nep-rmg New Economics Papers
on Risk Management
Issue of 2016‒05‒08
thirteen papers chosen by
Stan Miles
Thompson Rivers University

  1. Tracking Variation in Systemic Risk at US Banks During 1974-2013 By Armen Hovakimian; Edward Kane,; Luc Laeven
  2. Evaluating Systemic Risk using Bank Default Probabilities in Financial Networks By Sergio Rubens Stancato de Souza; Thiago Christiano Silva; Benjamin Miranda Tabak; Solange Maria Guerra
  3. Extreme Concurrent Portfolio Losses in Credit Risk By Joachim Sicking; Thomas Guhr; Rudi Sch\"afer
  4. The dynamic Black-Litterman approach to asset allocation By Harris, Richard D F; Stoja, Evarist; Tan, Linzhi
  5. Entropy and credit risk in highly correlated markets By Sylvia Gottschalk
  6. Heterogeneity and the formation of risk-sharing coalitions By Fernando Jaramillo; Hubert Kempf; Fabien Moizeau
  7. The Life Insurance Industry and Systemic Risk: A Bond Market Perspective By Paulson, Anna L.; Rosen, Richard J.
  8. Density forecasting comparison of volatility models By Leopoldo Catania; Nima Nonejad
  9. Capital Pricing in Margin Periods of Risk and Repo KVA By Wujiang Lou
  10. A comparative analysis of tools to limit the procyclicality of initial margin requirements By Murphy, David; Vasios, Michalis; Vause, Nicholas
  11. A General Optimal Investment Model in the Presence of Background Risk By Alghalith, Moawia; Guo, Xu; Wong, Wing-Keung; Zhu, Lixing
  12. On the Surprising Explanatory Power of Higher Realized Moments in Practice By Keren Shen; Jianfeng Yao; Wai Keung Li
  13. Capital Requirements, Risk Shifting and the Mortgage Market By Uluc, Arzu; Wieladek, Tomasz

  1. By: Armen Hovakimian (Baruch College); Edward Kane, (Boston College); Luc Laeven (European Central Bank)
    Abstract: This paper proposes a theoretically based and easy-to-implement way to measure the systemic risk of financial institutions using publicly available accounting and stock market data. The measure models the credit enhancement taxpayers provide to individual banks in the Merton tradition (1974) as a combination put option for the deep tail of bank losses and a knock-in stop-loss call on bank assets. This model expresses the value of taxpayer loss exposure from a string of defaults as the value of this combination option written on the portfolio of industry assets. The exercise price of the call is the face value of the debt of the entire sector. We conceive of an individual bank’s systemic risk as its contribution to the value of this sectorwide option on the financial safety net. To the extent that authorities are slow to see bank losses or reluctant to exercise the call, the government itself becomes a secondary source of systemic risk. We apply our model to quarterly data over the period 1974-2013. The model indicates that systemic risk reached unprecedented highs during the financial crisis years 2008- 2009, and that bank size, leverage, and asset risk are key drivers of systemic risk.
    JEL: G01 G28
    Date: 2015–08
  2. By: Sergio Rubens Stancato de Souza; Thiago Christiano Silva; Benjamin Miranda Tabak; Solange Maria Guerra
    Abstract: In this paper, we propose a novel methodology to measure systemic risk in networks composed of financial institutions. Our procedure combines the impact effects obtained from stress measures that rely on feedback centrality properties with default probabilities of institutions. We also present new heuristics for designing feasible and relevant stress-testing scenarios that can subside regulators in financial system surveillance tasks. We develop a methodology to extract banking communities and show that these communities are mostly composed of non-large banks and have a relevant effect on systemic risk. This finding renders these communities objects of interest for supervisory activities besides SIFIs and large banks. Finally, our results provide insights and guidelines that can be useful for policymaking
    Date: 2016–04
  3. By: Joachim Sicking; Thomas Guhr; Rudi Sch\"afer
    Abstract: Within the framework of the Merton model, we consider the problem of concurrent portfolio losses in two non-overlapping credit portfolios. In order to explore the full statistical dependence structure, we estimate the pairwise copulas of such portfolio losses. Instead of a Gaussian dependence, we typically find a strong asymmetry in the copulas. Concurrent large portfolio losses are much more likely than small ones. Studying the dependences of these losses as a function of portfolio size, we moreover reveal that not only large portfolios of thousands of contracts, but also medium-sized and small ones with only a few dozens of contracts exhibit notable loss correlations. Anticipated idiosyncratic effects turn out to be negligible in almost every realistic setting. These are troublesome insights not only for investors in structured fixed-income products, but particularly for the stability of the financial sector.
    Date: 2016–04
  4. By: Harris, Richard D F (Xfi Centre for Finance and Investment, University of Exeter); Stoja, Evarist (School of Economics, Finance and Management, University of Bristol); Tan, Linzhi (Division of Accounting and Finance, Nottingham Business School, Nottingham Trent University.)
    Abstract: We generalise the Black-Litterman (BL) portfolio management framework to incorporate time-variation in the conditional distribution of returns in the asset allocation process. We evaluate the performance of the dynamic BL model using both standard performance ratios as well as other measures that are designed to capture tail risk in the presence of non-normally distributed asset returns. We find that dynamic BL model outperforms a range of different benchmarks. Moreover, we show that the choice of volatility model has a considerable impact on the performance of the dynamic BL model.
    Keywords: Black-Litterman model; multivariate conditional volatility; portfolio optimization; non-normality; tail risk
    JEL: C22 C53 G11
    Date: 2016–04–22
  5. By: Sylvia Gottschalk
    Abstract: We compare two models of corporate default by calculating the Jeffreys-Kullback-Leibler divergence between their predicted default probabilities when asset correlations are either high or low. Our main results show that the divergence between the two models increases in highly correlated, volatile, and large markets, but that it is closer to zero in small markets, when asset correlations are low and firms are highly leveraged. These findings suggest that during periods of financial instability the single-and multi-factor models of corporate default will generate increasingly inconsistent predictions.
    Date: 2016–04
  6. By: Fernando Jaramillo (Universidad del Rosario - Facultad de Economia); Hubert Kempf (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics); Fabien Moizeau (CREM - Centre de Recherche en Economie et Management - UR1 - Université de Rennes 1 - Université de Caen Basse-Normandie - CNRS - Centre National de la Recherche Scientifique)
    Abstract: We study the relationship between the distribution of individuals' attributes over the pop-ulation and the extent of risk sharing in a risky environment. We consider a society where individuals voluntarily form risk-sharing groups in the absence of financial markets. We obtain a partition of society into distinct coalitions leading to partial risk sharing. When individuals differ only with respect to risk, the partition is homophily-based: the less risky agents congreg-ate together and reject more risky ones into other coalitions. The distribution of risk affects the number and size of these coalitions. It turns out that individuals may pay a lower risk premium in more risky societies. We show that a higher heterogeneity in risk leads to a lower degree of partial risk sharing. The case of heterogenous risk aversion generates similar results. The empirical evidence on partial risk sharing can be understood when the endogenous partition of society into risk-sharing coalitions is taken into account.
    Keywords: Risk Sharing,Group Membership
    Date: 2015–05
  7. By: Paulson, Anna L. (Federal Reserve Bank of Chicago); Rosen, Richard J. (Federal Reserve Bank of Chicago)
    Abstract: The 2008 financial crisis brought a focus on the potential for a large insurance firm to contribute to systemic risk. Among the concerns raised was that a negative shock to insurers could lead to a ‘fire sale’ of corporate bonds, a market where insurers are among the largest participants. This paper discusses the existing evidence on life insurance firms and systemic risk, with a focus on the investment grade corporate bond market. We provide some tentative evidence that life insurers tend to absorb liquidity risk by purchasing bonds when the bonds are less liquid than average. However, we do not find evidence that insurers increased bond purchases specifically during the financial crisis leaving open the question of whether insurers would play a stabilizing role in a future crisis.
    Keywords: Insurance; Bond; Over-the-Counter (OTC); Trading
    JEL: G12 G14 G22 G24
    Date: 2016–03–04
  8. By: Leopoldo Catania; Nima Nonejad
    Abstract: We compare the predictive ability of several volatility models for a long series of weekly log-returns of the Dow Jones Industrial Average Index from 1902 to 2016. Our focus is particularly on predicting one and multi-step ahead conditional and aggregated conditional densities. Our set of competing models includes: Well-known GARCH specifications, Markov switching GARCH, sempiparametric GARCH, Generalised Autoregressive Score (GAS), the plain stochastic volatility (SV) as well as its more flexible extensions such as SV with leverage, in-mean effects and Student-t distributed errors. We find that: (i) SV models generally outperform the GARCH specifications, (ii): The SV model with leverage effect provides very strong out-of-sample performance in terms of one and multi-steps ahead density prediction, (iii) Differences in terms of Value-at-Risk (VaR) predictions accuracy are less evident. Thus, our results have an important implication: the best performing model depends on the evaluation criterion
    Date: 2016–05
  9. By: Wujiang Lou
    Abstract: The presence of hedging errors is practically a norm of derivatives businesses. Using the unhedgeable gap risk during a margin period of risk as a starting point, this article introduces a reserve capital approach to the hedging error and its inclusion in derivatives pricing and valuation. Specifically, we define economic capital associated with the gap risk hedging error and build the cost of capital into the Black-Scholes-Merton option pricing framework. An extended partial differential equation is derived, showing terms for expected gap loss and economic capital charge, corresponding to capital valuation adjustment--KVA. For a repurchase agreement, economic capital is computed under a double-exponential jump-diffusion model, either estimated from historical data or calibrated to options smile. We find that the expected loss of a repo is very small and that cost of economic capital is the dominant component of the repo pricing spread. A repo therefore constitutes an ideal case to study economic capital and its valuation impact. The approach taken can be extended into margined OTC derivatives and more generally derivatives in incomplete markets.
    Date: 2016–04
  10. By: Murphy, David (Bank of England); Vasios, Michalis (Bank of England); Vause, Nicholas (Bank of England)
    Abstract: The requirement to post initial margin on derivatives transactions is a key feature of the post-crisis reforms of the OTC derivatives markets. Initial margin requirements are usually determined by risk-based models. These models typically require increased margin in stressed conditions: they are procyclical. This procyclicality causes a liquidity burden on market participants which sometimes falls when they are least able to bear it. In this paper we study a variety of tools which have been proposed to mitigate the procyclicality of initial margin requirements. Three of these tools are proposed in European regulation; the other two are new proposals which offer attractive procyclicality mitigation features. The behaviour of all five tools is studied in a simulation framework. We examine the extent to which each tool mitigates procyclicality, and at what cost in demanding unnecessary margin compared to a benchmark unmitigated model. Our findings indicate that all of the tools are useful in mitigating procyclicality to some extent, but that the optimal calibration of each tool in a particular situation depends on the relative weights placed by the modeller on the objectives of minimizing procyclicality on the one hand and minimizing undesirable overmargining in periods of low volatility on the other. This suggests that it may be appropriate to consider moving from tools-based procyclicality regulation to one based on the desired outcomes.
    Keywords: Central counterparty; central clearing; initial margin; margin models; OTC derivatives; procyclicality
    JEL: G17
    Date: 2016–04–22
  11. By: Alghalith, Moawia; Guo, Xu; Wong, Wing-Keung; Zhu, Lixing
    Abstract: In this paper we present two dynamic models of background risk. We first present a stochastic factor model with an additive background risk. Thereafter, we present a dynamic model of simultaneous (correlated) multiplicative background risk and additive background risk. In so doing, we use a general utility function.
    Keywords: Stochastic factor model, utility function
    JEL: G11
    Date: 2016–04
  12. By: Keren Shen; Jianfeng Yao; Wai Keung Li
    Abstract: Realized moments of higher order computed from intraday returns are introduced in recent years. The literature indicates that realized skewness is an important factor in explaining future asset returns. However, the literature mainly focuses on the whole market and on the monthly or weekly scale. In this paper, we conduct an extensive empirical analysis to investigate the forecasting abilities of realized skewness and realized kurtosis towards individual stock's future return and variance in the daily scale. It is found that realized kurtosis possesses significant forecasting power for the stock's future variance. In the meanwhile, realized skewness is lack of explanatory power for the future daily return for individual stocks with a short horizon, in contrast with the existing literature.
    Date: 2016–04
  13. By: Uluc, Arzu; Wieladek, Tomasz
    Abstract: We study the effect of changes to bank-specific capital requirements on mortgage loan supply with a new loan-level dataset containing all mortgages issued in the UK between 2005Q2 and 2007Q2. We find that a rise of a 100 basis points in capital requirements leads to a 5.4% decline in individual loan size by bank. Loans issued by competing banks rise by roughly the same amount, which is indicative of credit substitution. Borrowers with an impaired credit history (verified income) are not (most) affected. This is consistent with origination of riskier loans to grow capital by raising retained earnings. No evidence for credit substitution of non-bank finance companies is found.
    Keywords: Capital requirements; credit substitution.; loan-level data; mortgage market
    JEL: G21 G28
    Date: 2016–04

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