nep-rmg New Economics Papers
on Risk Management
Issue of 2019‒01‒28
sixteen papers chosen by
Stan Miles
Thompson Rivers University

  1. Systemic Risk: Conditional Distortion Risk Measures By Jan Dhaene; Roger J. A. Laeven; Yiying Zhang
  2. Systemic Risk and the Great Depression By Sanjiv R. Das; Kris James Mitchener; Angela Vossmeyer
  3. Optimal risk management problem of natural resources: Application to oil drilling By M’hamed Gaîgi; Stéphane Goutte; Idris Kharroubi; Thomas Lim
  4. Banks Risk Taking and Creditors Bargaining Power By Heller, Yuval; Peleg Lazar, Sharon; Raviv, Alon
  5. Using Value-at-Risk for effective energy portfolio risk management By Halkos, George; Tsirivis, Apostolos
  6. Financial Portfolios based on Tsallis Relative Entropy as the Risk Measure By Sandhya Devi
  7. Bank Capital Regulation in a Zero Interest Environment By Döttling, Robin
  9. Shareholder risk-taking incentives in the presence of contingent capital By Fatouh, Mahmoud; McMunn, Ayowande
  10. Risk Factor Exposure Variation and Mutual Fund Performance By Manuel Ammann; Sebastian Fischer; Florian Weigert;
  11. A Risk-Sharing Framework of Bilateral Contracts By Junbeom Lee; Stephan Sturm; Chao Zhou
  12. Modeling Interactions between Risk, Time, and Social Preferences By Mark Schneider
  13. A Probabilistic Approach to Nonparametric Local Volatility By Martin Tegn\'er; Stephen Roberts
  14. Bank capital buffers in a dynamic model By Mankart, Jochen; Michaelides, Alexander; Pagratis, Spyros
  15. Have Hedge Funds Solved the Idiosyncratic Volatility Puzzle? By Turan G. Bali; Florian Weigert;
  16. A Simple Macro-Finance Measure of Risk Premia in Fed Funds Futures By Anthony M. Diercks; Uri Carl

  1. By: Jan Dhaene; Roger J. A. Laeven; Yiying Zhang
    Abstract: Conditional risk (co-risk) measures and risk contribution measures are increasingly used in quantitative risk analysis to evaluate the systemic risk that the failure (or loss) of a component spreads to other components or even to the entire system. Co-risk measures are conditional versions of measures usually employed to assess isolated risks, while risk contribution measures evaluate how a stress situation for one component incrementally affects another one. In this article, we introduce the rich classes of conditional distortion (CoD) risk measures and distortion risk contribution ($\Delta$CoD) measures, which contain the well-known conditional Value-at-Risk (CoVaR), conditional Expected Shortfall (CoES), and risk contribution measures in terms of the VaR and ES ($\Delta$CoVaR and $\Delta$CoES) as special cases. Sufficient conditions are presented for two random vectors to be ordered by the proposed CoD-risk measures and distortion risk contribution measures. These conditions are stated in terms of the stochastic dominance, increasing convex/concave, dispersive order, and excess wealth orders of the marginals under some assumptions of positive/negative stochastic dependence. Numerical examples are provided to illustrate our theoretical findings. This paper is the second in a triplet of papers on systemic risk by the same authors. In Dhaene et al. (2018), we introduce and analyze some new stochastic orders related to systemic risk. In a third (forthcoming) paper, we attribute systemic risk to the different participants in a given risky environment.
    Date: 2019–01
  2. By: Sanjiv R. Das; Kris James Mitchener; Angela Vossmeyer
    Abstract: We employ a unique hand-collected dataset and a novel methodology to examine systemic risk before and after the largest U.S. banking crisis of the 20th century. Our systemic risk measure captures both the credit risk of an individual bank as well as a bank’s position in the network. We construct linkages between all U.S. commercial banks in 1929 and 1934 so that we can measure how predisposed the entire network was to risk, where risk was concentrated, and how the failure of more than 9,000 banks during the Great Depression altered risk in the network. We find that the pyramid structure of the commercial banking system (i.e., the network’s topology) created more inherent fragility, but systemic risk was nevertheless fairly dispersed throughout banks in 1929, with the top 20 banks contributing roughly 18% of total systemic risk. The massive banking crisis that occurred between 1930{33 raised systemic risk per bank by 33% and increased the riskiness of the very largest banks in the system. We use Bayesian methods to demonstrate that when network measures, such as eigenvector centrality and a bank’s systemic risk contribution, are combined with balance sheet data capturing ex ante bank default risk, they strongly predict bank survivorship in 1934.
    Keywords: systemic risk, banking networks, Great Depression, Global Financial Crisis, marginal likelihood
    JEL: L10 N20
    Date: 2018
  3. By: M’hamed Gaîgi; Stéphane Goutte (LED - Université Paris 8); Idris Kharroubi (CEREMADE - CEntre de REcherches en MAthématiques de la DEcision - Université Paris-Dauphine - CNRS - Centre National de la Recherche Scientifique); Thomas Lim (ENSIIE - Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise)
    Abstract: The aim of this paper is to determine the optimal balance between extraction and storage of a natural resource (in particular crude oil) over time under a large array of environmental, operational and financial constraints for an infinite maturity time. We consider a manager that owns an oil field from which he can extract oil and decides to sell or store it. This operational strategy has to be carried out in continuous time and has to satisfy physical, operational, environmental and financial constraints such as storage capacity, crude oil spot price volatility, amount available for possible extraction or maximum amount that could be invested at time t for the extraction choice. The costs of storage and extraction are also taken into account to better fit the real market scenario. We solve the optimization problem of the manager's profit under this large array of constraints and provide an optimal strategy. We then examine different numerical scenarios to check the robustness and the corresponding optimal strategies given by our model, which is obtained by a numerical approach, with respect to different possible events related to the market , environmental policies or ecological constraints.
    Keywords: Ecological,Oil Storage,Oil Extraction,Environment,Optimal Strategy,Drilling
    Date: 2019–01–09
  4. By: Heller, Yuval; Peleg Lazar, Sharon; Raviv, Alon
    Abstract: We analyze the influence of unsecured debt (subdebt) on risk-shifting in banks whose assets are risky debt claims. We assume that the stockholders and subdebt-holders jointly decide on risk-shifting. We show that replacing part of the stock with subdebt: (1) leads to fewer risk-shifting events, but can lead to higher levels of risk, depending on the relative bargaining power, (2) does not change the level of risk-shifting when side payments are possible, and (3) may yield the surprising result that risk-shifting increases with tighter regulatory control.
    Keywords: Risk-taking, asset risk, financial institutions, stress test, leverage, bargaining
    JEL: G21 G28
    Date: 2019–01–10
  5. By: Halkos, George; Tsirivis, Apostolos
    Abstract: It is evident that the prediction of future variance through advanced GARCH type models is essential for an effective energy portfolio risk management. Still it fails to provide a clear view on the specific amount of capital that is at risk on behalf of the investor or any party directly affected by the price fluctuations of specific or multiple energy commodities. Thus, it is necessary for risk managers to make one further step, determining the most robust and effective approach that will enable them to precisely monitor and accurately estimate the portfolio’s Value-at-Risk, which by definition provides a good measure of the total actual amount at stake. Nevertheless, despite the variety of the variance models that have been developed and the relative VaR methodologies, the vast majority of the researchers conclude that there is no model or specific methodology that outperforms all the others. On the contrary, the best approach to minimize risk and accurately forecast the future potential losses is to adopt that specific methodology that will be able to take into consideration the particular characteristic features regarding the trade of energy products.
    Keywords: Energy commodities, Risk Management, Value-at-Risk (VaR).
    JEL: C01 C58 D81 G30 O13 P28 Q43 Q47 Q5 Q58
    Date: 2019–01–23
  6. By: Sandhya Devi
    Abstract: The relation between volatility and the predicted average returns of portfolios in excess of market returns is investigated using four risk measures: 1) Tsallis q-Gaussian relative entropy, 2) Kullback-Leibler relative entropy, 3) the parameter 'beta' of the Capital Asset Pricing Model (CAPM), and 4) relative standard deviation. Portfolios are constructed by binning the securities according to their risk values. The mean risk value and the mean return in excess of market returns for each bin is calculated to get the risk-return patterns of the portfolios. The investigations have been carried out for both long (~18 years) and shorter (~9 years) terms that include the dot-com bubble and the 2008 crash periods. In all cases, a linear fit can be obtained for the risk and excess return profiles, both for long and shorter periods. For longer periods, the linear fits have a positive slope, with Tsallis relative entropy giving the best goodness of fit. For shorter periods, the risk-return profiles from Tsallis relative entropy show a more consistent pattern than those from the other three risk measures.
    Date: 2019–01
  7. By: Döttling, Robin
    Abstract: How do near-zero deposit rates affect (optimal) bank capital regulation and risk taking? I study these questions in a tractable, dynamic equilibrium model, in which forward-looking banks compete imperfectly for deposit funding, subject to a (zero) lower bound constraint on deposit rates (ZLB). At the ZLB, capital requirements become less effective in curbing excessive risk-taking incentives, as they disproportionately hurt franchise values. As a consequence, optimal dynamic capital requirements vary with the level of interest rates if the ZLB binds occasionally. Subsidizing bank funding costs at the ZLB dampens risk-taking, but may reduce overall welfare.
    Keywords: Zero lower bound,Search for yield,Capital regulation,Bank competition,Franchise value
    JEL: G21 G28 E43
    Date: 2019
  8. By: Xie, Zhuang
    Abstract: With the development of science and technology and economy, more and more financial intermediaries are appearing in the financial market to ensure more efficient and stable processes in the financial system. As the main part of financial intermediary, the bank plays a vital role in the whole financial market system. In recent years, China's banking industry has been developing rapidly, but there are many potential problems, such as the operational risk management. At the present stage, the operational risk management authority of China's commercial banks is overly centralized, there is no clear loan risk responsibility system, and no effective long-term credit mechanism has been established, and the problem of non-performing loans still exists. This paper takes Hua Xia Bank as the objective of study and its analysis of the data based on its annual report between 2013 to 2017. The result of analysis shows that the ratio of firm-specific factor which can influence operating ratio mostly is leverage. Moreover, for the macroeconomic part, the significant influential factor is GDP. Therefore, this study suggest the bank should manage the leverage ratio effectively and efficiently for preforming well in the operational risk management.
    Keywords: operating ratio,leverage,GDP
    JEL: G21
    Date: 2018–12–16
  9. By: Fatouh, Mahmoud (Bank of England); McMunn, Ayowande (Carmihnac Asset Managers)
    Abstract: This paper presents a model of shareholders’ willingness to exert effort to reduce the likelihood of bank distress, and the implications of the presence of contingent convertible (CoCo) bonds in the liabilities structure of a bank. Consistent with the existing literature, we show that the direction of the wealth transfer at the conversion of CoCo bonds determines their impact on shareholder risk-taking incentives. We also find that ‘anytime’ CoCos (CoCo bonds trigger-able anytime at the discretion of managers) have a minor advantage over regulator CoCo bonds, and that quality of capital requirements can reduce the risk-taking incentives of shareholders. We argue that shareholders can also use manager-specific CoCo bonds to reduce the riskiness of the bank activities. The issuance of such bonds can increase the resilience of individual banks and the whole banking system. Regulators can use restrictions on conversion rates and/or requirements on the quality of capital to address the impact of CoCo bonds issuance on risk-taking incentives.
    Keywords: Risk-taking; CoCo bonds; anytime CoCos; quality of capital requirements; additional Tier 1 capital (AT1); bank manager compensation packages; compensation policy.
    JEL: D81 G21 G28 G30
    Date: 2019–01–18
  10. By: Manuel Ammann; Sebastian Fischer; Florian Weigert;
    Abstract: We investigate the relationship between a mutual fund’s variation in systematic risk factor exposures and its future performance. Using a dynamic state space version of Carhart (1997)’s four factor model to capture risk factor variation, we find that funds with volatile risk factor exposures underperform funds with stable risk factor exposures by 147 basis points p.a. This underperformance is neither explained by volatile risk factor loadings of a fund’s equity holdings nor driven by a fund’s forced trading through investor flows. We conclude that fund managers voluntarily attempt to time risk factors, but are unsuccessful at doing so. Our results are important in the light of recent discussions about the predictability of asset pricing risk factors.
    Keywords: Mutual Fund, Market Timing, Factor Timing, Kalman Filter
    JEL: G11 G14 G20 G23
    Date: 2018–08
  11. By: Junbeom Lee; Stephan Sturm; Chao Zhou
    Abstract: We propose a risk-sharing framework for bilateral contracts to find the optimal pair, initial price and amount of collateral, with presence of default risks, collateral, and funding spreads. The derived optimal collateral can be used for contracts between financial firms and non-financial firms. For inter-dealers contracts, which are governed by regulations, the optimal collateral can interpret circumstances where the margin requirement is indeed optimal. We will see later that absence of market frictions is an inherent assumption for the margin requirement in Basel III. In addition, as we consider entity-specific information in bilateral pricing, law of one price does not hold. Moreover, inclusion of funding spreads causes asymmetry in individual pricing. Thus, the two parties should enter derivative contracts with a negotiated price, which is the other part of the solution of the risk-sharing framework. The risk-sharing framework defines the negotiation as a problem that maximizes the sum of utilities of the two parties. The optimal price from the risk-sharing framework does not have asymmetry due to different funding spreads of each party.
    Date: 2019–01
  12. By: Mark Schneider (University of Alabama)
    Abstract: Recent studies have observed systematic interactions between risk, time, and social preferences that constitute violations of `dimensional independence' and are not explained by the leading models of decision making. This note provides a simple approach to modeling such interaction eects while predicting new ones. In particular, we present a model of rational-behavioral preferences that takes the convex combination of `behavioral' System 1 preferences and `rational' System 2 preferences. The model provides a unifying approach to analyzing risk, time, and social preferences, and predicts how these preferences are correlated with reliance on System 1 or System 2 thinking.
    Keywords: Risk; Time; Social preference; System 1; System 2
    JEL: D90 D91
    Date: 2018
  13. By: Martin Tegn\'er; Stephen Roberts
    Abstract: The local volatility model is a widely used for pricing and hedging financial derivatives. While its main appeal is its capability of reproducing any given surface of observed option prices---it provides a perfect fit---the essential component is a latent function which can be uniquely determined only in the limit of infinite data. To (re)construct this function, numerous calibration methods have been suggested involving steps of interpolation and extrapolation, most often of parametric form and with point-estimate representations. We look at the calibration problem in a probabilistic framework with a nonparametric approach based on a Gaussian process prior. This immediately gives a way of encoding prior beliefs about the local volatility function and a hypothesis model which is highly flexible yet not prone to over-fitting. Besides providing a method for calibrating a (range of) point-estimate(s), we draw posterior inference from the distribution over local volatility. This leads to a better understanding of uncertainty associated with the calibration in particular, and with the model in general. Further, we infer dynamical properties of local volatility by augmenting the hypothesis space with a time dimension. Ideally, this provides predictive distributions not only locally, but also for entire surfaces forward in time. We apply our approach to S&P 500 market data.
    Date: 2019–01
  14. By: Mankart, Jochen; Michaelides, Alexander; Pagratis, Spyros
    Abstract: We estimate a dynamic structural banking model to examine the interaction between risk-weighted capital adequacy and unweighted leverage requirements, their differential impact on bank lending, and equity buffer accumulation in excess of regulatory minima. Tighter risk-weighted capital requirements reduce loan supply and lead to an endogenous fall in bank profitability, reducing bank incentives to accumulate equity buffers and, therefore, increasing the incidence of bank failure. Tighter leverage requirements, on the other hand, increase lending, preserve bank charter value and incentives to accumulate equity buffers, therefore leading to lower bank failure rates.
    Keywords: Banking,Equity Buffers,Regulatory Interactions
    JEL: E44 G21 G38
    Date: 2018
  15. By: Turan G. Bali; Florian Weigert;
    Abstract: This paper examines idiosyncratic volatility of equity-oriented hedge funds and provides an explanation for why there exists a positive cross-sectional relation between funds’ idiosyncratic volatility and their future returns, whereas higher idiosyncratic volatility predicts lower returns in the cross-section of individual stocks. We find that idiosyncratic volatility is a persistent hedge fund characteristic and positively linked to proxies for managerial incentives, discretion, and leverage. Moreover, funds with a greater value of long call options and confidential equity positions disclosed with a delay in their regulatory filings exhibit higher idiosyncratic volatility. We document a positive (negative) cross-sectional relation between idiosyncratic volatility and future returns on individual stocks with high (low) hedge fund ownership. The results indicate that hedge funds are able to solve the idiosyncratic volatility puzzle by successfully picking undervalued, high-volatility stocks that offer high future returns and shying away from overvalued, high-volatility and lottery-like stocks that offer low future returns.
    Keywords: Hedge Funds, Idiosyncratic Volatility Puzzle, Confidential Holdings, Derivatives, Managerial Incentives, Investment Performance
    JEL: G11 G23
    Date: 2018–12
  16. By: Anthony M. Diercks; Uri Carl
    Abstract: In this Note, we use rolling covariances between real and nominal activity in a regression framework, combined with a model averaging approach, to uncover intuitive dynamics in the term premium.
    Date: 2019–01–08

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