nep-rmg New Economics Papers
on Risk Management
Issue of 2018‒08‒13
twenty-two papers chosen by

  1. Quantile-Based Risk Sharing By Paul Embrechts; Haiyan Liu; Ruodu Wang
  2. Crash Risk in Individual Stocks By Paola Pederzoli
  3. Cyber Risk for the Financial Sector: A Framework for Quantitative Assessment By Antoine Bouveret
  4. Forecasting market states By Pier Francesco Procacci; Tomaso Aste
  5. Measuring the Capital Shortfall of Large U.S. Banks By Eric Jondeau; Amir Khalilzadeh
  6. Risk Management-Driven Policy Rate Gap By Giovanni Caggiano; Efrem Castelnuovo; Gabriela Nodari
  7. A General Equilibrium Appraisal of Capital Shortfall By Eric Jondeau; Jean-Guillaume Sahuc
  8. Transition drivers and crisis signaling in stock markets By Spelta, Alessandro; Pecora, Nicolò; Flori, Andrea; Pammolli, Fabio
  9. Preventing Controversial Catastrophes By Steven D. Baker; Burton Hollifield; Emilio Osambela
  10. A theory for robust risk measures By Marcelo Brutti Righi
  11. Half-full or Half-empty? Financial Institutions, CDS Use, and Corporate Credit Risk By Cecilia Caglio; R. Matthew Darst; Eric Parolin
  12. Measuring risks to UK financial stability By Aikman, David; Bridges, Jonathan; Burgess, Stephen; Galletly, Richard; Levina, Iren; O'Neill, Cian; Varadi, Alexandra
  13. Cancer Risk Messages: A Light Bulb Model By Ka C. Chan; Ruth F. G. Williams; Christopher T. Lenard; Terence M. Mills
  14. Assessing the impact of Basel III on bank behaviour: A micro-founded approach By Jérémy Pépy; Benjamin Williams
  15. Entropy Analysis of Financial Time Series By Stephan Schwill
  16. Spectral risk measure of holding stocks in the long run By Zsolt Bihary; Peter Csoka; David Zoltan Szabo
  17. Capital Regulation under Price Impacts and Dynamic Financial Contagion By Zachary Feinstein
  18. Return level applied to portfolio analysis By Suarez, Ronny
  19. Incremental Sharpe and other performance ratios By Eric Benhamou; Beatrice Guez
  20. Is Liquidity Risk Priced in Partially Segmented Markets? By Ines Chaieb; Vihang R. Errunza; Hugues Langlois
  21. Periodic or Generational Actuarial Tables: Which One to Choose? By Severine Arnold (-Gaille); Anca Jijiie; Eric Jondeau; Michael Rockinger
  22. The Economic Limits of Bitcoin and the Blockchain By Eric Budish

  1. By: Paul Embrechts (Swiss Federal Institute of Technology Zurich and Swiss Finance Institute); Haiyan Liu (Michigan State University); Ruodu Wang (University of Waterloo)
    Abstract: We address the problem of risk sharing among agents using a two-parameter class of quantile-based risk measures, the so-called Range-Value-at-Risk (RVaR), as their preferences. The family of RVaR includes the Value-at-Risk (VaR) and the Expected Shortfall (ES), the two popular and competing regulatory risk measures, as special cases. We first establish an inequality for RVaR-based risk aggregation, showing that RVaR satisfies a special form of subadditivity. Then, the Pareto-optimal risk sharing problem is solved through explicit construction. To study risk sharing in a competitive market, an Arrow-Debreu equilibrium is established for some simple, yet natural settings. Further, we investigate the problem of model uncertainty in risk sharing, and show that, generally, a robust optimal allocation exists if and only if none of the underlying risk measures is a VaR. Practical implications of our main results for risk management and policy makers are discussed, and several novel advantages of ES over VaR from the perspective of a regulator are thereby revealed.
    Keywords: Value-at-Risk, Expected Shortfall, risk sharing, regulatory capital, robustness, Arrow-Debreu equilibrium
    Date: 2018–01
  2. By: Paola Pederzoli (University of Geneva and Swiss Finance Institute)
    Abstract: In this study, I implement a novel methodology to extract crash risk premia from options and stock markets. I document a dramatic increase in crash risk premia after the 2008/2009 financial crisis, indicating that investors are willing to pay high insurance to hedge against crashes in individual stocks. My results apply to all sectors but are most pronounced for the financial sector. At the same time, crash risk premia on the market index remained at pre-crisis levels. I theoretically explain this puzzling feature in an economy where investors face short-sale constraints. Under short-sale constraints, prices are less informationally efficient which can explain the increase in downside risk in individual stocks. In the data, I document a strong link between proxies of short-sale constraints and crash risk premia.
    Keywords: Skewness risk premium, financial crisis, short-selling constraints
    JEL: G01 G12 G13
    Date: 2018–03
  3. By: Antoine Bouveret
    Abstract: Cyber risk has emerged as a key threat to financial stability, following recent attacks on financial institutions. This paper presents a novel documentation of cyber risk around the world for financial institutions by analyzing the different types of cyber incidents (data breaches, fraud and business disruption) and identifying patterns using a variety of datasets. The other novel contribution that is outlined is a quantitative framework to assess cyber risk for the financial sector. The framework draws on a standard VaR type framework used to assess various types of stability risk and can be easily applied at the individual country level. The framework is applied in this paper to the available cross-country data and yields illustrative aggregated losses for the financial sector in the sample across a variety of scenarios ranging from 10 to 30 percent of net income.
    Date: 2018–06–22
  4. By: Pier Francesco Procacci; Tomaso Aste
    Abstract: We propose a novel methodology to define, analyse and forecast market states. In our approach market states are identified by a reference sparse precision matrix and a vector of expectation values. In our procedure each multivariate observation is associated to a given market state accordingly to a penalized likelihood maximization. The procedure is made computationally very efficient and can be used with a large number of assets. We demonstrate that this procedure successfully classifies different states of the markets in an unsupervised manner. In particular, we describe an experiment with one hundred log-returns and two states in which the methodology automatically associates one state to periods with average positive returns and the other state to periods with average negative returns, therefore discovering spontaneously the common classification of `bull' and `bear' markets. In another experiment, with again one hundred log-returns and two states, we demonstrate that this procedure can be efficiently used to forecast off-sample future market states with significant prediction accuracy. This methodology opens the way to a range of applications in risk management and trading strategies where the correlation structure plays a central role.
    Date: 2018–07
  5. By: Eric Jondeau (University of Lausanne and Swiss Finance Institute); Amir Khalilzadeh (University of Lausanne)
    Abstract: We develop a new methodology to measure the capital shortfall of commercial banks during a market downturn. The measure, which we call stressed expected loss (SEL), adopts the structure of the individual bank's balance sheet. SEL is defined as the difference between the market value of assets in the stress scenario and the book value of the deposits and short-term debt of the bank. We estimate the probability of default and the SEL of the 31 largest commercial banks in the U.S. between 1996 and 2016. The probability of default in a market downturn was as high as 25%, on average, between 2008 and 2012. It is now much lower and close to 5%, on average. SEL was very high (between $250 and $350 billion) during the subprime crisis. In 2016, it is close to $200 billion.
    Keywords: Systemic Risk, Capital Shortfall, Stress Test, Multi-factor Model
    JEL: C32 G01 G21 G28 G32
    Date: 2018–02
  6. By: Giovanni Caggiano (University of Padova); Efrem Castelnuovo (University of Padova); Gabriela Nodari (Reserve Bank of Australia)
    Abstract: We employ real-time data available to the US monetary policy makers to estimate a Taylor rule augmented with a measure of financial uncertainty over the period 1969-2008. We find evidence in favor of a systematic response to financial uncertainty over and above that to expected inflation, output gap, and output growth. However, this evidence regards the Greenspan-Bernanke period only. Focusing on this period, the "risk-management" approach is found to be responsible for monetary policy easings for up to 75 basis points of the federal funds rate.
    Keywords: Risk management-driven policy rate gap, uncertainty, monetary policy, Taylor rules, real-time data
    JEL: C2 E4 E5
    Date: 2018–07
  7. By: Eric Jondeau (University of Lausanne and Swiss Finance Institute); Jean-Guillaume Sahuc (Banque de France, Université Paris Ouest - Nanterre, and La Défense - EconomiX)
    Abstract: We quantify the capital shortfall that results from a global financial crisis by using a macro-finance dynamic stochastic general equilibrium model that captures the interactions between the financial and real sectors of the economy. We show that a crisis similar to that observed in 2008 generates a capital shortfall (or stressed expected loss, SEL) equal to 2.8% of euro-area GDP, which corresponds to approximately 250 billion euros. We also find that using a cycle-dependent capital ratio that combines concern for both credit growth and SEL has a positive effect on output growth while mitigating the excessive risk taking of the banking system. Finally, our estimates confirm that most of the variability of the macroeconomic and financial variables at business cycle frequencies is due to investment and risk shocks.
    Keywords: Capital Shortfall, Systemic Risk, Leverage, Financial system, Euro Area, DSGE Model
    JEL: E32 E44 G01 G21
    Date: 2018–02
  8. By: Spelta, Alessandro; Pecora, Nicolò; Flori, Andrea; Pammolli, Fabio
    Abstract: The present paper introduces an up-to-date methodology to detect Early Warning Signals of critical transitions, that manifest when distress stages in financial markets are about to take place. As a first step, we demonstrate that a high-dimensional dynamical system can be formulated in a simpler form but in an abstract phase space. Then we detect its approaching towards a critical transition by means of a set of observable variables that exhibit some particular statistical features. We name these variables the Leading Temporal Module. The impactful change in the properties of this group reflects the transition of the system from a normal to a distress state. Starting from these observations we develop an early warning indicator for determining the proximity of a financial crisis. The proposed measure is model free and the application to three different stock markets, together with the comparison with alternative systemic risk measures, highlights the usefulness in signaling upcoming distress phases. Computational results establish that the methodology we propose is effective and it may constitute a relevant decision support mechanism for macro prudential policies.
    Keywords: Financial Crisis, Early Warning Signals, Critical Transition, Leading Temporal Module
    JEL: C02 C53 E37 G01 G17
    Date: 2018–07–23
  9. By: Steven D. Baker; Burton Hollifield; Emilio Osambela
    Abstract: In a market-based democracy, we model different constituencies that disagree regarding the likelihood of economic disasters. Costly public policy initiatives to reduce or eliminate disasters are assessed relative to private alternatives presented by financial markets. Demand for such public policies falls as much as 40% with disagreement, and crowding out by private insurance drives most of the reduction. As support for disaster-reducing policy jumps in periods of disasters, costly policies may be adopted only after disasters occur. In some scenarios constituencies may even demand policies oriented to increase disaster risk if these policies introduce speculative opportunities.
    Keywords: Crowding out ; Disagreement ; Disaster risk ; Government policy ; Willingness to pay
    JEL: G01 G18 H21 H23
    Date: 2018–07–19
  10. By: Marcelo Brutti Righi
    Abstract: In this paper, we address the uncertainty regarding the choice of a probability measure in the context of risk measures theory. To do that, we consider the notion of probability-based risk measurement and propose two general approaches to generate risk measures that are robust. The first approach is a worst-case situation, while the second one is based on weighted averaging. We develop results regarding issues on the theory of risk measures, such as financial, statistical, and continuity properties, as well dual representations. Furthermore, we explore similar results for deviation measures under our proposed framework.
    Date: 2018–07
  11. By: Cecilia Caglio; R. Matthew Darst; Eric Parolin
    Abstract: We construct a novel U.S. data set that matches bank holding company credit default swap (CDS) positions to detailed U.S. credit registry data containing both loan and corporate bond holdings to study the effects of banks' CDS use on corporate credit quality. Banks may use CDS to mitigate agency frictions and not renegotiate loans with solvent but illiquid borrowers resulting in poorer measures of credit risk. Alternatively, banks may lay off the credit risk of high quality borrowers through the CDS market to comply with risk-based capital requirements, which does not impact corporate credit risk. We find new evidence that corporate default probabilities and downgrade likelihoods, if anything, are slightly lower when banks purchase CDS against their borrowers. The results are consistent with banks using CDS to efficiently lay off credit risk rather than inefficiently liquidate firms.
    Keywords: Bank lending ; Credit default swaps ; Risk management
    JEL: G2 G21 G23
    Date: 2018–07–19
  12. By: Aikman, David (Bank of England); Bridges, Jonathan (Bank of England); Burgess, Stephen (Bank of England); Galletly, Richard (Bank of England); Levina, Iren (Bank of England); O'Neill, Cian (Bank of England); Varadi, Alexandra (Bank of England)
    Abstract: We present a framework for measuring the evolution of risks to financial stability over the financial cycle, which we apply to the United Kingdom. We identify 29 indicators of financial stability risk, drawing from the literature on early warning indicators of banking crises. We normalise and aggregate these indicators to produce three composite measures, capturing: leverage in the private nonfinancial sector, including the level and growth of household and corporate debt, as well as the United Kingdom’s external debt; asset valuations in residential and commercial property markets, and in government and corporate bond and equity markets; and credit terms facing household and corporate borrowers. We assess these composite measures relative to their historical distributions. And we present preliminary evidence for how they influence downside risks to economic growth and different horizons. The measures provide an intuitive description of the evolution of the financial cycle of the past three decades. And they could lend themselves to simple communication, both with macroprudential policymakers and the wider public.
    Keywords: Macroprudential policy; financial crises; financial stability; early warning indicators; countercyclical capital buffers; data visualisation
    JEL: E44 G01 G10 G28
    Date: 2018–07–20
  13. By: Ka C. Chan; Ruth F. G. Williams; Christopher T. Lenard; Terence M. Mills
    Abstract: The meaning of public messages such as "One in x people gets cancer" or "One in y people gets cancer by age z" can be improved. One assumption commonly invoked is that there is no other cause of death, a confusing assumption. We develop a light bulb model to clarify cumulative risk and we use Markov chain modeling, incorporating the assumption widely in place, to evaluate transition probabilities. Age-progression in the cancer risk is then reported on Australian data. Future modelling can elicit realistic assumptions.
    Date: 2018–07
  14. By: Jérémy Pépy (CERDI - Centre d'Études et de Recherches sur le Développement International - Clermont Auvergne - UCA - Université Clermont Auvergne - CNRS - Centre National de la Recherche Scientifique); Benjamin Williams (CRCGM - Centre de Recherche Clermontois en Gestion et Management - Clermont Auvergne - École Supérieure de Commerce (ESC) - Clermont-Ferrand - UCA - Université Clermont Auvergne)
    Abstract: The failures of the banking sector to promote sustainable lending and to build strong capital and liquidity buffers prior to the 2008 Financial Crisis addressed the rationale for implementing the banking regulatory regime Basel III. In this paper, we question the fundamental role of this new regulatory regime in promoting bank lending and ensuring the adequate funding structure of the banking sector regarding the introduction of unprecedented international liquidity standards notably. We build a theoretical model of bank behaviour under a regulatory regime à la Basel III which points to two major results. First, Regulatory Authorities need to define the objectives and thus, the underlying tools implemented in order to achieve the optimum-optimurum. Second, we show that the competitive structure of the markets the bank faces is a determinant to take into account for achieving this optimum-optimurum.
    Keywords: Basel III, Regulation, Bank behaviour, Regulatory distortions
    Date: 2018–07–19
  15. By: Stephan Schwill
    Abstract: This thesis applies entropy as a model independent measure to address three research questions concerning financial time series. In the first study we apply transfer entropy to drawdowns and drawups in foreign exchange rates, to study their correlation and cross correlation. When applied to daily and hourly EUR/USD and GBP/USD exchange rates, we find evidence of dependence among the largest draws (i.e. 5% and 95% quantiles), but not as strong as the correlation between the daily returns of the same pair of FX rates. In the second study we use state space models (Hidden Markov Models) of volatility to investigate volatility spill overs between exchange rates. Among the currency pairs, the co-movement of EUR/USD and CHF/USD volatility states show the strongest observed relationship. With the use of transfer entropy, we find evidence for information flows between the volatility state series of AUD, CAD and BRL. The third study uses the entropy of S&P realised volatility in detecting changes of volatility regime in order to re-examine the theme of market volatility timing of hedge funds. A one-factor model is used, conditioned on information about the entropy of market volatility, to measure the dynamic of hedge funds equity exposure. On a cross section of around 2500 hedge funds with a focus on the US equity markets we find that, over the period from 2000 to 2014, hedge funds adjust their exposure dynamically in response to changes in volatility regime. This adds to the literature on the volatility timing behaviour of hedge fund manager, but using entropy as a model independent measure of volatility regime.
    Date: 2018–07
  16. By: Zsolt Bihary (Corvinus University of Budapest, Corvinus Business School, Department of Finance); Peter Csoka ("Momentum" Game Theory Research Group, Centre for Economic and Regional Studies, Hungarian Academy of Sciences and Corvinus University of Budapest, Corvinus Business School, Department of Finance); David Zoltan Szabo (School of Mathematics, University of Manchester)
    Abstract: We investigate how the spectral risk measure associated with holding stocks rather than a risk-free deposit, depends on the holding period. Previous papers have shown that within a limited class of spectral risk measures, and when the stock price follows specific processes, spectral risk becomes negative at long periods. We generalize this result for arbitrary exponential Lévy processes. We also prove the same behavior for all spectral risk measures (including the important special case of Expected Shortfall) when the stock price grows realistically fast and when it follows a Geometric Brownian Motion or a Finite Moment Log Stable process. This result would suggest that holding stocks for long periods has a vanishing risk. However, using realistic models, we find numerically that the risk increases for a few decades and reaches zero at around 100 years. Therefore, we conclude that holding stocks is risky for all practically relevant periods.
    Keywords: Coherent Risk Measures, Spectral Risk Measures, Lévy processes, Finite Moment Log Stable Model, Time Diversification
    JEL: G11
    Date: 2018–06
  17. By: Zachary Feinstein
    Abstract: We construct a continuous time model for price-mediated contagion precipitated by a common exogenous stress to the trading book of all firms in the financial system. In this setting, firms are constrained so as to satisfy a risk-weight based capital ratio requirement. We use this model to find analytical bounds on the risk-weights for an asset as a function of the market liquidity. Under these appropriate risk-weights, we find existence and uniqueness for the joint system of firm behavior and the asset price. We further consider an analytical bound on the firm liquidations, which allows us to construct exact formulas for stress testing the financial system with deterministic or random stresses. Numerical case studies are provided to demonstrate various implications of this model and analytical bounds.
    Date: 2018–07
  18. By: Suarez, Ronny
    Abstract: In this paper, we estimated return levels of a portfolio of two assets using extreme value theory.
    Keywords: Generalized Pareto Distribution, Return Level
    JEL: C10
    Date: 2018–07–05
  19. By: Eric Benhamou; Beatrice Guez
    Abstract: We present a new methodology of computing incremental contribution for performance ratios for portfolio like Sharpe, Treynor, Calmar or Sterling ratios. Using Euler's homogeneous function theorem, we are able to decompose these performance ratios as a linear combination of individual modified performance ratios. This allows understanding the drivers of these performance ratios as well as deriving a condition for a new asset to provide incremental performance for the portfolio. We provide various numerical examples of this performance ratio decomposition.
    Date: 2018–07
  20. By: Ines Chaieb (University of Geneva and Swiss Finance Institute); Vihang R. Errunza (McGill University); Hugues Langlois (HEC Paris)
    Abstract: We develop an asset pricing model to analyze the joint impact of liquidity costs and market segmentation. The freely traded securities command a premium for liquidity level and global market and liquidity risk premiums whereas securities that can only be held by a subset of investors additionally command a local market and liquidity risk premiums. Based on a new methodology, we find that the liquidity level premium dominates the liquidity risk premiums for our sample of 24 emerging markets. Whereas the local liquidity risk premium is empirically small, the global market liquidity risk premium dramatically increases during crises and market corrections.
    Keywords: International asset pricing, liquidity risk, transaction cost, emerging markets, market integration.
    JEL: G12 G15 F30 G20 G30
    Date: 2018–01
  21. By: Severine Arnold (-Gaille) (University of Lausanne); Anca Jijiie (Faculty of Business and Economics); Eric Jondeau (University of Lausanne and Swiss Finance Institute); Michael Rockinger (University of Lausanne, Centre for Economic Policy Research (CEPR), and Swiss Finance Institute)
    Abstract: The increase in life expectancy over the past several decades has been impressive and represents a key challenge for institutions that provide life insurance products. Indeed, when a new actuarial table is released with updated survival and death rates, such institutions need to update the amount of mathematical reserve that they need to set aside to guarantee the future payments of their annuities. As mortality forecasting techniques are currently well developed, it is relatively easy to forecast mortality over several decades and to directly use these forecast rates in the determination of the mathematical reserve needed to guarantee annuity payments. Future mortality evolution is then directly incorporated into the liabilities valuation of an institution, and it is thus commonly believed that such liabilities should not require much updating when a new actuarial table is released. In this paper, we demonstrate that contrary to this common belief, institutions that use generational tables (namely, tables including future mortality evolution) will most likely need to make more important adjustments (positive or negative) to their liabilities than will institutions using periodic (static) tables whenever a new table is released. By using three very different models to project mortality, we demonstrate that our findings are inherent in the required long horizons of the forecasts needed in the generational approach, with the uncertainty surrounding the forecast values increasing with the horizon. Therefore, generational tables may introduce more instability in a pension institution’s accounts than periodic tables.
    Keywords: Mortality rates, Periodic actuarial tables, Generational actuarial tables, Life expectancy, Mathematical reserve, Mortality forecasts
    Date: 2018–01
  22. By: Eric Budish
    Abstract: The amount of computational power devoted to anonymous, decentralized blockchains such as Bitcoin's must simultaneously satisfy two conditions in equilibrium: (1) a zero-profit condition among miners, who engage in a rent-seeking competition for the prize associated with adding the next block to the chain; and (2) an incentive compatibility condition on the system's vulnerability to a “majority attack”, namely that the computational costs of such an attack must exceed the benefits. Together, these two equations imply that (3) the recurring, “flow”, payments to miners for running the blockchain must be large relative to the one-off, “stock”, benefits of attacking it. This is very expensive! The constraint is softer (i.e., stock versus stock) if both (i) the mining technology used to run the blockchain is both scarce and non-repurposable, and (ii) any majority attack is a “sabotage” in that it causes a collapse in the economic value of the blockchain; however, reliance on non-repurposable technology for security and vulnerability to sabotage each raise their own concerns, and point to specific collapse scenarios. In particular, the model suggests that Bitcoin would be majority attacked if it became sufficiently economically important — e.g., if it became a “store of value” akin to gold — which suggests that there are intrinsic economic limits to how economically important it can become in the first place.
    JEL: A1 D00 D53 E4 E42 G1 G12 G2 L99
    Date: 2018–06

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