nep-rmg New Economics Papers
on Risk Management
Issue of 2016‒04‒09
eight papers chosen by

  1. On the properties of the Lambda value at risk: robustness, elicitability and consistency By Matteo Burzoni; Ilaria Peri; Chiara Maria Ruffo
  2. Time-varying risk premium in large cross-sectional equity datasets By Ossola, Elisa; Gagilardini, Patrick; Scaillet, Olivier
  3. Systemic Risks in CCP Networks By Russell Barker; Andrew Dickinson; Alex Lipton; Rajeev Virmani
  4. Expected utility for nonstochastic risk By Ivanenko, Victor; Pasichnichenko, Illia
  5. Parisian ruin for a refracted L\'evy process By Mohamed Amine Lkabous; Irmina Czarna; Jean-Fran\c{c}ois Renaud
  6. The Risk Anomaly Tradeoff of Leverage By Malcolm Baker; Mathias F. Hoeyer; Jeffrey Wurgler
  7. Robust Optimization of Credit Portfolios By Agostino Capponi; Lijun Bo
  8. Estimating the Spot Covariation of Asset Prices – Statistical Theory and Empirical Evidence By Markus Bibinger; Nikolaus Hautsch; Peter Malec; Markus Reiss

  1. By: Matteo Burzoni; Ilaria Peri; Chiara Maria Ruffo
    Abstract: Recently, financial industry and regulators have enhanced the debate on the good properties of a risk measure. A fundamental issue is the evaluation of the quality of a risk estimation. On one hand a backtesting procedure is desirable for assessing the accuracy of such an estimation and this can be naturally achieved by elicitable risk measures. For the same objective an alternative approach has been introduced by Davis (2013) through the so-called consistency property. On the other hand a risk estimation should be less sensitive with respect to small changes in the available data set and exhibit qualitative robustness. A new risk measure, the Lambda value at risk (Lambda VaR), has been recently proposed by Frittelli et al. (2014), as a generalization of VaR, with the ability of discriminating the risk among P&L distributions with different tail behaviour. In this article, we show that Lambda VaR also satisfies the properties of robustness, elicitability and consistency under some conditions.
    Date: 2016–03
  2. By: Ossola, Elisa; Gagilardini, Patrick; Scaillet, Olivier
    Abstract: We develop an econometric methodology to infer the path of risk premia from a large unbalanced panel of individual stock returns. We estimate the time-varying risk premia implied by conditional linear asset pricing models where the conditioning includes both instruments common to all assets and asset specific instruments. The estimator uses simple weighted two-pass cross-sectional regressions, and we show its consistency and asymptotic normality under increasing cross-sectional and time series dimensions. We address consistent estimation of the asymptotic variance by hard thresholding, and testing for asset pricing restrictions induced by the no-arbitrage assumption. We derive the restrictions given by a continuum of assets in a multi-period economy under an approximate factor structure robust to asset repackaging. The empirical analysis on returns for about ten thousands US stocks from July 1964 to December 2009 shows that risk premia are large and volatile in crisis periods. They exhibit large positive and negative strays from time-invariant estimates, follow the macroeconomic cycles, and do not match risk premia estimates on standard sets of portfolios. The asset pricing restrictions are rejected for a conditional four-factor model capturing market, size, value and momentum effects.
    JEL: C12 C13 C23 C51 C52 G12
    Date: 2015
  3. By: Russell Barker; Andrew Dickinson; Alex Lipton; Rajeev Virmani
    Abstract: We propose a model for the credit and liquidity risks faced by clearing members of Central Counterparty Clearing houses (CCPs). This model aims to capture the features of: gap risk; feedback between clearing member default, market volatility and margining requirements; the different risks faced by various types of market participant and the changes in margining requirements a clearing member faces as the system evolves. By considering the entire network of CCPs and clearing members, we investigate the distribution of losses to default fund contributions and contingent liquidity requirements for each clearing member; further, we identify wrong-way risks between defaults of clearing members and market turbulence.
    Date: 2016–04
  4. By: Ivanenko, Victor; Pasichnichenko, Illia
    Abstract: The world of random phenomena exceeds the domain of the classical probability theory. In the general case the description of randomness requires a specific set of probability distributions (which is called statistical regularity) rather than a singe distribution. Such statistical regularity arises as a limit of relative frequencies. This approach to randomness allows to generalize the expected utility theory in order to cover the decision problems under nonstochastic random events. Applying the von Neumann-Morgenstern utility theorem, we derive the maxmin expected utility representation for statistical regularities. The derivation is based on the axiom of the preference for stochastic risk, i.e. the decision maker wishes to reduce the set of probability distributions to a single one.
    Keywords: expected utility, risk, mass phenomena, statistical regularity, nonstochastic randomness, multiple prior
    JEL: C10 D81
    Date: 2016–04–01
  5. By: Mohamed Amine Lkabous; Irmina Czarna; Jean-Fran\c{c}ois Renaud
    Abstract: In this paper, we investigate Parisian ruin for a L\'evy surplus process with an adaptive premium rate, namely a refracted L\'evy process. More general Parisian boundary-crossing problems with a deterministic implementation delay are also considered. Our main contribution is a generalization of the result in Loeffen et al. (2013) for the probability of Parisian ruin of a standard L\'evy insurance risk process. Despite the more general setup considered here, our main result is as compact and has a similar structure. Examples are provided.
    Date: 2016–03
  6. By: Malcolm Baker; Mathias F. Hoeyer; Jeffrey Wurgler
    Abstract: Higher-beta and higher-volatility equities do not earn commensurately higher returns, a pattern known as the risk anomaly. In this paper, we consider the possibility that the risk anomaly represents mispricing and develop its implications for corporate leverage. The risk anomaly generates a simple tradeoff theory: At zero leverage, the overall cost of capital falls as leverage increases equity risk, but as debt becomes riskier the marginal benefit of increasing equity risk declines. We show that there is an interior optimum and that it is reached at lower leverage for firms with high asset risk. Empirically, the risk anomaly tradeoff theory and the traditional tradeoff theory are both consistent with the finding that firms with low-risk assets choose higher leverage. More uniquely, the risk anomaly theory helps to explain why leverage is inversely related to systematic risk, holding constant total risk; why leverage is inversely related to upside risk, not just downside risk; why numerous firms maintain low or zero leverage despite high marginal tax rates; and, why other firms maintain high leverage despite little tax benefit.
    JEL: G32
    Date: 2016–03
  7. By: Agostino Capponi; Lijun Bo
    Abstract: We introduce a dynamic credit portfolio framework where optimal investment strategies are robust against misspecifications of the reference credit model. The risk-averse investor models his fear of credit risk misspecification by considering a set of plausible alternatives whose expected log likelihood ratios are penalized. We provide an explicit characterization of the optimal robust bond investment strategy, in terms of default state dependent value functions associated with the max-min robust optimization criterion. The value functions can be obtained as the solutions of a recursive system of HJB equations. We show that each HJB equation is equivalent to a suitably truncated equation admitting a unique bounded regular solution. The truncation technique relies on estimates for the solution of the master HJB equation that we establish.
    Date: 2016–03
  8. By: Markus Bibinger; Nikolaus Hautsch; Peter Malec; Markus Reiss
    Abstract: We propose a new estimator for the spot covariance matrix of a multi-dimensional continuous semimartingale log asset price process which is subject to noise and non-synchronous observations. The estimator is constructed based on a local average of block-wise parametric spectral covariance estimates. The latter originate from a local method of moments (LMM) which recently has been introduced by Bibinger et al. (2014). We extend the LMM estimator to allow for autocorrelated noise and propose a method to adaptively infer the autocorrelations from the data. We prove the consistency and asymptotic normality of the proposed spot covariance estimator. Based on extensive simulations we provide empirical guidance on the optimal implementation of the estimator and apply it to high-frequency data of a cross-section of NASDAQ blue chip stocks. Employing the estimator to estimate spot covariances, correlations and betas in normal but also extreme-event periods yields novel insights into intraday covariance and correlation dynamics. We show that intraday (co-)variations (i) follow underlying periodicity patterns, (ii) reveal substantial intraday variability associated with (co-)variation risk, (iii) are strongly serially correlated, and (iv) can increase strongly and nearly instantaneously if new information arrives.
    Keywords: local method of moments, spot covariance, smoothing, intraday (co-)variation risk
    JEL: C58 C14 C32
    Date: 2014–10–07

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