nep-rmg New Economics Papers
on Risk Management
Issue of 2018‒05‒21
eighteen papers chosen by
Stan Miles
Thompson Rivers University

  1. Property Portfolio Management - Monitoring, Managing and Mitigating Property Market Risk By Charles Ostroumoff
  2. Improving Value-at-Risk prediction under model uncertainty By Shuzhen Yang; Jianfeng Yao
  3. A comprehensive view on risk reporting: Evidence from supervisory data By Abbassi, Puriya; Schmidt, Michael
  4. The economics and management of flood risk in Germany By Volker Meyer; Reimund Schwarze
  5. Chebyshev Methods for Ultra-efficient Risk Calculations By Mariano Zeron Medina Laris; Ignacio Ruiz
  6. Cyclical variations in liquidity risk of corporate bonds By Anténor-Habazac, Cassandre; Dionne, Georges; Guesmi, Sahar
  7. When panic makes you blind: a chaotic route to systemic risk By Piero Mazzarisi; Fabrizio Lillo; Stefano Marmi
  8. Unprofitable tenants: the usual suspects? A case study of modelling tenant profitability By Bernd Kolkmann; Ingrid Janssen
  9. Could “Tontines” Expand the Market for Longevity Insurance? By Gal Wettstein
  10. Characteristics Are Covariances: A Unified Model of Risk and Return By Bryan Kelly; Seth Pruitt; Yinan Su
  11. Optimal Model Averaging of Mixed-Data Kernel-Weighted Spline Regressions By Jeffrey S. Racine; Qi Li; Li Zheng
  12. Standard Risk Aversion and Efficient Risk Sharing By Suen, Richard M. H.
  13. On the Rise of FinTechs – Credit Scoring using Digital Footprints By Tobias Berg; Valentin Burg; Ana Gombović; Manju Puri
  14. The Hidden Predictive Power of Cryptocurrencies: Evidence from US Stock Market By Kazeem Isah; Ibrahim D. Raheem
  15. Safe asset shortage by regulation By Demary, Markus; Voigtländer, Michael
  16. Bitcoin is not the New Gold - A Comparison of Volatility, Correlation, and Portfolio Performance By Thomas Walther; Tony Klein; Hien Pham Thu;
  17. Solvency Risk Premia and the Carry Trades By Vitaly Orlov; ;
  18. Cash Holdings and the Performance of European Mutual Funds By Frank Graef; Pascal Vogt; Volker Vonhoff; Florian Weigert

  1. By: Charles Ostroumoff
    Abstract: This paper examines portfolio risk management techniques and tools, commonly used in equity and bond portfolios, to: measure, manage and mitigate property market risk / "beta". The techniques used to measure and manage property market risk uses annual historical capital value returns of UK indices (Peter Scott’s data from 1920 and MSCI-IPD Data from 1972). These values are then adjusted for inflation and a trend line is established to form a dynamic gauge identifying where we are in the property cycle by indicating when the market is over / undervalued, based off historical metrics. By measuring and monitoring the property market practitioners (asset allocators / fund managers / risk managers) can use an innovative beta risk management tool (MSCI-IPD Futures) to apply "risk on" / "risk off" strategies at specific points in the cycle. Whilst the analysis and approach was applied to the UK property investment market, the approach can be applied to any property market where high quality historical data is evident and where a listed futures market has developed.
    Keywords: Capital Values; MSCI-IPD Futures; Portfolio Management; Property Beta; Risk Management
    JEL: R3
    Date: 2017–07–01
  2. By: Shuzhen Yang; Jianfeng Yao
    Abstract: Several well-established benchmark predictors exist for Value-at-Risk (VaR), a major instrument for financial risk management. Hybrid methods combining AR-GARCH filtering with skewed-$t$ residuals and the extreme value theory-based approach are particularly recommended. This study introduces yet another VaR predictor, G-VaR, which follows a novel methodology. Inspired by the recent mathematical theory of sublinear expectation, G-VaR is built upon the concept of model uncertainty, which in the present case signifies that the inherent volatility of financial returns cannot be characterized by a single distribution but rather by infinitely many statistical distributions. By considering the worst scenario among these potential distributions, the G-VaR predictor is precisely identified. Extensive experiments on both the NASDAQ Composite Index and S\&P500 Index demonstrate the excellent performance of the G-VaR predictor, which is superior to most existing benchmark VaR predictors.
    Date: 2018–05
  3. By: Abbassi, Puriya; Schmidt, Michael
    Abstract: We show that banks' risk exposure in one asset category affects how they report regulatory risk weights for another asset category. Specifically, banks report lower credit risk weights for their loan portfolio when they face higher risk exposure in their trading book. This relationship is especially strong for banks that have binding regulatory capital constraints. Our results suggest the existence of incentive spillovers across different risk categories. We relate this behavior to the discretion inherent in internal ratings-based models which these banks use to assess risk. These findings imply that supervision should include a comprehensive view of different bank risk dimensions.
    Keywords: internal ratings-based regulation,credit risk,market risk,incentive spillovers,capital regulation,comprehensive risk assessment
    JEL: G01 G21 G28
    Date: 2018
  4. By: Volker Meyer (Helmholtz-Zentrum für Umweltforschung − UFZ); Reimund Schwarze (Europa University Viadrina and Helmholtz Centre for Environmental Research (UFZ))
    Abstract: Assessing the economic impacts of flooding is a crucial part of identifying appropriate flood risk management options as required by the EU flood management directive. This chapter describes methods for assessing economic flood damage. To begin, some fundamental issues are discussed: Which types of economic flood damage should be taken into account? What kind of information is necessary in general for assessing flood damage in monetary terms and what is the general procedure for calculating economic flood damage? Having clarified these questions, the methodological challenges posed by economic flood risk management are described. This includes the indirect impacts, i.e. induced loss to customers and suppliers of good and services damaged by floods, and intangible impacts, i.e. the impacts of flooding on mortality and morbidity and the environment. Ways to deal with the persistent uncertainty in damage and risk assessments are discussed in the following chapter. The findings in this chapter will be evaluated in relation to flood risk management practices in Germany, based on examples from Saxony.
    Date: 2018–05
  5. By: Mariano Zeron Medina Laris; Ignacio Ruiz
    Abstract: Financial institutions now face the important challenge of having to do multiple portfolio revaluations for their risk computation. The list is almost endless: from XVAs to FRTB, stress testing programs, etc. These computations require from several hundred up to a few million revaluations. The cost of implementing these calculations via a "brute-force" full revaluation is enormous. There is now a strong demand in the industry for algorithmic solutions to the challenge. In this paper we show a solution based on Chebyshev interpolation techniques. It is based on the demonstrated fact that those interpolants show exponential convergence for the vast majority of pricing functions that an institution has. In this paper we elaborate on the theory behind it and extend those techniques to any dimensionality. We then approach the problem from a practical standpoint, illustrating how it can be applied to many of the challenges the industry is currently facing. We show that the computational effort of many current risk calculations can be decreased orders of magnitude with the proposed techniques, without compromising accuracy. Illustrative examples include XVAs and IMM on exotics, XVA sensitivities, Initial Margin Simulations, IMA-FRTB and AAD.
    Date: 2018–05
  6. By: Anténor-Habazac, Cassandre (HEC Montreal, Canada Research Chair in Risk Management); Dionne, Georges (HEC Montreal, Canada Research Chair in Risk Management); Guesmi, Sahar (HEC Montreal, Department of Decision science)
    Abstract: We study regime switching features of liquidity risk in corporate bond premiums. Within a sample period ranging from July 2002 to April 2015, we first compute a liquidity risk index for BBB bonds, which considers various liquidity risk facets based on principal component analysis. Second, we identify two liquidity regimes in our sample using a Markov switching regime model that highlights the dynamic characteristics of this risk and its behavior before, during and after the last financial crisis. We observe that the liquidity risk index improved after the financial crisis. It seems that the recent Volcker Rule did not affect the liquidity of BBB bonds during our sample period.
    Keywords: Liquidity risk; corporate bonds; financial crisis; regime change; Markov model; principal component analysis
    JEL: G01 G10 G18 G20 G21
    Date: 2018–05–10
  7. By: Piero Mazzarisi; Fabrizio Lillo; Stefano Marmi
    Abstract: We present an analytical model to study the role of expectation feedbacks and overlapping portfolios on systemic stability of financial systems. Building on [Corsi et al., 2016], we model a set of financial institutions having Value at Risk capital requirements and investing in a portfolio of risky assets, whose prices evolve stochastically in time and are endogenously driven by the trading decisions of financial institutions. Assuming that they use adaptive expectations of risk, we show that the evolution of the system is described by a slow-fast random dynamical system, which can be studied analytically in some regimes. The model shows how the risk expectations play a central role in determining the systemic stability of the financial system and how wrong risk expectations may create panic-induced reduction or over-optimistic expansion of balance sheets. Specifically, when investors are myopic in estimating the risk, the fixed point equilibrium of the system breaks into leverage cycles and financial variables display a bifurcation cascade eventually leading to chaos. We discuss the role of financial policy and the effects of some market frictions, as the cost of diversification and financial transaction taxes, in determining the stability of the system in the presence of adaptive expectations of risk.
    Date: 2018–05
  8. By: Bernd Kolkmann; Ingrid Janssen
    Abstract: Studies have shown that certain tenants are frequently excluded from the housing market given landlords’ measurement of financial eligibility using opaque risk management approaches. What is arguably needed is a scientific model that would allow landlords to build their decision on the dependent variable they are most interested in; that is, customer profit. This would follow in the footsteps of other industries that commonly use customer profitability analysis, such as hotels, financial services, and the private health care sector. Using the case study of the German housing market, this study will construct such a model that landlords can use to evaluate tenant profitability. Using a methodology based on customer profitability analysis, the research will deconstruct the key variables that make tenants financially profitable in the eyes of a residential landlord, and demonstrate their interaction. This paper argues why and how a profitability approach adds value for the landlord and explains the model based on an extensive literature review.
    Keywords: Customer profitability analysis; Housing; Tenant profitability; Tenant risk
    JEL: R3
    Date: 2017–07–01
  9. By: Gal Wettstein
    Abstract: A big challenge facing retirees is how to draw down their nest egg in retirement. The main consideration is insuring against “longevity risk” – the possibility of outliving one’s savings – without unduly restricting spending. One solution is to buy an annuity, which converts wealth into an income stream that is guaranteed until death. Common annuities include Social Security and traditional employer pensions. However, Social Security is not intended to be the sole source of retirement income and pensions in the private sector are rapidly disappearing, so buying an additional annuity with savings is often a good idea. Yet few people actually do. Many reasons exist for the lack of annuitization. These include the complexity of the product and the fear of giving up one’s wealth and then dying too soon to “break even.” A simpler reason is price, since annuity prices include a premium to protect the insurer selling the policy against longevity risk.1 Given the lack of interest in annuities, some policy experts have begun advocating an alternative form of longevity insurance – a “tontine” – which would require insurers to assume less risk and, in turn, charge lower premiums. Tontines, which do not currently exist in the marketplace, are the topic of this brief. The discussion proceeds as follows. The first section describes a basic tontine and how it differs from an annuity. The second section discusses the legal status of tontines. The third section explores the central tradeoff of a tontine: lower cost for less insurance. The fourth section describes a way to eliminate a potential downside of the payout pattern of tontines. The final section concludes that some of the enthusiasm for tontines is well placed but drawbacks also exist.
    Date: 2018–04
  10. By: Bryan Kelly; Seth Pruitt; Yinan Su
    Abstract: We propose a new modeling approach for the cross section of returns. Our method, Instrumented Principal Components Analysis (IPCA), allows for latent factors and time-varying loadings by introducing observable characteristics that instrument for the unobservable dynamic loadings. If the characteristics/expected return relationship is driven by compensation for exposure to latent risk factors, IPCA will identify the corresponding latent factors. If no such factors exist, IPCA infers that the characteristic effect is compensation without risk and allocates it to an "anomaly" intercept. Studying returns and characteristics at the stock-level, we find that four IPCA factors explain the cross section of average returns significantly more accurately than existing factor models and produce characteristic-associated anomaly intercepts that are small and statistically insignificant. Furthermore, among a large collection of characteristics explored in the literature, only eight are statistically significant in the IPCA specification and are responsible for nearly 100% of the model's accuracy.
    JEL: G1 G11 G12 G17
    Date: 2018–04
  11. By: Jeffrey S. Racine; Qi Li; Li Zheng
    Abstract: Model averaging has a rich history dating from its use for combining forecasts from time-series models (Bates & Granger 1969) and presents a compelling alternative to model selection methods. We propose a frequentist model average procedure defined over categorical regression splines (Ma, Racine & Yang 2015) that allows for non-nested and heteroskedastic candidate models. Theoretical underpinnings are provided, finite-sample performance is evaluated, and an empirical illustration reveals that the method is capable of outperforming a range of popular model selection criteria in applied settings. An R package is available for practitioners (Racine 2017).
    Date: 2018–05
  12. By: Suen, Richard M. H.
    Abstract: This paper analyzes the risk attitude and investment behavior of a group of heterogeneous consumers who face an undesirable background risk. It is shown that standard risk aversion at the individual level does not imply standard risk aversion at the group level under efficient risk sharing. This points to a potential divergence between individual and collective investment choices in the presence of background risk. We show that if the members' absolute risk tolerance is increasing and satisfies a strong form of concavity, then the group has standard risk aversion.
    Keywords: Standard risk aversion; Efficient risk sharing; Background risk; Portfolio choice.
    JEL: D70 D81 G11
    Date: 2018–03–29
  13. By: Tobias Berg; Valentin Burg; Ana Gombović; Manju Puri
    Abstract: We analyze the information content of the digital footprint – information that people leave online simply by accessing or registering on a website – for predicting consumer default. Using more than 250,000 observations, we show that even simple, easily accessible variables from the digital footprint equal or exceed the information content of credit bureau (FICO) scores. Furthermore, the discriminatory power for unscorable customers is very similar to that of scorable customers. Our results have potentially wide implications for financial intermediaries’ business models, for access to credit for the unbanked, and for the behavior of consumers, firms, and regulators in the digital sphere.
    JEL: D12 G20 O33
    Date: 2018–04
  14. By: Kazeem Isah (Centre for Econometric and Allied Research, University of Ibadan); Ibrahim D. Raheem (School of Economics, University of Kent, Canterbury, UK)
    Abstract: This paper is motivated by the news that the surge in cryptocurrencies is an important candidate to in explaining the plummeting stock markets. To validate this believe, we construct a predictive model in which cryptocurrencies are identified as the predictors of US stock returns. The inherent statistical properties of cryptocurrencies such as persistence, endogeneity, and conditional heteroscedasticity are being accounted for in the Westerlund and Narayan (2015) estimator. Three salient results emanated from our estimations. First, we validated the importance of cryptocurrencies in predicting US stock prices; second, the cryptocurrencies predictive model outperforms the conventional time-series models such as Autoregressive Integrated Moving Average (ARIMA) model and the Autoregressive Fractionally Integrated Moving Average (ARFIMA); third, our results are robust to different method of forecast performance evaluation measures and different sub-sample periods. These results have important policy implications for the investors and policymakers.
    Keywords: Stock Prices, Cryptocurrency, Digital Asset Prices, Predictive Model, Forecast Evaluation
    JEL: C52 C53 G11 G14 G17
    Date: 2018–05
  15. By: Demary, Markus; Voigtländer, Michael
    Abstract: Banks have changed their asset allocation. While the number of loans to non-financial corporations on their balance sheets is slowly growing after a period of deleveraging, banks' demand for Euro-area sovereign bonds is still accelerating. The high demand for safe and liquid assets is not only driven by risk aversion and liquidity preferences, it is also a side effect of financial regulation.
    Date: 2018
  16. By: Thomas Walther; Tony Klein; Hien Pham Thu;
    Abstract: Cryptocurrencies such as Bitcoin are establishing themselves as an investment asset and are often named the New Gold. This study, however, shows that the two assets could barely be more di?erent. Firstly, we analyze and compare conditional variance properties of Bitcoin and Gold as well as other assets and ?nd di?erences in their structure. Secondly, we implement a BEKK-GARCH model to estimate time-varying conditional correlations. Gold plays an important role in ?nancial markets with ?ight-to-quality in times of market distress. Our results show that Bitcoin behaves as the exact opposite and it positively correlates with downward markets. Lastly, we analyze the properties of Bitcoin as portfolio component and ?nd no evidence for hedging capabilities. We conclude that Bitcoin and Gold feature fundamentally di?erent properties as assets and linkages to equity markets. Our results hold for the broad cryptocurrency index CRIX. As of now, Bitcoin does not re?ect any distinctive properties of Gold other than asymmetric response in variance.
    Keywords: BEKK, Bitcoin, CRIX, Cryptocurrency, Gold, GARCH, Conditional Correlation, Asymmetry, Long memory
    JEL: C10 C58 G11
    Date: 2018–03
  17. By: Vitaly Orlov; ;
    Abstract: The paper shows that currency carry trades can be rationalized by the time-varying risk premia originating from the sovereign solvency risk. We find that solvency risk is a key determinant of risk premia in the cross section of carry trade returns, as its covariance with returns captures a substantial part of the cross-sectional vraiation of carry trade returns. Importantly, low interest rate currencies serve as insurance against solvency risk, while high interest rate currencies expose investors to more risk. The results are not attenuated by existing risks and pass a broad range of various robustness checks.
    Keywords: Solvency Risk, Carry Trades, Risk Premia
    JEL: F31 G15
    Date: 2018–02
  18. By: Frank Graef; Pascal Vogt; Volker Vonhoff; Florian Weigert
    Abstract: We investigate the determinants and performance implications of cash holdings for a large sample of actively-managed equity funds domiciled in the European Union (EU). In line with recent evidence from the US, we observe that cash holdings are strongly influenced by a fund's fee structure, past flows and flow volatility, and a fund's investment strategy. EU Funds with cash holdings in excess of the level predicted by fund attributes (i.e., high abnormal cash funds) outperform their low abnormal cash peers by risk-adjusted 0.96% per annum.
    Keywords: Cash holding, mutual funds, performance evaluation
    JEL: G10 G11 G15 G23
    Date: 2018–02

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