nep-rmg New Economics Papers
on Risk Management
Issue of 2016‒07‒23
twenty papers chosen by
Stan Miles
Thompson Rivers University

  1. Portfolio Selection with Active Risk Monitoring By Marc S. PAOLELLA; Pawel POLAK
  2. Insurance valuation: a computable multi-period cost-of-capital approach By Hampus Engsner; Mathias Lindholm; Filip Lindskog
  3. Risk-Adjusted Time Series Momentum By Martin DUDLER; Bruno GMUER; Semyon MALAMUD
  4. Portfolio Selection with Options and Transaction Costs By Semyon MALAMUD
  5. Multiple risk factor dependence structures: Distributional properties By Jianxi Su; Edward Furman
  6. Estimating the Joint Tail Risk Under the Filtered Historical Simulation. An Application to the CCP's Default and Waterfall Fund By Giovanni BARONE-ADESI; Kostas GIANNOPOULOS; Les VOSPER
  7. Analysing the Determinants of Credit Risk for General Insurance Firms in the UK By Guglielmo Maria Caporale; Mario Cerrato; Xuan Zhang
  8. A form of multivariate Pareto distribution with applications to financial risk measurement By Jianxi Su; Edward Furman
  9. A Fast, Accurate Method for Value at Risk and Expected Shortfall By Jochen KRAUSE; Marc S. PAOLELLA
  10. Hedging under generalized good-deal bounds and model uncertainty By Dirk Becherer; Klebert Kentia
  11. Bank Risk Proxies and the Crisis of 2007/09: A Comparison By Noth, Felix; Tonzer, Lena
  12. Pay Attention or Pay Extra: Evidence on the Compensation of Investors for the Implicit Credit Risk of Structured Products By Marc ARNOLD; Dustin SCHUETTE; Alexander WAGNER
  13. portfolio management with Islam Equity in Korea stock market By Hong-Bae Kim
  14. Tail protection for long investors: Trend convexity at work By Tung-Lam Dao; Trung-Tu Nguyen; Cyril Deremble; Yves Lemp\'eri\`ere; Jean-Philippe Bouchaud; Marc Potters
  15. Long/Short Equity Hedge Funds and Systematic Ambiguity By Rajna Gibson BRANDON; Nikolay RYABKOV
  16. Basel 3: Does One Size Really Fit All Banks' Business Models? By Giuliana Birindelli; Paola Ferretti; Marco Savioli
  17. “Total Assets” versus “Risk Weighted Assets”: Does it matter for MREL requirements? By Martin Hellwig
  18. An ergodic BSDE approach to entropic risk measure and its large time behavior By Wing Fung Chong; Ying Hu; Gechun Liang; Thaleia Zariphopoulou
  19. The Role of Complexity for Bank Risk during the Financial Crisis: Evidence from a Novel Dataset By Krause, Thomas; Sondershaus, Talina; Tonzer, Lena
  20. Crashes and High Frequency Trading By Didier SORNETTE; Susanne VON DER BECKE

  1. By: Marc S. PAOLELLA (University of Zurich and Swiss Finance Institute); Pawel POLAK (University of Zurich and Swiss Finance Institute)
    Abstract: The paper proposes a framework for large-scale portfolio optimization which accounts for all the major stylized facts of multivariate financial returns, including volatility clustering, dynamics in the dependency structure, asymmetry, heavy tails, and nonellipticity. It introduces a so-called risk fear portfolio strategy which combines portfolio optimization with active risk monitoring. The former selects optimal portfolio weights. The later, independently, initiates market exit in case of excessive risks. The strategy agrees with the stylized fact of stock market major sell-offs during the initial stage of market downturns. The advantages of the new framework are illustrated with an extensive empirical study. It leads to superior multivariate density and Value-at-Risk forecasting, and better portfolio performance. The proposed risk fear portfolio strategy outperforms various competing types of optimal portfolios, even in the presence of conservative transaction costs and frequent rebalancing. The risk monitoring of the optimal portfolio can serve as an early warning system against large market risks. In particular, the new strategy avoids all the losses during the 2008 financial crisis, and it profits from the subsequent market recovery.
    Keywords: COMFORT; Financial Crises; Portfolio Optimization; Risk Monitoring
    JEL: C51 C53 C58 G11 G17
  2. By: Hampus Engsner; Mathias Lindholm; Filip Lindskog
    Abstract: We present an approach to market-consistent multi-period valuation of insurance liability cash flows based on a two-stage valuation procedure. First, a portfolio of traded financial instrument aimed at replicating the liability cash flow is fixed. Then the residual cash flow is managed by repeated one-period replication using only cash funds. The latter part takes capital requirements and costs into account, as well as limited liability and risk averseness of capital providers. The cost-of-capital margin is the value of the residual cash flow. We set up a general framework for the cost-of-capital margin and relate it to dynamic risk measurement. Moreover, we present explicit formulas and properties of the cost-of-capital margin under further assumptions on the model for the liability cash flow and on the conditional risk measures and utility functions. Finally, we highlight computational aspects of the cost-of-capital margin, and related quantities, in terms of an example from life insurance.
    Date: 2016–07
  3. By: Martin DUDLER (Quantica Capital); Bruno GMUER (Quantica Capital); Semyon MALAMUD (Ecole Polytechnique Fédérale de Lausanne and Swiss Finance Institute)
    Abstract: We introduce a new class of momentum strategies, the risk-adjusted time series momentum (RAMOM) strategies, which are based on averages of past futures returns, normalized by their volatility. We test these strategies on a universe of 64 liquid futures contracts and show that RAMOM strategies outperform the time series momentum (TSMOM) strategies of Ooi, Moskowitz, and Pedersen (2012) for almost all combinations of holding and look-back periods. This outperformance is driven by the following new striking stylized fact that we document: For almost all of the 64 futures contracts, independent of the asset class, realized futures volatility is contemporaneously negatively related to the Fama and French (1987) market (MKT), value (HML), and momentum (UMD) factors. As a result, RAMOM returns have a natural, built-in exposure to the MKT, HML, and UMD factors and outperform TSMOM returns precisely in times when (some of) the factors deliver good returns. In particular, RAMOM allows investors to gain significant exposure to Fama and French factors without actually trading the very large stock universe. Furthermore, dollar turnover of RAMOM strategies is about 40% lower than that of TSMOM, implying a drastic reduction in trading costs. We construct measures of momentum-specific volatility, both within and across asset classes, and show how these volatility measures can be used for risk management. We find that momentum risk management significantly increases Sharpe ratios, but at the same time may lead to more pronounced negative skewness and tail risk. Furthermore, momentum risk management leads to a much lower exposure to market, value, and momentum factors; as a result, risk-managed momentum returns offer much higher diversification benefits than those of standard momentum returns.
    Keywords: Momentum, risk, return, volatility, trend following
    JEL: C41 G11
  4. By: Semyon MALAMUD (EPFL and Swiss Finance Institute)
    Abstract: I introduce dynamic option trading and non-linear views into the classical portfolio selection problem. The optimal dynamic option portfolio is characterized explicitly in terms of its expected sensitivities (Greeks) and the role of the mean-variance efficient portfolio is played by the "Greek efficient" portfolio. This is the portfolio that has the optimal sensitivities to chosen risk factors. I test these portfolios empirically and find that options signifi cantly improve the risk-return pro file due to predictability of powers (and other non-linear functions) of returns which allows for optimal management of non-linear views. To test the eff ects of higher moments on portfolio choice, I compute (both analytically and numerically) the Greek efficient portfolios for a CRRA investor and find that accounting for higher moments may have ambiguous eff ects on the optimal tail risk. In fact, even Greek efficient portfolios for a mean-variance investor already o er a highly attractive skewness-kurtosis profi le. In the presence of transactions costs that depend on an option's moneyness and maturity, optimal state contingent option portfolios are characterized in terms of state prices Greeks as well as a new object, the transactions costs Greeks.
    Keywords: portfolio selection, dynamic trading, options, Greeks, transaction costs
    JEL: G11 G13
  5. By: Jianxi Su; Edward Furman
    Abstract: We introduce a class of dependence structures, that we call the Multiple Risk Factor (MRF) dependence structures. On the one hand, the new constructions extend the popular CreditRisk+ approach, and as such they formally describe default risk portfolios exposed to an arbitrary number of fatal risk factors with conditionally exponential and dependent hitting (or occurrence) times. On the other hand, the MRF structures can be seen as an encompassing family of multivariate probability distributions with univariate margins distributed Pareto of the 2nd kind, and in this role they can be used to model insurance risk portfolios of dependent and heavy tailed risk components.
    Date: 2016–07
  6. By: Giovanni BARONE-ADESI (University of Lugano and Swiss Finance Institute); Kostas GIANNOPOULOS (Neapolis University, Pafos); Les VOSPER (London Metal Exchange)
    Abstract: To ensure that central counterparties (“CCPs”) are safe in all market conditions the European Union (EU) has adopted legislation, commonly known as the European Market Infrastructure Regulation (“EMIR”) that deals with their organisational requirements, including prudential requirements in relations to margins and the waterfall and default funds. It has published in a single Regulation (EU) No 153/2013, the technical standards required to be adopted by all CCPs operating in the EU. EMIR requires a mandatory clearing of certain standardised OTC (i.e. over-the-counter) derivatives transactions through central counterparties. A risk methodology that can meet some of the most challenging technical requirements, such as sensitivity testing, estimating the probability of joint member defaults and reverse stress testing, is the Filtered Historical Simulation (FHS). In this study we extend the use of Filtered Historical Simulation in estimating the potential losses the CCP would face from a multiple default. The proposed methodology provides a probabilistic estimation of defaulting of named members, the expected size of losses, i.e. the joint expected shortfall (JES), and confidence intervals around the JES. This in turn provides an estimate of financial resources needed to absorb multiple defaults. Our methodology is carrying a full re-pricing of all instruments in the portfolio. It takes into account positions that expire before the profits and losses (P&L) horizon. Order statistics tell us that estimates on the tails are unreliable. To improve their reliability we carry out a bootstrapping of 5,000,000 simulation trials. The bootstrapping of 5,000,000 trials is repeated 5,000 times to generate the density of the JES.
    Keywords: Central counterparty risk management, filtered historical simulation, stress testing, tail dependency
    JEL: C4 G21 G23
  7. By: Guglielmo Maria Caporale; Mario Cerrato; Xuan Zhang
    Abstract: Abstract This paper estimates a reduced-form model to assess the credit risk of General Insurance (GI) non-life firms in the UK. Compared to earlier studies, it uses a much larger sample including 30 years of data for 515 firms, and also considers a much wider set of possible determinants of credit risk. The empirical results suggest that macroeconomic and firm-specific factors both play important roles. Other key findings are the following: credit risk varies across firms depending on their business lines; there is default clustering in the GI industry; different reinsurance levels also affect the credit risk of insurance firms. The implications of these findings for regulators of GI firms under the coming Solvency II are discussed.
    Keywords: Insolvent, Doubly Stochastic, Insurance, Reinsurance
    JEL: G22 C58
    Date: 2016
  8. By: Jianxi Su; Edward Furman
    Abstract: A new multivariate distribution possessing arbitrarily parametrized and positively dependent univariate Pareto margins is introduced. Unlike the probability law of Asimit et al. (2010) [Asimit, V., Furman, E. and Vernic, R. (2010) On a multivariate Pareto distribution. Insurance: Mathematics and Economics 46(2), 308-316], the structure in this paper is absolutely continuous with respect to the corresponding Lebesgue measure. The distribution is of importance to actuaries through its connections to the popular frailty models, as well as because of the capacity to describe dependent heavy-tailed risks. The genesis of the new distribution is linked to a number of existing probability models, and useful characteristic results are proved. Expressions for, e.g., the decumulative distribution and probability density functions, (joint) moments and regressions are developed. The distributions of minima and maxima, as well as, some weighted risk measures are employed to exemplify possible applications of the distribution in insurance.
    Date: 2016–07
  9. By: Jochen KRAUSE (University of Zurich); Marc S. PAOLELLA (University of Zurich and Swiss Finance Institute)
    Abstract: A fast method is developed for value at risk and expected shortfall prediction for univariate asset return time series exhibiting leptokurtosis, asymmetry, and conditional heteroskedasticity. It is based on a GARCH-type process driven by noncentral t innovations. While the method involves use of several shortcuts for speed, it performs admirably in terms of accuracy, and actually outperforms highly competitive models.
    Keywords: GARCH, Mixture-Normal-GARCH, Noncentral t, Table Lookup
    JEL: C51 C53 G11 G17
  10. By: Dirk Becherer; Klebert Kentia
    Abstract: We study a notion of good-deal hedging, that corresponds to good-deal valuation for generalized good-deal constraints. Under model uncertainty about the market prices of risk of hedging assets, a robust approach leads to a reduction or even elimination of a speculative component in good-deal hedging, which is shown to be equivalent to a global risk-minimization in the sense of F\"ollmer and Sondermann (1986) if uncertainty is sufficiently large. Constructive results on hedges and valuations are derived from backward stochastic differential equations, including new examples with explicit formulas.
    Date: 2016–07
  11. By: Noth, Felix; Tonzer, Lena
    Abstract: Motivated by the variety of bank risk proxies, our analysis reveals that nonperforming assets are a well-suited complement to the Z-score in studies of bank risk.
    Keywords: Banking,Financial Institutions,Risk Proxie
    JEL: G21 G28 G32
    Date: 2015
  12. By: Marc ARNOLD (University of St. Gallen); Dustin SCHUETTE (University of St. Gallen); Alexander WAGNER (University of Zurich and Swiss Finance Institute)
    Abstract: This paper analyzes the pricing of issuer credit risk in retail structured products. After the default of Lehman Brothers, investors are compensated for the counterparty risk they bear if the products are not constructed to provide an implicit "credit enhancement", i.e., if they do not feature a sufficiently high correlation of the promised payout and the issuer's financial health. Before the financial crisis, and during the crisis up to the default of Lehman Brothers, investors are not compensated for credit risk. As the default of Lehman Brothers has arguably sharpened investors' attention for counterparty risk, these results suggest that whether issuers compensate investors for a certain risk does not only depend on the level but on investors' awareness for the corresponding risk. Our findings have regulatory and policy implications.
    Keywords: Structured products, credit risk, risk awareness
    JEL: D8 G34 M52
  13. By: Hong-Bae Kim (Dongseo University)
    Abstract: This paper investigated the volatility spillover effects between Islamic stock markets and Korean stock market using the AR-DCC-GARCH models. First, we found bi-directional volatility transmissions between the Islamic and Korean financial markets Second, we compared the correlation of KOSPI-DJIM portfolio and that of KOSPI-SHX portfolio. It shows the correlation of KOSPI-DJIM portfolio has stronger linkage than that of KOSPI-SHX portfolio. In the portfolio perspective, the S&P 500 Sharia stock Index(SHX) acts as a better hedge asset than DJIM against the risk of stock market. Last, The hedge ratio between two Islamic stock market and Korean stock market pairs is generally low, indicating that the Korean stock risk can be effectively hedged by taking a short position in the Islamic stock markets. In comparison with two pairs, the pair of KOSPI-SHX relatively shows a cheaper hedging cost than that of KOSP-DJIM pair. This evidence indicates that S&P 500 Sharia index serve more effective hedging role against the risk of Korean stock market.
    Keywords: Islamic market, hedge ratio, AR-DCC-GARCH model
    JEL: G11 G15
  14. By: Tung-Lam Dao; Trung-Tu Nguyen; Cyril Deremble; Yves Lemp\'eri\`ere; Jean-Philippe Bouchaud; Marc Potters
    Abstract: The performance of trend following strategies can be ascribed to the difference between long-term and short-term realized variance. We revisit this general result and show that it holds for various definitions of trend strategies. This explains the positive convexity of the aggregate performance of Commodity Trading Advisors (CTAs) which -- when adequately measured -- turns out to be much stronger than anticipated. We also highlight interesting connections with so-called Risk Parity portfolios. Finally, we propose a new portfolio of strangle options that provides a pure exposure to the long-term variance of the underlying, offering yet another viewpoint on the link between trend and volatility.
    Date: 2016–07
  15. By: Rajna Gibson BRANDON (University of Geneva and Swiss Finance Institute); Nikolay RYABKOV (University of Zurich and Swiss Finance Institute)
    Abstract: This study presents a hedge fund portfolio choice model for an investor facing ambiguity. In the empirical section, we measure ambiguity as the cross-sectional dispersion in Industrial Production growth and in stock market return forecasts, and we construct the systematic ambiguity factors from the universe of S&P 500 stocks. We estimate ambiguity betas for long/short equity hedge funds strategies and document signi cant ambiguity exposures for directional L/S equity hedge funds. We compare the out-of-sample performance of portfolios constructed according to the L/S hedge fund alphas' ranking with and without systematic ambiguity exposures and nd that the former outperform.
    Keywords: Ambiguity, Asset Allocation, Long/Short Equity Hedge Funds, Performance Measurement
    JEL: G11
  16. By: Giuliana Birindelli (Department of Management and Business Administration, University of Chieti-Pescara, Italy); Paola Ferretti (Department of Economics and Management, University of Pisa, Italy); Marco Savioli (Department of Economics, University of Bologna, Italy; The Rimini Centre for Economic Analysis, Italy)
    Abstract: Based on a sample of eurozone banks classified into six business models over the period 2001–2014, this paper aims to investigate whether and how strongly the Basel 3 requirements affect differently the stability of banks working under different business models. Our findings show that, irrespective of the business model, the most positive driver of banks' stability is the leverage ratio, followed by the net stable funding ratio. The interactions with banks' business models allow us to highlight significant differences in the coefficients of the Basel 3 variables. In particular, savings banks are predicted to gain the greatest advantage from our set of identified reform measures in banking prudential regulation; on the contrary, commercial and investment banks are the least advantaged. Thus, our findings stress the need to revise the current “one-size-fits-all” prudential framework.
    Keywords: Basel 3, banks' business model, financial stability
    JEL: G21 G28
    Date: 2016–07
  17. By: Martin Hellwig (Max Planck Institute for Research on Collective Goods)
    Abstract: The paper discusses the role of risk weighting in the determination of minimum requirements for eligible bail-in-able liabilities of banks (MREL), i.e. liabilities that are not exempt from the bail-in tool in bank resolution and that can be written down or converted into equity if losses on assets exceed the available equity and such bailing-in is required to re-establish bank solvency so as to provide a basis for maintaining systemically important operations in resolution. The paper begins with a general discussion of the reasons for introducing bank resolution as a special procedure outside of insolvency law, of the reasons for having the bail-in tool and of the frictions that may stand in the way of successful and frictionless resolution. This discussion emphasizes the importance of having sufficient bail-in-able liabilities available; in contrast, for large institutions that have access to bond markets, the social costs of such requirements are small (unlike the private costs to the banks themselves). However, neither risk weighted nor total assets provide proper guidance for determining MREL. Risk-weighting suffers from a lack of a proper statistical basis and a certain manipulability. Moreover, the risk weighting that is used for capital regulation is not well suited for determining MREL; whereas capital regulation focuses on the probability of bad results, MREL is concerned with the extent of losses conditional on results being bad. “Total assets” suffer from not truly representing total assets because various rules, e.g. for netting, allow banks to keep certain assets and liabilities off their balance sheets.
    Date: 2016–07
  18. By: Wing Fung Chong; Ying Hu; Gechun Liang; Thaleia Zariphopoulou
    Abstract: This paper shows that the long-time behavior of the entropic risk measure (under both forward performance process framework and classical utility framework) converges to a constant, which is independent of the initial state of the stochastic factors in a stochastic factor model. The exponential convergence rate to the long-term limit is also obtained by using ergodic backward stochastic differential equation method. Finally, the paper establishes a connection between the two notions of entropic risk measures and their large time behavior.
    Date: 2016–07
  19. By: Krause, Thomas; Sondershaus, Talina; Tonzer, Lena
    Abstract: We construct a novel dataset to measure banks' complexity and relate it to banks' riskiness. The sample covers stock listed Euro area banks from 2007 to 2014. Bank stability is significantly affected by complexity, whereas the direction of the effect differs across complexity measures. This heterogeneity advises against the use of a single complexity measure when evaluating the implications of bank complexity.
    Keywords: bank risk,complexity,globalization
    JEL: G01 G20 G33
    Date: 2016
  20. By: Didier SORNETTE (ETH Zurich and Swiss Finance Institute); Susanne VON DER BECKE (ETH Zurich)
    Abstract: We present a partial review of the potential for bubbles and crashes associated with high frequency trading (HFT). Our analysis intends to complement still inconclusive academic literature on this topic by drawing upon both conceptual frameworks and indicative evidence observed in the markets. A generic classification in terms of Barenblatt’s theory of similarity is proposed that suggests, given the available empirical evidence, that HFT has profound consequences for the organization and time dynamics of market prices. Provided one accepts the evidence that financial stock returns exhibit multifractal properties, it is likely that HFT time scales and the associated structures and dynamics do significantly affect the overall organization of markets. A significant scenario of Barenblatt’s classification is called “non-renormalizable”, which corresponds to HFT functioning essentially as an accelerator to previous market dynamics such as bubbles and crashes. New features can also be expected to occur, truly innovative properties that were not present before. This scenario is particularly important to investigate for risk management purposes. This report thus suggests a largely positive answer to the question: “Can high frequency trading lead to crashes?” We believe it has in the past, and it can be expected to do so more and more in the future. Flash crashes are not fundamentally a new phenomenon, in that they do exhibit strong similarities with previous crashes, albeit with different specifics and of course time scales. As a consequence of the increasing inter-dependences between various financial instruments and asset classes, one can expect in the future more flash crashes involving additional markets and instruments. The technological race is not expected to provide a stabilization effect, overall. This is mainly due to the crowding of adaptive strategies that are pro-cyclical, and no level of technology can change this basic fact, which is widely documented for instance in numerical simulations of agent-based models of financial markets. New “crash algorithms” will likely be developed to trade during periods of market stresses in order to profit from these periods. Finally, we argue that flash crashes could be partly mitigated if the central question of the economic gains (and losses) provided by HFT was considered seriously. We question in particular the argument that HFT provides liquidity and suggest that the welfare gains derived from HFT are minimal and perhaps even largely negative on a long-term investment horizon. This question at least warrants serious considerations especially on an empirical basis. As a consequence, regulations and tax incentives constitute the standard tools of policy makers at their disposal within an economic context to maximize global welfare (in contrast with private welfare of certain players who promote HFT for their private gains). We believe that a complex systems approach to future research can provide important and necessary insights for both academics and policy makers.
    Keywords: High-frequency trading, financial crashes, flash crash, liquidity, efficient market hypothesis, market makers, market breakers, herding, financial bubbles, computer trading, algorithmic trading.
    JEL: G01 G14

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