nep-rmg New Economics Papers
on Risk Management
Issue of 2018‒10‒22
thirteen papers chosen by
Stan Miles
Thompson Rivers University

  1. Econometric Modeling of Risk Measures: A Selective Review of the Recent Literature By Dingshi Tian; Zongwu Cai; Ying Fang
  2. Replicating Expected Commercial Real Estate (CRE) Risk and Returns Using Liquid Market Instruments and CRE Market-Related Investment Risk By Emilian Belev; Richard Gold
  3. Firm's Protection against Disasters: Are Investment and Insurance Substitutes or Complements? By Giuseppe Attanasi; Laura Concina; Caroline Kamate; Valentina Rotondi
  4. A framework for early-warning modeling with an application to banks By Lang, Jan Hannes; Peltonen, Tuomas A.; Sarlin, Peter
  5. Complex Valued Risk Diversification By Yusuke Uchiyama; Takanori Kadoya; Kei Nakagawa
  6. Challenges in approximating the Black and Scholes call formula with hyperbolic tangents By Michele Mininni; Giuseppe Orlando; Giovanni Taglialatela
  7. Unemployment Risk By Michael T. Kiley
  8. Trending Mixture Copula Models with Copula Selection By Bingduo Yang; Zongwu Cai; Christian M. Hafner; Guannan Liu
  9. Modelling Competitive Mortgage Termination Option Strategies: Default vs Restructuring and Prepayment vs Defeasance By Lok Man Michel Tong; Gianluca Marcato
  10. The Differential Impact of Bank Size on Systemic Risk By Amy Lorenc; Jeffery Y. Zhang
  11. Operating and financial leverage as risk measures in agricultural companies By Zabolotnyy, Serihiy; Wasilewski, Mirosław
  12. Real Estate Risk Factors and Portfolio Allocation By Jean-Christophe Delfim; Martin Hoesli
  13. Risk preference dynamics around life events By Kettlewell, Nathan

  1. By: Dingshi Tian (The Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen, China); Zongwu Cai (Department of Economics, The University of Kansas); Ying Fang (The Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen, China)
    Abstract: Since the financial crisis in 2008, the risk measures which are the core of risk management, have received increasing attention among economists and practitioners. In this review, the concentrate is on recent developments in the estimation of the most popular risk measures, namely, value at risk (VaR), expected shortfall (ES), and expectile. After introducing the concept of risk measures, the focus is on discussion and comparison of their econometric modeling. Then, parametric and nonparametric estimations of tail dependence are investigated. Finally, we conclude with insights into future research directions.
    Keywords: Expectile; Expected Shortfall; Network; Nonparametric Estimation; Tail Dependence; Value at Risk.
    JEL: C58 C14
    Date: 2018–10
    URL: http://d.repec.org/n?u=RePEc:kan:wpaper:201807&r=rmg
  2. By: Emilian Belev; Richard Gold
    Abstract: The purpose of this paper is twofold. First, we estimate forward looking risk and return characteristics of a theoretical commercial real estate portfolio employing real world hedonics with the goal of seamlessly integrating the asset class into a total portfolio risk management system. Because a factor model is at the core of the model’s analytics, the model is additive and we are able to calculate estimates at both the property and portfolio-levels. Second, we create liquid instrument portfolios that mimic the portfolio’s performance in order to hedge the portfolio’s risk or simply to gain exposure in the form of direct or collateralized investments in instruments such as stock and bonds whose characteristics would otherwise be unknown if investors were to rely solely on appraisals or index-based risk models. The paper hopes to show, not only what drives real estate risk and return, but also ask the fundamental question about ownership. If liquid synthetic portfolios can be efficiently built with a desired set of risk and/or return characteristics, why own the bricks and mortar? That is the fundamental question that all investors need to both ask and answer
    Keywords: hedge; Portfolio; Return; Risk; Synthetic
    JEL: R3
    Date: 2018–01–01
    URL: http://d.repec.org/n?u=RePEc:arz:wpaper:eres2018_13&r=rmg
  3. By: Giuseppe Attanasi (Université Côte d'Azur, CNRS, GREDEG, France); Laura Concina (FONCSI, Toulouse); Caroline Kamate (FONCSI, Toulouse); Valentina Rotondi (Bocconi University, Milan)
    Abstract: We use a controlled laboratory experiment to study firm's and insurer's behavior when the firm can protect itself against potential technological damages. The probability of a catastrophic event is objective, and the firm's costly investment in safety reduces it. The firm can also buy an insurance with full or partial refund against the consequences of the catastrophic event, which ultimately reduces the variance of the firm's investment-in-safety lottery. In the insurer-firm game, first the insurer decides which contract to propose to the firm, then the firm simultaneously decides whether or not to buy this contract and whether or not to invest in the reduction of the probability of the catastrophic events. We parametrize the insurer-firm game such that: (i) a risk-neutral insurer maximizes his expected profit by o↵ering an actuarially fair contract with full insurance; (ii) a risk-neutral firm is indi↵erent between investing in safety and accepting a fair insurance contract. We aim at understanding whether investment in safety and insurance are substitutes or complements in the firm's risk management of catastrophic events. In line with our predictions, the experimental results suggest that they are substitutes rather than complements: the firm's investment in safety measures is a↵ected by the insurer's proposed contract, the latter usually involving only partial insurance.
    Keywords: Decision under risk, Losses, Small probabilities, Probability reduction, Technological disasters, Insurance, Deductible
    JEL: D81 G22 K32 Q58
    Date: 2018
    URL: http://d.repec.org/n?u=RePEc:gre:wpaper:2018-24&r=rmg
  4. By: Lang, Jan Hannes; Peltonen, Tuomas A.; Sarlin, Peter
    Abstract: This paper proposes a framework for deriving early-warning models with optimal out-of-sample forecasting properties and applies it to predicting distress in European banks. The main contributions of the paper are threefold. First, the paper introduces a conceptual framework to guide the process of building early-warning models, which highlights and structures the numerous complex choices that the modeler needs to make. Second, the paper proposes a flexible modeling solution to the conceptual framework that supports model selection in real-time. Specifically, our proposed solution is to combine the loss function approach to evaluate early-warning models with regularized logistic regression and cross-validation to find a model specification with optimal real-time out-of-sample forecasting properties. Third, the paper illustrates how the modeling framework can be used in analysis supporting both microand macro-prudential policy by applying it to a large dataset of EU banks and showing some examples of early-warning model visualizations. JEL Classification: G01, G17, G21, G33, C52, C54
    Keywords: bank distress, early-warning models, financial crises, micro- and macro-prudential analysis, regularization
    Date: 2018–10
    URL: http://d.repec.org/n?u=RePEc:ecb:ecbwps:20182182&r=rmg
  5. By: Yusuke Uchiyama; Takanori Kadoya; Kei Nakagawa
    Abstract: Risk diversification is one of the dominant concerns for portfolio managers. Various portfolio constructions have been proposed to minimize the risk of the portfolio under some constrains including expected returns. We propose a portfolio construction method that incorporates the complex valued principal component analysis into the risk diversification portfolio construction. The proposed method is verified to outperform the conventional risk parity and risk diversification portfolio constructions.
    Date: 2018–10
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1810.04370&r=rmg
  6. By: Michele Mininni; Giuseppe Orlando; Giovanni Taglialatela
    Abstract: In this paper we introduce the concept of standardized call function and we obtain a new approximating formula for the Black and Scholes call function through the hyperbolic tangent. This formula is useful for pricing and risk management as well as for extracting the implied volatility from quoted options. The latter is of particular importance since it indicates the risk of the underlying and it is the main component of the option's price. Further we estimate numerically the approximating error of the suggested solution and, by comparing our results in computing the implied volatility with the most common methods available in literature we discuss the challenges of this approach.
    Date: 2018–09
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1810.04623&r=rmg
  7. By: Michael T. Kiley
    Abstract: Fluctuations in upside risks to unemployment over the medium term are examined using quantile regressions. U.S. experience reveals an elevated risk of large increases in unemployment when inflation or credit growth is high and when the unemployment rate is low. Inflation was a significant contributor to unemployment risk in the 1970s and early 1980s, and fluctuations in credit have contributed importantly to unemployment risk since the 1980s. Fluctuations in upside risk to unemployment are larger than fluctuations in the median outlook or downside risk to unemployment. Accounting for inflation and the state of the business cycle is important for understanding the role of financial conditions in shaping unemployment risk. The analysis suggests that fluctuations in near-term risks to unemployment decreased after 1984 because inflation stabilized, but fluctuations in medium-term risks increased owing to the large swings in credit in recent decades.
    Keywords: Credit ; GDP at risk ; Risk management
    JEL: E32 E24 E66
    Date: 2018–09–28
    URL: http://d.repec.org/n?u=RePEc:fip:fedgfe:2018-67&r=rmg
  8. By: Bingduo Yang (Lingnan (University) College, Sun Yat-sen University, Guangzhou, China); Zongwu Cai (Department of Economics, The University of Kansas); Christian M. Hafner (Institut de statistique and CORE, Universitie Catholique de Louvain, Louvain-la-Neuve, Belgium.); Guannan Liu (The Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen, China)
    Abstract: Modeling the joint tails of multiple nancial time series has important implications for risk management. Classical models for dependence often encounter a lack of fit in the joint tails, calling for additional flexibility. In this paper we introduce a new nonparametric time-varying mixture copula model, in which both weights and dependence parameters are deterministic functions of time. We propose penalized trending mixture copula models with group smoothly clipped absolute deviation (SCAD) penalty functions to do the estimation and copula selection simultaneously. Monte Carlo simulation results suggest that the shrinkage estimation procedure performs well in selecting and estimating both constant and trending mixture copula models. Using the proposed model and method, we analyze the evolution of the dependence among four international stock markets, and find substantial changes in the levels and patterns of the dependence, in particular around crisis periods.
    Keywords: Copula, Time-Varying Copula, Mixture Copula, Copula Selection
    JEL: C31 C32 C51
    Date: 2018–09
    URL: http://d.repec.org/n?u=RePEc:kan:wpaper:201809&r=rmg
  9. By: Lok Man Michel Tong; Gianluca Marcato
    Abstract: We build a two-stage competing risk model for pricing four types of early Termination options written on commercial mortgages: default vs restructuring and prepayment vs defeasance as two pairs of competitions. It is the first study to consider restructuring as a “competitor” with default. The key feature of our model is to introduce collateral underlying property market supply constraints into a property Price process which would determine values of early termination options. Our simulations find out greater probability to restructure mortgages by reducing interest and extending maturity and to prepay in cash. We also prove that tightening property supply constraints pushes up values of default, restructuring and prepayment by pricing their analogous options: default (a series of compound European Call on Put options), mortgage restructuring (an exchange option between mortgages with different cash flow structures), prepayment in cash (a series of compound European Call on Call options),and defeasance (an exchange option of more liquid assets with less liquid ones)in different scenarios. Therefore, we suggest controlling property supply constraints as an alternative risk management measure for mortgage markets.
    Keywords: Defeasance; Mortgage Default; Prepayment; Property Supply Constraints; Restructuring
    JEL: R3
    Date: 2018–01–01
    URL: http://d.repec.org/n?u=RePEc:arz:wpaper:eres2018_300&r=rmg
  10. By: Amy Lorenc; Jeffery Y. Zhang
    Abstract: We examine whether financial stress at larger banks has a different impact on the real economy than financial stress at smaller banks. Our empirical results show that stress experienced by banks in the top 1 percent of the size distribution leads to a statistically significant and negative impact on the real economy. This impact increases with the size of the bank. The negative impact on quarterly real GDP growth caused by stress at banks in the top 0.15 percent of the size distribution is more than twice as large as the impact caused by stress at banks in the top 0.75 percent, and more than three times as large as the impact caused by stress at banks in the top 1 percent. These results are broadly informative as to how the stringency of regulatory standards should vary with bank size, and support the idea that the largest banks should be subject to the most stringent requirements while smaller banks should be subject to successively less stringent requirements.
    Keywords: Bank failures ; Bank size ; Financial regulation ; Systemic risk ; Tailoring
    JEL: G21 G28
    Date: 2018–09–28
    URL: http://d.repec.org/n?u=RePEc:fip:fedgfe:2018-66&r=rmg
  11. By: Zabolotnyy, Serihiy; Wasilewski, Mirosław
    Abstract: The goal of the research is to estimate the level of risk of agricultural companies according to degree of operating and financial leverage, and to define relations between these measures and ratios of financial efficiency. The research involved companies from the database of the Institute of Agricultural and Food Economics – National Research Institute in 2005-2013. The greatest impact on risk of agricultural companies had the degree of operating leverage characterizing sensitivity of operating profit on volatility of operating revenue, regarding to cost structure. The degree of financial leverage showing the level of debt and interest paid influenced the risk of agricultural companies to a lesser extent. Agricultural companies with a high degree of total leverage had lower financial efficiency, arising from a low ability to generate operating profit.
    Keywords: Agricultural Finance, Research Methods/ Statistical Methods, Risk and Uncertainty
    Date: 2018
    URL: http://d.repec.org/n?u=RePEc:ags:iafepa:276377&r=rmg
  12. By: Jean-Christophe Delfim; Martin Hoesli
    Abstract: This research focuses on macroeconomic risk factors pertaining to the various types of real estate exposure (direct, listed, and non-listed) and how the resulting return predictability can be used in a mixed-asset portfolio framework. Comparing sensitivities to risk factors is important to assess whether indirect (listed and non-listed) exposures react in the same way as direct investments to the macroeconomy and how well such investments replicate direct real estate behavior. The various types of real estate exposure generally respond similarly to risk factors: GDP, money supply, construction costs, expected inflation, and expected economic activity positively impact returns, while the term and credit spreads, unemployment, and unexpected inflation negatively affect returns. We then rely on the identified risk factors to predict the expected returns and volatility of real estate, stocks, and bonds. These forecasts are used to build mixed-asset portfolios for various investment horizons. The benefits of including real estate in a portfolio and the possible substitutability between the three types of exposure are analyzed. The empirical analyses are conducted using U.S. data spanning over 30 years.
    Keywords: Investment horizon; Macroeconomy; Mixed-asset allocation; Real estate risk factors; Return predictability
    JEL: R3
    Date: 2018–01–01
    URL: http://d.repec.org/n?u=RePEc:arz:wpaper:eres2018_124&r=rmg
  13. By: Kettlewell, Nathan
    Abstract: Using a panel of Australians I estimate the dynamic relationship between common life events and risk preferences. Changes in financial circumstances, parenthood and family loss predict changes in risk preferences. Importantly the effects are largest closer to the event date and disappear over time. This supports a model of preference information where risk preferences are (trend) stable but fluctuations are at least partly deterministic. The linkages between life events and risk preferences are explored. There is little evidence that changes in consumption, state dependence, or changes in mental health and mood explain the results. However, emotional stability is an influential moderator suggesting that emotions play an important role.
    Keywords: risk preferences; life events; dynamics; fixed effects ordered logit
    Date: 2018–07
    URL: http://d.repec.org/n?u=RePEc:syd:wpaper:2018-07&r=rmg

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