures contract traded on LIFFE demonstrates the usefulness of this new approach.
    Keywords: ARCH process, clearinghouse, exchange, extreme value theory, futures markets, highfrequency data, intraday dynamics, margin requirements, model risk, risk management, stress testing, value at risk.
    JEL: G15
    Date: 2011–06–24
    URL: http://d.repec.org/n?u=RePEc:ucd:wpaper:2005/19&r=rmg
  9. By: Kevin Dowd (The University of Nottingham, UK); John Cotter (University College Dublin, Ireland)
    Abstract: Spectral risk measures are attractive risk measures as they allow the user to obtain risk measures that reflect their subjective risk-aversion. This paper examines spectral risk measures based on an exponential utility function, and finds that these risk measures have nice intuitive properties. It also discusses how they can be estimated using numerical quadrature methods, and how confidence intervals for them can be estimated using a parametric bootstrap. Illustrative results suggest that estimated exponential spectral risk measures obtained using such methods are quite precise in the presence of normally distributed losses.
    Keywords: limit orders, market orders, tail risks
    JEL: G15
    Date: 2011–06–24
    URL: http://d.repec.org/n?u=RePEc:ucd:wpaper:2007/46&r=rmg
  10. By: John Cotter (University College Dublin, Ireland); Kevin Dowd (The University of Nottingham, UK)
    Abstract: This paper examines the intra-day seasonality of transacted limit and market orders in the DEM/USD foreign exchange market. Empirical analysis of completed transactions data based on the Dealing 2000-2 electronic inter-dealer broking system indicates significant evidence of intraday seasonality in returns and return volatilities under usual market conditions. Moreover, analysis of realised tail outcomes supports seasonality for extraordinary market conditions across the trading day.
    Keywords: Value at Risk, Expected Shortfall, Spectral Risk Measures, Moments, Precision.
    JEL: G15
    Date: 2011–06–24
    URL: http://d.repec.org/n?u=RePEc:ucd:wpaper:2007/43&r=rmg
  11. By: Carlos Castro; Stijn Ferrari
    Abstract: This paper analyzes the measure of systemic importance ΔCoVaR proposed by Adrian and Brunnermeier (2009, 2010) within the context of a similar class of risk measures used in the risk management literature. Inaddition, we develop a series of testing procedures, based on ΔCoVaR, toidentify and rank the systemically important institutions. We stress the importance of statistical testing in interpreting the measure of systemic importance. An empirical application illustrates the testing procedures, using equity data for three European banks.
    Date: 2011–06–21
    URL: http://d.repec.org/n?u=RePEc:col:000092:008779&r=rmg
  12. By: John Cotter (University College Dublin, Ireland)
    Abstract: One stylized feature of financial volatility impacting the modeling process is long memory. This paper examines long memory for alternative risk measures, observed absolute and squared returns for Daily REITs and compares the findings for a non- REIT equity index. The paper utilizes a variety of tests for long memory finding evidence that REIT volatility does display persistence, in contrast to the actual return series. Trading volume is found to be strongly associated with long memory. The results do however suggest differences in the findings with regard to REITs in comparison to the broader equity sector which may be due to relatively thin trading during the sample period.
    Keywords: Long Memory, FGARCH, REITs
    Date: 2011–06–24
    URL: http://d.repec.org/n?u=RePEc:ucd:wpaper:2006/14&r=rmg
  13. By: Mario Genco (Centre for Industrial Studies (CSIL))
    Abstract: Cost-benefit analysis allows to assess in advance the performance of investment projects through the calculation of appropriate indices, such as the NPV, the IRR, the B/C ratio. Performance indicators are, however, affected by the uncertainty inherent in the exercise of forecasting the future values of the physical and economic parameters generated by the project. Probability distribution of the expected values of each performance indicator can be determined, e.g., through Montecarlo simulations of the CBA model. Derived from the simulated probability distribution, the paper, starting from the definition of the loss function in the statistical decision theory, proposes a set of risk indicators (Index of absolute risk, Index of internal relative risk, Index of generalized relative risk), which include a "weight" function that models the level of aversion against the expected loss of the performance indices by the person who will bear the project risk.
    Keywords: risk analysis, risk adversion, Montecarlo simulation, cost benefit analysis - rischio, avversione al rischio, simulazione Montecarlo, analisi costi benefici
    JEL: D81
    Date: 2011–04–01
    URL: http://d.repec.org/n?u=RePEc:mst:wpaper:201102&r=rmg
  14. By: John Cotter (University College Dublin, Ireland); Simon Stevenson (University College Dublin, Ireland)
    Abstract: This paper examines volatility in REITs using multivariate GARCH based model. The Multivariate VAR-GARCH technique documents the return and volatility linkages between REIT sub-sectors and also examines the influence of other US equity series. The motivation is for investors to incorporate time-varying volatility and correlations in their portfolio selection. The results illustrate the difference in results when higher frequency daily data is tested in comparison to the monthly data that has been commonly used in the existing literature. The linkages both within the REIT sector and between REITs and related sectors such as value stocks are weaker than commonly found in monthly studies. The broad market would appear to be more influential in the daily case.
    Date: 2011–06–24
    URL: http://d.repec.org/n?u=RePEc:ucd:wpaper:2005/17&r=rmg
  15. By: Tao Sun
    Abstract: This paper attempts to identify the indicators that can demonstrate the vulnerabilities in systemically important financial institutions. The paper finds that (i) indicators on leverage, liquidity, and business scope can help identify the differences between the intervened and non-intervened financial institutions during the subprime crisis; (ii) the expected default frequencies react positively to shocks to leverage, inflation, global financial stress, and global excess liquidity, and negatively to return on assets and equity prices; and (iii) leverage has been the most robust factor with a long-run causal effect on the expected default frequencies.
    Keywords: Banking crisis , Banking sector , Credit risk , Economic models , Financial institutions ,
    Date: 2011–05–09
    URL: http://d.repec.org/n?u=RePEc:imf:imfwpa:11/111&r=rmg
  16. By: Ojo, Marianne
    Abstract: As well as a consideration of the role contributed by national supervisors in the successful implementation and enforcement of standards, recommendations and regulations, the significance of clear and unambiguous mandates in enhancing communication between micro prudential supervisors (usually national financial supervisors and central banks) and macro prudential bodies which are responsible for writing the laws that are enforced by micro prudential supervisors, will be highlighted in this paper. This will incorporate a discussion on the advantages and disadvantages inherent in clear, explicit mandates – such a discussion necessitating a distinction between financial stability and monetary policy objectives. Furthermore, the role of credit ratings and their significance in influencing investor choices and judgments, will be considered as a means of highlighting how they contribute to the neglect of risks, exposures attributed to certain financial instruments, and ultimately, systemic risks which de stabilize the financial system.
    Keywords: European Systemic Risk Board; financial stability; credit ratings; Dodd Frank Act; Basel III; micro prudential supervision; risk weights; European Central Bank; counterparty risks; macro prudential arrangements; central banks; European Supervisory Authorities; monetary policy; risks
    JEL: D0 K2 E5 D8 E3
    Date: 2011–06–22
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:31777&r=rmg
  17. By: David Blake (city University London); John Cotter (University College Dublin, Ireland); Kevin Dowd (The University of Nottingham, UK)
    Abstract: This paper discusses the financial risks faced by the UK Pension Protection Fund (PPF) and what, if anything, it can do about them. It draws lessons from the regulatory regimes under which other financial institutions, such as banks and insurance companies, operate and asks why pension funds are treated differently. It also reviews the experience with other government-sponsored insurance schemes, such as the US Pension Benefit Guaranty Corporation, upon which the PPF is modelled. We conclude that the PPF will live under the permanent risk of insolvency as a consequence of the moral hazard, adverse selection, and, especially, systemic risks that it faces.
    Date: 2011–06–24
    URL: http://d.repec.org/n?u=RePEc:ucd:wpaper:2006/15&r=rmg

General information on the NEP project can be found at https://nep.repec.org. For comments please write to the director of NEP, Marco Novarese at <director@nep.repec.org>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.