nep-rmg New Economics Papers
on Risk Management
Issue of 2018‒02‒26
fourteen papers chosen by
Stan Miles
Thompson Rivers University

  1. The impact of mandatory governance changes on financial risk management By Hege, Ulrich; Hutson, Elaine; Laing, Elaine
  2. Bank lending behavior and business cycle under Basel regulations: Is there a significant procyclicality? By Katsutoshi Shimizu; Kim Cuong Ly
  3. Sovereign bond-backed securities: a VAR-for-VaR and Marginal Expected Shortfall assessment By Maite De Sola Perea; Peter G. Dunne; Martin Puhl; Thomas Reininger
  4. Explicit size distributions of failure cascades redefine systemic risk on finite networks By Rebekka Burkholz; Hans J. Herrmann; Frank Schweitzer
  5. Volatility options in rough volatility models By Blanka Horvath; Antoine Jacquier; Peter Tankov
  6. Can Technology Undermine Macroprudential Regulation? Evidence from Peer-to-Peer Credit in China By Braggion, Fabio; Manconi, Alberto; Zhu, Haikun
  7. Replica Approach for Minimal Investment Risk with Cost By Takashi Shinzato
  8. The Samuelson Effect and Seasonal Stochastic Volatility in Agricultural Futures Markets By Lorenz Schneider; Bertrand Tavin
  9. Deep Hedging By Hans B\"uhler; Lukas Gonon; Josef Teichmann; Ben Wood
  10. Short-selling bans and bank stability By Alessandro Beber; Daniela Fabbri; Marco Pagano; Saverio Simonelli
  11. Modeling Your Stress Away By Niepmann, Friederike; Stebunovs, Viktors
  12. Decisions under Risk Dispersion and Skewness By Bayrak, Oben K.; Hey, John D.
  13. Collateral Unchained: Rehypothecation Networks, Concentration and Systemic Effects By Duc Thi Luu; Mauro Napoletano; Paolo Barucca; Stefano Battiston
  14. How Do Foreclosures Exacerbate Housing Downturns? By Adam M. Guren; Timothy J. McQuade

  1. By: Hege, Ulrich; Hutson, Elaine; Laing, Elaine
    Abstract: This paper uses the staggered adoption of the Sarbanes-Oxley Act of 2002 for a difference-in-difference identification of the impact of corporate governance on hedging. In a large panel of listed US firms, we focus on two indexes of the legally required governance reforms, but also a wide index of governance quality. We find that the substantial improvements in governance standards robustly lead to less foreign exchange exposure and more foreign exchange derivatives hedging, and that the economic magnitude of the effect is large. Also, the adoption of mandatory governance measures is a stronger predictor of hedging than voluntary improvements. Dynamic panel GMM estimates confirm a significant positive relationship between governance quality and hedging.
    Keywords: hedging; foreign exchange exposure; Sarbanes-Oxley Act; corporate governance; board monitoring; staggered introduction
    JEL: F23 F31 G34
    Date: 2018–02
  2. By: Katsutoshi Shimizu (Department of Economics, Nagoya University); Kim Cuong Ly (School of Management, Swansea University)
    Abstract: This paper re-examines the procyclical effect of risk{sensitive capital regulation on bank lending. The risk{sensitive requirement of the Basel II/III regulation affects procyclically the bank lending in European countries, but the actual requirements are indeed too risk-insensitive. However, the risk{sensitive capital regulation induces less lending than the risk-insensitive capital regulation. Furthermore, the introduction of Basel II has a negative impact on lending even under the risk{insensitive regulation.
    Keywords: Bank capital, Basel regulation, macro-prudential policy, business cycle, procyclicality, buffer capital, countercyclical buffer.
    JEL: G21 G28 G18 G14 G32
    Date: 2018–02–01
  3. By: Maite De Sola Perea; Peter G. Dunne; Martin Puhl; Thomas Reininger
    Abstract: The risk reducing benefits of the sovereign bond-backed security (SBBS) proposal of Brunnermeier et al (2011, 2016, 2017) have been assessed in terms of the likely losses that different kinds of holders would suffer under simulated default scenarios. However, the effects of mark-to-market losses that may occur when there is rising uncertainty about defaults, or when self-fulfilling destablising dynamics are prevalent, have not yet been examined. We apply the “VAR-for-VaR” method of White, Kim and Manganelli (2015) and the Marginal Expected Shortfall approach of Brownlees and Engle (2012, 2017) to estimated yields of SBBS to assess how ex ante exposures are likely to playout under various securitisation structures. We compare these with exposures of single sovereigns and a diversified portfolio. We find that the senior SBBS has extremely low ex ante tail risk and that, like the lowest-risk single-named sovereigns, it acts as a hedge against extreme adverse movements in the yields on more junior tranches. The mezzanine SBBS has tail risk exposure similar to that of Italian and Spanish bonds. Yields on SBBS appear to be adequate compensation for their risks when compared with single sovereigns or a diversified portfolio. JEL Classification: E43, E44, E52, E53, G12, G14
    Keywords: Safe Assets; Sovereign Bonds; Value-at-Risk; Spillover; CAViaR; Co-Dependence
    Date: 2018–01
  4. By: Rebekka Burkholz; Hans J. Herrmann; Frank Schweitzer
    Abstract: How big is the risk that a few initial failures of nodes in a network amplify to large cascades that span a substantial share of all nodes? Predicting the final cascade size is critical to ensure the functioning of a system as a whole. Yet, this task is hampered by uncertain or changing parameters and missing information. In infinitely large networks, the average cascade size can often be well estimated by established approaches building on local tree approximations and mean field approximations. Yet, as we demonstrate, in finite networks, this average does not even need to be a likely outcome. Instead, we find broad and even bimodal cascade size distributions. This phenomenon persists for system sizes up to $10^{7}$ and different cascade models, i.e. it is relevant for most real systems. To show this, we derive explicit closed-form solutions for the full probability distribution of the final cascade size. We focus on two topological limit cases, the complete network representing a dense network with a very narrow degree distribution, and the star network representing a sparse network with a inhomogeneous degree distribution. Those topologies are of great interest, as they either minimize or maximize the average cascade size and are common motifs in many real world networks.
    Date: 2018–02
  5. By: Blanka Horvath; Antoine Jacquier; Peter Tankov
    Abstract: We discuss the pricing and hedging of volatility options in some rough volatility models. First, we develop efficient Monte Carlo methods and asymptotic approximations for computing option prices and hedge ratios in models where log-volatility follows a Gaussian Volterra process. While providing a good fit for European options, these models are unable to reproduce the VIX option smile observed in the market, and are thus not suitable for VIX products. To accommodate these, we introduce the class of modulated Volterra processes, and show that they successfully capture the VIX smile.
    Date: 2018–02
  6. By: Braggion, Fabio; Manconi, Alberto; Zhu, Haikun
    Abstract: We study whether and to what extent peer-to-peer (P2P) credit helps circumvent loan-to-value (LTV) caps, a key macroprudential tool to contain household leverage. We exploit the tightening of mortgage LTV caps in a number of cities in China in 2013 as our testing ground, in a difference-in-differences setting, and we base our tests on a novel, hand-collected database covering all lending transactions at RenrenDai, a leading Chinese P2P credit platform. P2P loans increase at the cities affected by the LTV cap tightening relative to the control cities, consistent with borrowers tapping P2P credit to circumvent the regulation. The granularity of our data allows us to separate credit demand from credit supply effects, with a fixed effects strategy. Our results also indicate that P2P lenders do not adjust their pricing and screening to the influx of new borrowers after 2013, despite the fact that their loans ex post have higher delinquency and default rates. Symmetric effects are associated with a loosening of mortgage LTV caps in 2015. Our test provides empirical evidence on the capacity of P2P credit to undermine LTV caps. More broadly, our analysis informs the debate on the challenges posed by the interaction between FinTech and credit regulation.
    Keywords: peer-to-peer credit; household leverage; macroprudential regulation; loan-to-value caps
    JEL: G01 G23 G28
    Date: 2018–01
  7. By: Takashi Shinzato
    Abstract: In the present work, the optimal portfolio minimizing the investment risk with cost is discussed analytically, where this objective function is constructed in terms of two negative aspects of investment, the risk and cost. We note the mathematical similarity between the Hamiltonian in the mean-variance model and the Hamiltonians in the Hopfield model and the Sherrington{Kirkpatrick model and show that we can analyze this portfolio optimization problem by using replica analysis, and derive the minimal investment risk with cost and the investment concentration of the optimal portfolio. Furthermore, we validate our proposed method through numerical simulations.
    Date: 2018–02
  8. By: Lorenz Schneider; Bertrand Tavin
    Abstract: We introduce a multi-factor stochastic volatility model based on the CIR/Heston variance process that incorporates seasonality and the Samuelson effect. Conditions on the seasonal term under which the corresponding volatility factor is well-defined are given, and five different specifications of the seasonality pattern are proposed. We calculate the joint characteristic function of two futures prices for different maturities in the risk-neutral measure, and explain how European options on futures and calendar spread options can be priced. The model is then presented under the physical measure, and its state-space representation is derived, in order to estimate the model's parameters with the Kalman filter for time series of corn, cotton, soybean, sugar and wheat futures from 2007 to 2017. We confirm the importance of correctly modelling the Samuelson effect in order to account for futures with different maturities. We also see that the seasonal model significantly outperforms the nested non-seasonal model in all five markets, and show which seasonality patterns are particularly well-suited for each market.
    Date: 2018–02
  9. By: Hans B\"uhler; Lukas Gonon; Josef Teichmann; Ben Wood
    Abstract: We present a framework for hedging a portfolio of derivatives in the presence of market frictions such as transaction costs, market impact, liquidity constraints or risk limits using modern deep reinforcement machine learning methods. We discuss how standard reinforcement learning methods can be applied to non-linear reward structures, i.e. in our case convex risk measures. As a general contribution to the use of deep learning for stochastic processes, we also show that the set of constrained trading strategies used by our algorithm is large enough to $\epsilon$-approximate any optimal solution. Our algorithm can be implemented efficiently even in high-dimensional situations using modern machine learning tools. Its structure does not depend on specific market dynamics, and generalizes across hedging instruments including the use of liquid derivatives. Its computational performance is largely invariant in the size of the portfolio as it depends mainly on the number of hedging instruments available. We illustrate our approach by showing the effect on hedging under transaction costs in a synthetic market driven by the Heston model, where we outperform the standard "complete market" solution.
    Date: 2018–02
  10. By: Alessandro Beber; Daniela Fabbri; Marco Pagano; Saverio Simonelli
    Abstract: In both the subprime crisis and the euro-area crisis, regulators imposed bans on short sales, aimed mainly at preventing stock price turbulence from destabilizing financial institutions. Contrary to the regulators’ intentions, financial institutions whose stocks were banned experienced greater increases in the probability of default and volatility than unbanned ones, and these increases were larger for more vulnerable financial institutions. To take into account the endogeneity of short sales bans, we match banned financial institutions with unbanned ones of similar size and riskiness, and instrument the 2011 ban decisions with regulators’ propensity to impose a ban in the 2008 crisis. JEL Classification: G01, G12, G14, G18
    Keywords: short-selling, ban, financial c risis, bank s tability, s ystemic risk
    Date: 2018–01
  11. By: Niepmann, Friederike; Stebunovs, Viktors
    Abstract: We investigate systematic changes in banks' projected credit losses between the 2014 and 2016 EBA stress tests, employing methodology from Philippon et al. (2017). We find that projected credit losses were smoothed across the tests through systematic model adjustments. Those banks whose losses would have increased the most from 2014 to 2016 due to changes in their exposures and supervisory scenarios-keeping the models constant-saw the largest decrease in losses due to model changes. Model changes were realistic and more pronounced for banks that rely more on the Internal Ratings-Based approach, and they explain the cross-section of market responses to the release of the 2016 results. Stock prices and CDS spreads increased more for banks with larger reductions in projected credit losses due to model changes, as investors apparently did not interpret lower loan losses as reflecting a decrease in credit risk but, instead, as a sign of lower capital requirements going forward.
    Keywords: credit risk models; financial institutions; regulation; stress tests
    JEL: G21 G28
    Date: 2018–01
  12. By: Bayrak, Oben K. (CERE - the Center for Environmental and Resource Economics); Hey, John D. (CERE - the Center for Environmental and Resource Economics)
    Abstract: When people take decisions under risk, it is not only the expected utility that is important, but also the shape of the distribution of returns: clearly the dispersion is important, but also the skewness. For given mean and dispersion, decision‐makers treat positively and negatively skewed prospects differently. This paper presents a new behaviourally‐inspired model for decision making under risk, incorporating both dispersion and skewness. We run a horse‐race of this new model against seven other models of decision‐making under risk, and show that it outperforms many in terms of goodness of fit and, perhaps more importantly, predictive ability. It can incorporate the prominent anomalies of standard theory such as the Allais paradox, the valuation gap, and preference reversals.
    Keywords: Decision under Risk; Anomalies; Valuation Gap; Preference Reversals; Allais Paradox; Skewness; Dispersion; Preference Functionals; Experiments; Pairwise Choice; Expected Utility; Non‐Expected Utility; Stochastic Specifications
    JEL: D81
    Date: 2018–01–15
  13. By: Duc Thi Luu (University of Kiel, Germany); Mauro Napoletano (OFCE Sciences-Po; SKEMA Business School); Paolo Barucca (University of Zurich, Switzerland; Scuola Superiore Sant'Anna, Pisa (Italy)); Stefano Battiston (University of Zurich, Switzerland)
    Abstract: We study how network structure affects the dynamics of collateral in presence of rehypothecation. We build a simple model wherein banks interact via chains of repo contracts and use their proprietary collateral or re-use the collateral obtained by other banks via reverse repos. In this framework, we show that total collateral volume and its velocity are affected by characteristics of the network like the length of rehypothecation chains, the presence or not of chains having a cyclic structure, the direction of collateral flows, the density of the network. In addition, we show that structures where collateral flows are concentrated among few nodes (like in core-periphery networks) allow large increases in collateral volumes already with small network density. Furthermore, we introduce in the model collateral hoarding rates determined according to a Value-at-Risk (VaR) criterion, and we then study the emergence of collateral hoarding cascades in different networks. Our results highlight that network structures with highly concentrated collateral flows are also more exposed to large collateral hoarding cascades following local shocks. These networks are therefore characterized by a trade-off between liquidity and systemic risk.
    Keywords: Rehypothecation, Collateral, Repo Contracts, Networks, Liquidity, Collateral-Hoarding Effects, Systemic Risk
    JEL: G01 G11 G32 G33
    Date: 2018–02
  14. By: Adam M. Guren (Boston University); Timothy J. McQuade (Stanford University)
    Abstract: We present a dynamic search model in which foreclosures exacerbate housing busts and delay the housing market;s recovery. By eroding lender equity, destroying the credit of potential buyers, and making buyers more selective, foreclosures freeze the market for non-foreclosures can cause price-default spirals that amplify an initial shock. To quantitatively asses these channels, the model is calibrated to the recent bust. The amplification is significant: ruined credit and choosey buyers account for 22.5 percent of the total decline in non-distressed prices and lender losses account for an additional 30 percent. We use our model to evaluate foreclosure mitigation policies and find that payment reduction is quite effective, but creating a single seller of foreclosures that holds them off the market until demand picks up is the most effective policy. Policies that slow down the pace of foreclosures can be counterproductive.
    Keywords: Housing Prices & Dynamics, Foreclosures, Search, Great Recession
    JEL: E30 R31

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