New Economics Papers
on Risk Management
Issue of 2010‒11‒27
nine papers chosen by

  1. Forecasting Short-Run Inflation Volatility using Futures Prices: An Empirical Analysis from a Value at Risk Perspective By Guillermo Benavides
  2. Reduced form models of bond portfolios By Matti Koivu; Teemu Pennanen
  3. Dangers of Bilateral Counterparty Risk: the fundamental impact of closeout conventions By Damiano Brigo; Massimo Morini
  4. Extreme Returns: The Case of Currencies By Carol Osler; Tanseli Savaser
  5. A Non-parametric Approach to Incorporating Incomplete Workouts Into Loss Given Default Estimates By Rapisarda, Grazia; Echeverry, David
  6. Challenges to Solvency II Reform in Insurance Industry By Ramosaj, Berim
  7. Multidimensional dynamic risk measure via conditional g-expectation By Yuhong Xu
  8. Networks of Economic Market Interdependence and Systemic Risk By Dion Harmon; Blake Stacey; Yavni Bar-Yam; Yaneer Bar-Yam
  9. Alternative Asymmetric Stochastic Volatility Models By Manabu Asai; Michael McAleer

  1. By: Guillermo Benavides
    Abstract: In this research paper ARCH-type models are applied in order to estimate the Value-at-Risk (VaR)of an inflation-index futures portfolio for several time-horizons. The empirical analysis is carried out for Mexican inflation-indexed futures traded at the Mexican Derivatives Exchange (MEXDER). To analyze the VaR with time horizons of more than one trading day bootstrapping simulations were applied. The results show that these models are relatively accurate for time horizons of one trading day. However, the volatility persistence of ARCH-type models is reflected with relatively high VaR estimates for longer time horizons. These results have implications for short-term inflation forecasts. By estimating confidence intervals in the VaR, it is possible to have certain confidence about the future range of inflation (or extreme inflation values) for a specified time horizon.
    Keywords: Bootstrapping, inflation, inflation-indexed futures, Mexico, value at risk, volatility persistence.
    JEL: C15 C22 C53 E31 E37
    Date: 2010–10
  2. By: Matti Koivu; Teemu Pennanen
    Abstract: We derive simple return models for several classes of bond portfolios. With only one or two risk factors our models are able to explain most of the return variations in portfolios of fixed rate government bonds, inflation linked government bonds and investment grade corporate bonds. The underlying risk factors have natural interpretations which make the models well suited for risk management and portfolio design.
    Date: 2010–11
  3. By: Damiano Brigo; Massimo Morini
    Abstract: We analyze the practical consequences of the bilateral counterparty risk adjustment. We point out that past literature assumes that, at the moment of the first default, a risk-free closeout amount will be used. We argue that the legal (ISDA) documentation suggests in many points that a substitution closeout should be used. This would take into account the risk of default of the survived party. We show how the bilateral counterparty risk adjustment changes strongly when a substitution closeout amount is considered. We model the two extreme cases of default independence and co-monotonicity, which highlight pros and cons of both risk free and substitution closeout formulations, and allow us to interpret the outcomes as dramatic consequences on default contagion. Finally, we analyze the situation when collateral is present.
    Date: 2010–11
  4. By: Carol Osler (International Business School, Brandeis University); Tanseli Savaser (Department of Economics, Williams College)
    Abstract: This paper investigates how active price-contingent trading contributes to extreme returns even in the absence of news. Price-contingent trading, which is common across financial markets, includes algorithmic trading, technical trading, and dynamic option hedging. The paper highlights four properties of such trading that increase the frequency of extreme returns, and then estimates the relative of these properties using data from the foreign exchange market. The four key properties we consider are: (1) high kurtosis in the distribution of order sizes; (2) clustering of trades within the day; (3) clustering of trades at certain prices; and (4) positive and negative feedback between trading and returns. Calibrated simulations indicate that interactions among these properties are at least as important as any single one. Among individual properties, the orders’ size distribution and feedback effects have the strongest influence. Price-contingent trading could account for over half of realized excess kurtosis in currency returns.
    Keywords: Crash, Fat Tails,Kurtosis,Exchange Rates,Order Flow,High-Frequency,Microstructure,Jump Process,Value-At-Risk,Risk Management
    JEL: G1 F3
    Date: 2010–11
  5. By: Rapisarda, Grazia; Echeverry, David
    Abstract: When estimating Loss Given Default (LGD) parameters using a workout approach, i.e. discounting cash flows over the workout period, the problem arises of how to take into account partial recoveries from incomplete work-outs. The simplest approach would see LGD based on complete recovery profiles only. Whilst simple, this approach may lead to data selection bias, which may be at the basis of regulatory guidance requiring the assessment of the relevance of incomplete workouts to LGD estimation. Despite its importance, few academic contributions have covered this topic. We enhance this literature by developing a non-parametric estimator that -under certain distributional assumptions on the recovery profiles- aggregates complete and incomplete workout data to produce unbiased and more efficient estimates of mean LGD than those obtained from the estimator based on resolved cases only. Our estimator is appropriate in LGD estimation for wholesale portfolios, where the exposure-weighted LGD estimators available in the literature would not be applicable under Basel II regulatory guidance.
    Keywords: Credit risk; bank loans; loss-given-default; LGD; incomplete observations; mortality curves
    JEL: C14 G32
    Date: 2010–11–16
  6. By: Ramosaj, Berim
    Abstract: Insurance Industry is going through a very important stage of its transformation - the transition from the classical system of management into a risk-based management. These changes were launched in Europe by international organizations which deal with the development of the necessary infrastructure for a better-managed industry and with a proper legal infrastructure through different European directives in insurance area. These changes have intensity in the finalization of the general technical, legal and structural infrastructure, which would be developed based on three pillars. The consequences of the current financial crisis as well as its impact towards the implementation of Insolvency II have not been analyzed yet. Its implementation, perhaps, would be an adequate response in facing this crisis.
    Keywords: Solvency II; insurance industry; insurance reform; risk-based management
    JEL: G11 G23 G30 G20 G22 G38 G18 G32 G28 G10
    Date: 2010–11–16
  7. By: Yuhong Xu
    Abstract: This paper studies multidimensional dynamic risk measure induced by conditional $g$-expectation. A notion of multidimensional $g$-expectation is proposed to provide a multidimensional version of nonlinear expectations. By a technical result on explicit expressions for the comparison theorem, uniqueness theorem and viability on a rectangle of solutions to multidimensional backward stochastic differential equations, some necessary and sufficient conditions are given for the constancy, monotonicity, positivity, homogeneity and translatability properties of multidimensional conditional $g$-expectation and multidimensional dynamic risk measure; we prove that a multidimensional dynamic $g$-risk measure is nonincreasingly convex if and only if the generator $g$ satisfies a quasi-monotone increasingly convex condition. A general dual representation is also given for multidimensional dynamic convex $g$-risk measure in which the penalty term is expressed more precisely. Several examples are presented to show how this multidimensional approach is applied to a class of agent-based model and to the problem of risk allocation.
    Date: 2010–11
  8. By: Dion Harmon; Blake Stacey; Yavni Bar-Yam; Yaneer Bar-Yam
    Abstract: The dynamic network of relationships among corporations underlies cascading economic failures including the current economic crisis, and can be inferred from correlations in market value fluctuations. We analyze the time dependence of the network of correlations to reveal the changing relationships among the financial, technology, and basic materials sectors with rising and falling markets and resource constraints. The financial sector links otherwise weakly coupled economic sectors, particularly during economic declines. Such links increase economic risk and the extent of cascading failures. Our results suggest that firewalls between financial services for different sectors would reduce systemic risk without hampering economic growth.
    Date: 2010–11
  9. By: Manabu Asai; Michael McAleer (University of Canterbury)
    Abstract: The stochastic volatility model usually incorporates asymmetric effects by introducing the negative correlation between the innovations in returns and volatility. In this paper, we propose a new asymmetric stochastic volatility model, based on the leverage and size effects. The model is a generalization of the exponential GARCH (EGARCH) model of Nelson (1991). We consider categories for asymmetric effects, which describes the difference among the asymmetric effect of the EGARCH model, the threshold effects indicator function of Glosten, Jagannathan and Runkle (1992), and the negative correlation between the innovations in returns and volatility. The new model is estimated by the efficient importance sampling method of Liesenfeld and Richard (2003), and the finite sample properties of the estimator are investigated using numerical simulations. Four financial time series are used to estimate the alternative asymmetric SV models, with empirical asymmetric effects found to be statistically significant in each case. The empirical results for S&P 500 and Yen/USD returns indicate that the leverage and size effects are significant, supporting the general model. For TOPIX and USD/AUD returns, the size effect is insignificant, favoring the negative correlation between the innovations in returns and volatility. We also consider standardized t distribution for capturing the tail behavior. The results for Yen/USD returns show that the model is correctly specified, while the results for three other data sets suggest there is scope for improvement.
    Keywords: Stochastic volatility; asymmetric effects; leverage; threshold; indicator function; importance sampling; numerical simulations
    Date: 2010–11–01

General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. 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.