New Economics Papers
on Risk Management
Issue of 2012‒01‒10
seven papers chosen by

  1. Dependent default and recovery: MCMC study of downturn LGD credit risk model By Pavel V. Shevchenko; Xiaolin Luo
  2. Real Output Costs of Financial Crises: A Loss Distribution Approach By Daniel Kapp; Marco Vega
  3. Saddlepoint methods in portfolio theory By Richard J Martin
  4. Risk and Return: Long-Run Relationships, Fractional Cointegration, and Return Predictability By Tim Bollerslev; Daniela Osterrieder; Natalia Sizova; George Tauchen
  5. Do investors care about noise trader risk? By Francisca Beer; Mohamad Watfa; Mohamed Zouaoui
  6. Credit rating changes’ impact on banks: evidence from the US banking industry By Apergis, Nicholas; Payne, James E.; Tsoumas, Chris
  7. Resilience to Contagion in Financial Networks By Hamed Amini; Rama Cont; Andreea Minca

  1. By: Pavel V. Shevchenko; Xiaolin Luo
    Abstract: There is empirical evidence that recovery rates tend to go down just when the number of defaults goes up in economic downturns. This has to be taken into account in estimation of the capital against credit risk required by Basel II to cover losses during the adverse economic downturns; the so-called "downturn LGD" requirement. This paper presents estimation of the LGD credit risk model with default and recovery dependent via the latent systematic risk factor using Bayesian inference approach and Markov chain Monte Carlo method. This approach allows joint estimation of all model parameters and latent systematic factor, and all relevant uncertainties. Results using Moody's annual default and recovery rates for corporate bonds for the period 1982-2010 show that the impact of parameter uncertainty on economic capital can be very significant and should be assessed by practitioners.
    Date: 2011–12
  2. By: Daniel Kapp; Marco Vega
    Abstract: The adverse effects of financial crises in terms of output losses or output growth below its potential can be treated like losses from catastrophic events which have a low likelihood but a large impact in the event that they occur. We therefore analyze GDP losses in terms of frequency (number of loss events per period) and severity (loss per occurrence). Crises' frequency, severity, and the associated global output losses over periods of five years are identified on the basis of Laeven et al. (2008). Applying the Loss Distribution Approach used in insurance and operational risk theory and practice, we estimate a multi-country aggregate GDP loss distribution and thus approximate the conditional losses in the event of financial crises. The analysis of losses produced in the paper suggests that the LDA approach is a useful tool in discussions about the existence and capital requirements of a potential insurance against the risk of financial crises at the aggregate level.
    Date: 2012–01
  3. By: Richard J Martin
    Abstract: We discuss the use of saddlepoint methods in the analysis of portfolios, with particular reference to credit portfolios. The objective is to proceed from a model of the loss distribution, given through probabilities, correlations and the like, to an analytical approximation of the distribution. Once this is done we show how to derive the so-called risk contributions which are the derivatives of risk measures, such as a given quantile (VaR) or expected shortfall, to the allocations in the underlying assets. These show, informally, where the risk is coming from, and also indicate how to go about optimising the portfolio.
    Date: 2011–12
  4. By: Tim Bollerslev (Duke University and CREATES); Daniela Osterrieder (Aarhus University and CREATES); Natalia Sizova (Rice University); George Tauchen (Duke University and CREATES)
    Abstract: The dynamic dependencies in financial market volatility are generally well described by a long-memory fractionally integrated process. At the same time, the volatility risk premium, defined as the difference between the ex-post realized volatility and the market’s ex-ante expectation thereof, tends to be much less persistent and well described by a short-memory process. Using newly available intraday data for the S&P 500 and the VIX volatility index, coupled with frequency domain inference procedures that allow us to focus on specific parts of the spectra, we show that the existing empirical evidence based on daily and coarser sampled data carries over to the high-frequency setting. Guided by these empirical findings, we formulate and estimate a fractionally cointegrated VAR model for the two high-frequency volatility series and the corresponding high-frequency S&P 500 returns. Consistent with the implications from a stylized equilibrium model that directly links the realized and expected volatilities to returns, we show that the equilibrium variance risk premium estimated with the intraday data within the fractionally cointegrated system results in non-trivial return predictability over longer interdaily and monthly horizons. These results in turn suggest that much of the existing literature seeking to establish a risk-return tradeoff relationship between expected returns and expected volatilities may be misguided, and that the variance risk premium provides a much better proxy for the true economic uncertainty that is being rewarded by the market.
    Keywords: High-frequency data, realized volatility, options implied volatility, variance risk premium, fractional integration, long-memory, fractional cointegration, equilibrium asset pricing, return predictability.
    JEL: C22 C32 C51 C52 G12 G13 G14
    Date: 2011–12–21
  5. By: Francisca Beer (California State University of San Bernardino); Mohamad Watfa (ITIC Paris); Mohamed Zouaoui (University of Franche-Comté and LEG-UMR 5118)
    Abstract: The link between investor sentiment and asset valuation is at the centre of a long-running debate in behavioral finance. Using a new composite sentiment indicator, we show that the conventional risk does not explain the abnormal returns of portfolios most sensitive to the sentiment factor. Our result supports the existence of a sentiment risk valued by financial markets. We also find that the firms more impacted by the sentiment risk correspond to difficult to arbitrage and hard to value stocks, e.g. small stocks, growth stocks, young stocks, unprofitable stocks, lower dividend-paying stocks, intangible stocks and high volatility stocks.
    Keywords: investor sentiment;asset valuation;behavioral finance;abnormal returns of portfolios.
    JEL: G11 G12
    Date: 2011–10
  6. By: Apergis, Nicholas; Payne, James E.; Tsoumas, Chris
    Abstract: This study examines the impact of credit rating upgrades and downgrades on six comprehensive banks’ asset classes, profitability, leverage and size using data from the Federal Deposit Insurance Corporation’s call reports and Bloomberg over the period 1989-2008. In summary, the results suggest that a downgrade has a lasting and relatively more severe impact on banks than an upgrade; however, downgraded banks do not seem to effectively reduce their appetite for risk over a longer horizon. It seems that the role of credit rating agencies as an integral part of banks’ prudential supervision through market discipline is, in a longer horizon, overstated.
    Keywords: Credit rating changes; banks; market discipline
    JEL: G28 C21 G21
    Date: 2011–12
  7. By: Hamed Amini; Rama Cont; Andreea Minca
    Abstract: Propagation of balance-sheet or cash-flow insolvency across financial institutions may be modeled as a cascade process on a network representing their mutual exposures. We derive rigorous asymptotic results for the magnitude of contagion in a large financial network and give an analytical expression for the asymptotic fraction of defaults, in terms of network characteristics. Our results extend previous studies on contagion in random graphs to inhomogeneous directed graphs with a given degree sequence and arbitrary distribution of weights. We introduce a criterion for the resilience of a large financial network to the insolvency of a small group of financial institutions and quantify how contagion amplifies small shocks to the network. Our results emphasize the role played by "contagious links" and show that institutions which contribute most to network instability in case of default have both large connectivity and a large fraction of contagious links. The asymptotic results show good agreement with simulations for networks with realistic sizes.
    Date: 2011–12

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