nep-rmg New Economics Papers
on Risk Management
Issue of 2012‒09‒30
seventeen papers chosen by
Stan Miles
Thompson Rivers University

  1. Be as safe as possible: A behavioral approach to the optimal corporate risk strategy of insurers By Zimmer, Anja; Gründl, Helmut; Schade, Christian
  2. A Macroeconomic Model of Endogenous Systemic Risk Taking By Martinez-Miera, David; Suarez, Javier
  3. Dynamic risk management: investment, capital structure, and hedging in the presence of financial frictions By Amaya, Diego; Gauthier, Geneviève; Léautier, Thomas-Olivier
  4. Optimal investment strategies for insurance companies in the presence of standardised capital requirements By Fischer, Katharina; Schlütter, Sebastian
  5. Risk Management strategies in a highly uncertain environment: undesrtanding the role of common unknown By Olga Kokshagina; Pascal Le Masson; Benoit Weil; Patrick Cogez
  6. Downside risk and the energy hedger's horizon By Thomas Conlon; John Cotter
  7. Will Solvency II market risk requirements bite? The impact of Solvency II on insurers' asset allocation By Höring, Dirk
  8. Spectral Risk Measures, With Adaptions For Stochastic Optimization By Alois Pichler
  9. A Continuous Time Structural Model for Insolvency, Recovery, and Rollover Risks By Gechun Liang; Eva L\"utkebohmert; Wei Wei
  10. The minimum balance at risk: a proposal to mitigate the systemic risks posed by money market funds By Patrick E. McCabe; Marco Cipriani; Michael Holscher; Antoine Martin
  11. Safety versus affordability as targets of insurance regulation in an opaque market: A welfare approach By Stoyanova, Rayna; Schlütter, Sebastian
  12. On the strategic value of risk management By Léautier, Thomas-Olivier; Rochet, Jean-Charles
  13. How Do Regulators Influence Mortgage Risk? Evidence from an Emerging Market By Campbell, John Y; Ramadorai, Tarun; Ranish, Benjamin
  14. Do Margin Requirements Affect Asset Prices? By Bruno Cara Giovannetti; Guilherme B. Martins
  15. Sparsifying Defaults: Optimal Bailout Policies for Financial Networks in Distress By Zhang Li; Ilya Pollak
  16. Platform emergence in double unknown: Common challenge strategy By Olga Kokshagina; Pascal Le Masson; Benoit Weil; Patrick Cogez
  17. Intertemporal Risk Management in Agriculture By Jesse Tack; Rulon Pope; Jeffrey LaFrance; Timothy Graciano; Scott Colby

  1. By: Zimmer, Anja; Gründl, Helmut; Schade, Christian
    Abstract: This paper empirically studies the impact of consumer reaction to default risk on an insurer's optimal solvency level. Using experimentally obtained data, we derive a price-default risk-demand-curve that serves as an input variable for the insurer's risk strategy. We show that an insurer should choose to be default-free rather than having even a very small default probability. This risk strategy is also optimal when assuming substantial transaction costs for risk management activities undertaken to achieve the maximum solvency level. --
    Keywords: Behavioral Insurance,Risk Management of Insurance Companies
    Date: 2012
  2. By: Martinez-Miera, David; Suarez, Javier
    Abstract: We analyze banks' systemic risk taking in a simple dynamic general equilibrium model. Banks collect funds from savers and make loans to firms. Banks are owned by risk-neutral bankers who provide the equity needed to comply with capital requirements. Bankers decide their (unobservable) exposure to systemic shocks by trading off risk-shifting gains with the value of preserving their capital after a systemic shock. Capital requirements reduce credit and output in
    Keywords: Capital requirements; Credit cycles; Financial crises; Macroprudential policies; Risk shifting; Systemic risk
    JEL: E44 G21 G28
    Date: 2012–09
  3. By: Amaya, Diego (UQAM); Gauthier, Geneviève (HEC Montréal); Léautier, Thomas-Olivier (TSE,IAE)
    Abstract: This paper develops a dynamic risk management model to determine a firm's optimal risk management strategy. The risk management strategy has two elements: first, until leverage is very high, the firm fully hedges its operating cash how exposure, due to the convexity in its cost of capital. When leverage exceeds a very high threshold, the firm gambles for resurrection and stops hedging. Second, the firm manages its capital structure through dividend distributions and investment. When leverage is very low, the firm fully replaces depreciated assets, fully invests in opportunities if they arise, and distribute dividends to reach its optimal capital structure. As leverage increases, the firm stops paying dividends, while fully investing. After a certain leverage, the firm also reduces investment, until it stop investing completely. The model predictions are consistent with empirical observations.
    JEL: C61 G32
    Date: 2012–04
  4. By: Fischer, Katharina; Schlütter, Sebastian
    Abstract: The standard formula of the Solvency II framework employs an approximate value-at-risk approach to define risk-based capital requirements. The parameterization of the standard formula determines how much additional capital insurers need in order to back investments in risky assets. This paper investigates how the standard formula's stock risk calibration influences the equity position and investment strategy of a shareholder-value-maximising insurance company. Intuitively, a higher stock risk parameter should reduce the insurer's risky investments as well as his insolvency risk. However, by considering the insurer's equity level as an endogenous variable, we identify situations in which a stricter stock risk calibration leads to a significant reduction of stock investments, but leaves the actual solvency level virtually unaffected, since the insurer also lowers his equity capital position. While previous articles only deal with the statistical accuracy of the standard formula's calibration, our results shed light on the incentives resulting from different calibrations. --
    Keywords: solvency regulation,capital requirements,asset allocation,insurer default risk
    Date: 2012
  5. By: Olga Kokshagina (CGS - Centre de Gestion Scientifique - Mines ParisTech, ST-CROLLES - STMicroelectronics (Crolles) - STMicroelectronics); Pascal Le Masson (CGS - Centre de Gestion Scientifique - Mines ParisTech); Benoit Weil (CGS - Centre de Gestion Scientifique - Mines ParisTech); Patrick Cogez (ST-CROLLES - STMicroelectronics (Crolles) - STMicroelectronics)
    Abstract: This work deals with strategies of risk management techniques in projects and portfolios in the situation of radical innovation. Existing literature suggests different methods of risk management at the level of 1) projects (S1) (unknown reduction by selecting a priori the less uncertain projects, depending on the identified market and technological risk) 2) portfolio (S2) (consists in using an existing platform core to construct several options. This strategy increases chances to succeed by increasing the size of the sample, maximizing the total economic value of the portfolio of derivatives). These methods consider different level of uncertainties and are independent from each other. We will show that there exists another strategy (S3) of working on "common unknown" of multiple options but its managerial implementation is not obvious. By testing the proposed framework in two cases of Advanced R&D (explorative phase of new technologies development for unknown markets with fixed budget) in semiconductor industry, we compare identified S3 strategy with existing S1' lead by S2'. The paper demonstrates that management of "common unknown" is possible and could be implemented in the context of largely unknown exploration. The proposed strategy of working on common unknown opens a new way to portfolio risk management in the context of radical innovation. Using S3 framework of knowledge gap identification to construct common unknown core, company can build its innovative capabilities through knowledge management and better position to innovate in emerging fields.
    Keywords: Risk management, uncertainty, common unknown, project portfolio, platform core, platform derivatives
    Date: 2012–06–17
  6. By: Thomas Conlon (Smurfit School of Business, University College Dublin); John Cotter (UCD Smurfit School of Business, University College Dublin)
    Abstract: In this paper, we explore the impact of investor time-horizon on an optimal downside hedged energy portfolio. Previous studies have shown that minimum-variance hedging effectiveness improves for longer horizons using variance as the performance metric. This paper investigates whether this result holds for different hedging objectives and effectiveness measures. A wavelet transform is applied to calculate the optimal heating oil hedge ratio using a variety of downside objective functions at different time-horizons. We demonstrate decreased hedging effectiveness for increased levels of uncertainty at higher confidence intervals. Moreover, for each of the different hedging objectives and effectiveness measures studied, we also demonstrate increasing hedging effectiveness at longer horizons. While small differences in effectiveness are found across the different hedging objectives, time-horizon effects are found to dominate confirming the importance of considering the hedgers horizon. The findings suggest that while downside risk measures are useful in the computation of an optimal hedge ratio that accounts for unwanted negative returns, hedging horizon and confidence intervals should also be given careful consideration by the energy hedger.
    Keywords: Energy Hedging, Futures Hedging, Wavelet Transform, Hedging Horizon, Downside Risk
    Date: 2012–09–17
  7. By: Höring, Dirk
    Abstract: The European insurance industry is among the largest institutional investors in Europe. Therefore, major reallocations in their investment portfolios due to the new risk-based economic capital requirements introduced by Solvency II would cause significant disruptions in European capital markets and corporate financing. This paper studies whether the new regulatory capital requirements for market risk are a binding constraint for European insurers by comparing the market risk capital requirements of the Solvency II standard model with the Standard & Poor's rating model for a fictitious, but representative, European-based life insurer. The results show that for a comparable level of confidence, the rating model requires 68% more capital than the standard model for the same market risks. Hence, Solvency II seems not to be a binding capital constraint for market risk and thus would not significantly influence the insurance companies' investment strategies. --
    Keywords: Solvency II,Rating,Market Risk,Capital Requirements
    Date: 2012
  8. By: Alois Pichler
    Abstract: Stochastic optimization problems often involve the expectation in its objective. When risk is incorporated in the problem description as well, then risk measures have to be involved in addition to quantify the acceptable risk, often in the objective. For this purpose it is important to have an adjusted, adapted and efficient evaluation scheme for the risk measure available. In this article different representations of an important class of risk measures, the spectral risk measures, are elaborated. The results allow concise problem formulations, they are particularly adapted for stochastic optimization problems. Efficient evaluation algorithms can be built on these new results, which finally make optimization problems involving spectral risk measures eligible for stochastic optimization.
    Date: 2012–09
  9. By: Gechun Liang; Eva L\"utkebohmert; Wei Wei
    Abstract: We propose a unified structural credit risk model incorporating insolvency, recovery and rollover risks. The firm finances itself mainly by issuing short- and long-term debt. Short-term debt can have either a discrete or a more realistic staggered tenor structure. We show that a unique threshold strategy (i.e., a bank run barrier) exists for short-term creditors to decide when to withdraw their funding, and this strategy is closely related to the solution of a non-standard optimal stopping time problem with control constraints. We decompose the total credit risk into an insolvency component and an illiquidity component based on such an endogenous bank run barrier together with an exogenous insolvency barrier.
    Date: 2012–09
  10. By: Patrick E. McCabe; Marco Cipriani; Michael Holscher; Antoine Martin
    Abstract: This paper introduces a proposal for money market fund (MMF) reform that could mitigate systemic risks arising from these funds by protecting shareholders, such as retail investors, who do not redeem quickly from distressed funds. Our proposal would require that a small fraction of each MMF investor's recent balances, called the "minimum balance at risk" (MBR), be demarcated to absorb losses if the fund is liquidated. Most regular transactions in the fund would be unaffected, but redemptions of the MBR would be delayed for thirty days. A key feature of the proposal is that large redemptions would subordinate a portion of an investor's MBR, creating a disincentive to redeem if the fund is likely to have losses. In normal times, when the risk of MMF losses is remote, subordination would have little effect on incentives. We use empirical evidence, including new data on MMF losses from the U.S. Treasury and the Securities and Exchange Commission, to calibrate an MBR rule that would reduce the vulnerability of MMFs to runs and protect investors who do not redeem quickly in crises.
    Keywords: Money market funds ; Human behavior ; Investments ; Financial crises ; Systemic risk
    Date: 2012
  11. By: Stoyanova, Rayna; Schlütter, Sebastian
    Abstract: Insurance regulation is typically aimed at policyholder protection. In particular, regulators attempt to ensure the financial safety of insurance firms, for example, by means of capital regulation, and to enhance the affordability of insurance, for example, by means of price ceilings. However, these goals are in conflict. Therefore, we identify situations in which regulators should be more concerned with safety or, alternatively, affordability. Our model incorporates default-risk-sensitive insurance demand, capital-related frictional costs, and imperfect risk transparency for policyholders. --
    Keywords: Insurance Regulation,Regulatory Targets,Welfare,Opaqueness
    Date: 2012
  12. By: Léautier, Thomas-Olivier (TSE,IAE); Rochet, Jean-Charles (TSE, University of Zurich)
    Abstract: This article examines how firms facing volatile input prices and holding some degree of market power in their product market link their risk management and production or pricing strategies. This issue is relevant in many industries ranging from manufacturing to energy retailing, where risk averse firms decide on their hedging strategies before their product market strategies. We find that hedging modifies the pricing and production strategies of firms. This strategic effect is channelled through the expected risk-adjusted cost, i.e., the expected marginal cost under the measure induced by investors'risk aversion, and has diametrically opposed impacts depending on the nature of product market competition: hedging toughens quantity competition while it softens price competition. Finally, committing to a hedging strategy is always a best response to non committing, and is a dominant strategy if firms compete à la Hotelling.
    JEL: G32 L13
    Date: 2012–09–03
  13. By: Campbell, John Y; Ramadorai, Tarun; Ranish, Benjamin
    Abstract: To understand the effects of regulation on mortgage risk, it is instructive to track the history of regulatory changes in a country rather than to rely entirely on cross-country evidence that can be contaminated by unobserved heterogeneity. However, in developed countries with fairly stable systems of financial regulation, it is difficult to track these effects. We employ loan-level data on over a million loans disbursed in India over the 1995 to 2010 period to understand how fast-changing regulation impacted mortgage lending and risk. We find evidence that regulation has important effects on mortgage rates and delinquencies in both the time-series and the cross-section.
    Keywords: delinquencies; emerging markets; India; mortgage finance; regulation
    JEL: G21 G28 R21 R31
    Date: 2012–09
  14. By: Bruno Cara Giovannetti; Guilherme B. Martins
    Abstract: Some recent theoretical papers show that margin requirements can affect asset prices. Such results are important, for example, to understand the unconventional polices implemented by the Fed during the financial crisis of 2007-2010. However, empirical evidence remains scarce. The present article contributes to filling this gap. It shows that an aggregate margin factor predicts future excess returns of the S&P 500, and that stocks with high exposures to the ted spread pay on average higher risk-adjusted returns. Both findings are in accordance with the theory that relates margins and prices.
    Keywords: asset prices, margin requirements, capital constraint
    JEL: G01 G10 G12
    Date: 2012–09–11
  15. By: Zhang Li; Ilya Pollak
    Abstract: The events of the last few years revealed an acute need for tools to systematically model and analyze large financial networks. Many applications of such tools include the forecasting of systemic failures and analyzing probable effects of economic policy decisions. We consider optimizing the amount and structure of a bailout in a borrower-lender network: Given a fixed amount of cash to be injected into the system, how should it be distributed among the nodes in order to achieve the smallest overall amount of unpaid liabilities or the smallest number of nodes in default? We develop an exact algorithm for the problem of minimizing the amount of unpaid liabilities, by showing that it is equivalent to a linear program. For the problem of minimizing the number of defaults, we develop an approximate algorithm using a reweighted l1 minimization approach. We illustrate this algorithm using an example with synthetic data for which the optimal solution can be calculated exactly, and show through numerical simulation that the solutions calculated by our algorithm are close to optimal.
    Date: 2012–09
  16. By: Olga Kokshagina (CGS - Centre de Gestion Scientifique - Mines ParisTech, ST-CROLLES - STMicroelectronics (Crolles) - STMicroelectronics); Pascal Le Masson (CGS - Centre de Gestion Scientifique - Mines ParisTech); Benoit Weil (CGS - Centre de Gestion Scientifique - Mines ParisTech); Patrick Cogez (ST-CROLLES - STMicroelectronics (Crolles) - STMicroelectronics)
    Abstract: The proposed paper deals with platform emergence in double unknown situations when technology and markets are highly uncertain. The interest in technological platform development to enable creation of products and processes that support present and future development of multiple options is widely recognized by practitioners and academics The existing literature considers already existing platforms and the development is based on exploiting this common platform core to build future markets and technological derivatives. However, when we are in double unknown situations, markets and technologies are highly uncertain and neither options, nor platform core are known. Thus, how can one ensure platform emergence in double unknown?The history of innovation promotes mostly singular challenge strategy to guide innovative development. But in certain sectors, like semiconductors, telecommunications, pharmaceuticals, the success of common challenge strategy applicable to several markets is more important than singular project success. Thus, which strategy to choose for innovative technological platform emergence? Why common challenge strategy appears to be so challenging and risky? The objective of the paper is to define what are the precise market and technological conditions that in certain situations lead to 1) develop common building block (common core) that facilitate all the others projects but don't provide access directly to the market 2) launch singular project exploration to emerge future platform core consequently. We attempt to address our research questions by formally describing each strategy and fabricating simple economical model to compare them. For simulation the data was created by taking into account specifics of real management situations and parameters were chosen based on the literature review. Then we illustrate the insights of the model through a case study of innovative technology development in semiconductor industry. The in-depth empirical case study was conducted in STMicroelectronics, one of the leaders in the semiconductor industry. The data for case study was gathered from advanced technology platform with several interdependent modules developed by company and introduced to the several markets after all. This paper contributes to existing work on platform emergence by introducing the strategy of platform core construction in double unknown based on future common challenge investigation.
    Keywords: Risk management, uncertainty, platform emergence
    Date: 2012–05–23
  17. By: Jesse Tack; Rulon Pope; Jeffrey LaFrance; Timothy Graciano; Scott Colby
    Abstract: Agricultural production is subject to supply risk. Expected and realized farm outputs and output prices are unknown and unobservable when inputs are chosen. Crop and livestock production decisions are linked over time. Producers’ expectations are particularly difficult to model. This paper presents the necessary and sufficient condition to allow input demands to be specified as functions of input prices, technology, quasi-fixed inputs, and cost in place of planned/expected outputs. These are all observable when inputs are committed to production. Next we derive a flexible, exactly aggregable, economically regular econometric model of input demands. This model is consistent with any dynamic von Newman – Morgenstern expected utility function. We combine this framework with a model of the life-cycle production, investment and savings, and consumption decisions of owner/operators who face output and output price risk, and who have opportunities to invest in a conditionally risk free asset, other risky financial assets, and farm assets. The econometric framework allows for location specific technological change and production processes, cross-equation, interspatial, and intertemporal correlation among the error terms, and structural simultaneity between inputs and outputs, input and output prices, investment in durable goods used in agriculture, consumption, savings, and wealth. The result is a consistent dynamic structural model of inputs, outputs, savings, investment, and consumption under risk. We apply this model at the national-level to crop and livestock production for the years 1960-1999.
    Keywords: Aggregation, consumption, ex ante cost, expected utility, functional form, investment
    JEL: C3 D2 D8
    Date: 2012–09

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