nep-rmg New Economics Papers
on Risk Management
Issue of 2016‒06‒04
fifteen papers chosen by
Stan Miles
Thompson Rivers University

  1. Vine-Copula Based Models for Farmland Portfolio Management By Feng, Xiaoguang; Hayes, Dermot
  2. Taming the Basel leverage cycle By Christoph Aymanns; Fabio Caccioli; J. Doyne Farmer; Vincent W.C. Tan
  3. Finance & Stochastic By Giandomenico, Rossano
  4. Firms’ risk endogenous to strategic management choices By Delis, Manthos D.; Hasan, Iftekhar; Tsionas, Efthymios G.
  5. Risk Measures At Risk- Are we missing the point? Discussions around sub-additivity and distortion By Dominique Guegan; Bertrand K. Hassani
  6. The Effect of Crop Insurance Premium Subsidies on Soybean Producers' Risk Management Portfolios By Hungerford, Ashley; Rosch, Stephanie
  7. Expected returns and idiosyncratic risk: Industry-level evidence from Russia By Kinnunen, Jyri; Martikainen, Minna
  8. Indicators used in setting the countercyclical capital buffer By Kalatie, Simo; Laakkonen, Helinä; Tölö, Eero
  9. Are Thai Equity Index Returns Sensitive to Interest and Exchange Rate Risks? By Jiranyakul, Komain
  10. Portfolio Optimization Problem with Non-identical Variances of Asset Returns using Statistical Mechanical Informatics By Takashi Shinzato
  11. The Ethanol Mandate and Downside Risk in Agriculture By Russell, Levi A.; Langemeier, Michael R.; Ibendahl, Gregory A.; Biermacher, Jon T.
  12. Strengthening City Disaster Risk Financing in Viet Nam By Asian Development Bank (ADB); Asian Development Bank (ADB); Asian Development Bank (ADB); Asian Development Bank (ADB)
  13. Bubble Economics How Big a Shock to China’s Real Estate Sector Will Throw the Country into Recession, and Why Does It Matter? By Michael, Bryane; Zhao, Simon
  15. How large banks use CDS to manage risks: bank-firm-level evidence By Hasan, Iftekhar; Wu, Deming

  1. By: Feng, Xiaoguang; Hayes, Dermot
    Abstract: U.S. farmland has achieved total returns of 10%-13% over the past decade with volatility of only 4%-5% (NCREIF Farmland Index). In addition, farmland returns have had low or negative correlation with traditional asset classes. These characteristics make farmland an attractive asset class for investors. Farmland, as a real asset, can also provide a hedge against inflation because farmland returns exhibit positive correlation with inflation. Over the past decade, annual U.S. farmland total return exceeds U.S. inflation rate by 3.55% (NCREIF Farmland Index and Consumer Price Index - Urban). With growing global demand for agricultural commodities and limited land to expand capacity, some investors expect that farmland will continue to generate superior returns for the foreseeable future. Efficient risk management and portfolio management are critical to create optimal risk/return profile for all investments. An essential issue in portfolio risk management is how marginal time series and the correlation structure of a large number of asset returns are treated. Most previous studies on farmland portfolio analysis were performed under the Capital Asset Pricing Model (CAPM) framework (Barry, 1980; Hennings, Sherrick, and Barry, 2005; Noland, Norvell, Paulson, and Schnitkey, 2011). The linear correlation assumption implied by the CAPM, however, is not adequate to capture complex correlation structure such as tail dependence and asymmetry that potentially exist among farmland asset returns. In addition, the normality assumption of the CAMP for asset returns has proven to be inappropriate in agriculture (Just and Weninger, 1999). Copula modeling is a suitable alternative. Margins and dependence can be separated by the copula function. The choice of marginal distribution is arbitrary and various copula types exhibiting flexible and complex correlation structures are available. Chen, Wilson, Larsen, and Dahl (2014) used the Gaussian copula to model joint distribution of agricultural asset returns to account for non-normal margins. However, the Gaussian copula can only capture symmetric correlation structure and allows no tail-dependence. Besides, the Gaussian copula, restrictions exist for most other multivariate copulas (Student’s t copula, Archimedean copulas, etc.). This inflexibility issue can be overcome by the pair-copula modeling proposed by Joe (1996). In particular, the regular vine (R-vines) representation of pair-wise copulas specifies arbitrary bivariate copulas as building blocks and hence can model any possible correlation structure. This study applies vine copulas to model farmland asset returns. We focus on annual state-level cropland returns for 30 major U.S. agricultural producing states. Average annual cropland returns on eight multi-state regions that the 30 states belong to and the average returns on the United States are included as well. This 39-dimensional data set covers the period spanning from 1998 to 2015. Following Brechmann and Czado (2013), ARMA-GARCH models with appropriate error distribution are fitted to each return. R-vine copulas are then used to model the correlation structure of standardized residuals obtained from the marginal GARCH models. Given the high dimensionality of the vine copula modeling, a Regular Vine Market Sector (RVMS) model (Brechmann and Czado, 2013) is applied to specify the R-vine structures and estimate the parameters. By grouping states by multi-state regions, this model mitigates the curse of dimensionality and facilitates interpretation of the correlation structure. The vine-copula based model used in this study loosens the restrictive normality and linearity assumptions under the classical CAPM framework, and allows for complex and flexible correlation structure such as tail-dependence. We compare this model to relevant benchmark models using the Gaussian and t copulas. The results show that the vine-copula based model provides a better a fit as indicated by modeling-fitting criteria. We show that, farmland portfolio management can benefit in terms of forecasting tail risk (Value-at-Risk) and constructing optimal portfolio more accurately for both passive and active portfolio management. We also use the vine-copula based model to identify and separate market, regional, and idiosyncratic risk for different risk measures. Our results show that the model provides an approach to precisely assessing and allocating risk of the farmland portfolio under the modern risk management framework. The vine-copula based model used in this study can serve as an initiative for more elaborate models for farmland portfolio management. One direction for future research would be to explore dynamic vine-copula structures to take into account the dynamics of correlations among farmland asset returns for forward-looking portfolio management. Another direction could be the consideration of estimation risk to account for the uncertainty of correlation parameters in the vine-copula model.
    Keywords: Copulas, Farmland Investment, Portfolio Management, Agribusiness, Agricultural Finance, Financial Economics, Risk and Uncertainty,
    Date: 2016
  2. By: Christoph Aymanns; Fabio Caccioli; J. Doyne Farmer; Vincent W.C. Tan
    Abstract: We investigate a simple dynamical model for the systemic risk caused by the use of Value-at-Risk, as mandated by Basel II. The model consists of a bank with a leverage target and an unleveraged fundamentalist investor subject to exogenous noise with clustered volatility. The parameter space has three regions: (i) a stable region, where the system has a fixed point equilibrium; (ii) a locally unstable region, characterized by cycles with chaotic behavior; and (iii) a globally unstable region. A calibration of parameters to data puts the model in region (ii). In this region there is a slowly building price bubble, resembling the period prior to the Global Financial Crisis, followed by a crash resembling the crisis, with a period of approximately 10-15 years. We dub this the Basel leverage cycle. To search for an optimal leverage control policy we propose a criterion based on the ability to minimize risk for a given average leverage. Our model allows us to vary from the procyclical policies of Basel II or III, in which leverage decreases when volatility increases, to countercyclical policies in which leverage increases when volatility increases. We find the best policy depends on the market impact of the bank. Basel II is optimal when the exogenous noise is high, the bank is small and leverage is low; in the opposite limit where the bank is large and leverage is high the optimal policy is closer to constant leverage. In the latter regime systemic risk can be dramatically decreased by lowering the leverage target adjustment speed of the banks. While our model does not show that the financial crisis and the period leading up to it were due to VaR risk management policies, it does suggest that it could have been caused by VaR risk management, and that the housing bubble may have just been the spark that triggered the crisis.
    Keywords: Financial stability; capital regulation; systemic risk
    JEL: G11 G20
    Date: 2016–03–03
  3. By: Giandomenico, Rossano
    Abstract: The study analyses quantitative models for financial markets by starting from geometric Brown process and Wiener process by analyzing Ito’s lemma and first passage model. Furthermore, it is analyzed the prices of the options, Vanilla & Exotic, by using the expected value and numerical model with geometric applications. From contingent claim approach ALM strategies are also analyzed so to get the effective duration measure of liabilities by assuming that clients buy options for protection and liquidity by assuming defaults protection barrier as well. Furthermore, the study analyses interest rate models by showing that the yields curve is given by the average of the expected short rates & variation of GDP with the liquidity risk, but in the case we have crisis it is possible to have risk premium as well, the study is based on simulated modelisation by using the drift condition in combination with the inflation models as expectation of the markets. Moreover, the CIR process is considered as well by getting with modification of the diffusion process the same result of the simulated modelisation but we have to consider that the CIR process is considered in the simulated environment as well. The credit risk model is considered as well in intensity model & structural model by getting the liquidity and risk premium and the PD probability from the Rating Matrix as well by using the diagonal. Furthermore, the systemic risk is considered as well by using a deco relation concept by copula approaches. Moreover, along the equilibrium condition between financial markets is achieved the equity pricing with implications for the portfolio construction in simulated environment with Bayesian applications for Smart Beta.. Finally, Value at Risk is also analyzed both static and dynamic with implications for the percentile of daily return and the tails risks by using a simulated approach.
    Keywords: Contingent Claim, Interest Rate Models, Credit Risk Model, Portfolio, VAR
    JEL: F37 F47 G22 G24
    Date: 2014–10
  4. By: Delis, Manthos D.; Hasan, Iftekhar; Tsionas, Efthymios G.
    Abstract: Use of variability of profits and other accounting-based ratios in order to estimate a firm's risk of insolvency is a well-established concept in management and economics. This paper argues that these measures fail to approximate the true level of risk accurately because managers consider other strategic choices and goals when making risky decisions. Instead, we propose an econometric model that incorporates current and past strategic choices to estimate risk from the profit function. Specifically, we extend the well-established multiplicative error model to allow for the endogeneity of the uncertainty component. We demonstrate the power of the model using a large sample of U.S. banks, and show that our estimates predict the accelerated bank risk that led to the subprime crisis in 2007. Our measure of risk also predicts the probability of bank default both in the period of the default, but also well in advance of this default and before conventional measures of bank risk.
    Keywords: risk, strategic management, endogenous, profit function
    Date: 2015–08–20
  5. By: Dominique Guegan (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique); Bertrand K. Hassani (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)
    Abstract: This paper discusses the regulatory requirements (Basel Committee, ECB-SSM andEBA) to measure the major risks of financial institutions, for instance Market, Credit and Operational, regarding the choice of the risk measures, the choice of the distributions used to model them and the level of confidence. We highlight and illustrate paradoxes and issues observed when implementing one approach over another, the inconsistencies between the methodologies suggested and the goals required to achieve them. We focus on the notion of sub-additivity and alternative risk measures, providing the supervisor with some recommendations and risk managers with some tools to assess and manage the risks in a financial institution.
    Keywords: Spectral measure,Distortion,Risk measures,Sub-additivity,Level of confidence,Distributions,Financial regulation
    Date: 2016–04
  6. By: Hungerford, Ashley; Rosch, Stephanie
    Abstract: We examine how reducing subsidies for federal crop insurance affects the risk management portfolios of US soybean producers. We apply the portfolio optimization approach of Das and Statman \citeyearpar{das2013options} to model how producers’ risk management portfolios change as subsidies for federal crop insurance premiums change, and examine how the changes to the risk management portfolios impact farmers’ on-farm income and exposure to downside risk. We optimize farmers’ risk management portfolio by adjusting the budget shares dedicated to each of four risk management tools: returns on production, forward contracting, savings, and crop insurance.
    Keywords: crop insurance, soybeans, risk management, agricultural finance, Agricultural and Food Policy, Agricultural Finance, Farm Management, Risk and Uncertainty, Q14, Q18,
    Date: 2016
  7. By: Kinnunen, Jyri; Martikainen, Minna
    Abstract: ​In this paper, we explore a relation between expected returns and idiosyncratic risk. As in many emerging markets, investors in the Russian stock market cannot fully diversify their portfolios due to transaction costs, information gathering and processing costs, and short-comings in investor protection. This implies that investors demand a premium for idiosyncratic risk – unique asset-specific risk plays a role in investment decisions. We estimate the price of idiosyncratic risk using MIDAS regressions and a cross-section of Russian industry portfolios. We find that idiosyncratic risk commands an economically and statistically significant risk premium. The results remain unaffected after controlling for global pricing factors and short-term return reversal.
    Keywords: idiosyncratic risk, industry risk, cross-sectional returns, MIDAS, Russia
    JEL: G12
    Date: 2015–10–30
  8. By: Kalatie, Simo; Laakkonen, Helinä; Tölö, Eero
    Abstract: According to EU legislation, the national authorities should use the principle of 'guided discretion' in setting the countercyclical capital buffer (CCB), which increases banks' resilience against systemic risk associated with periods of excessive credit growth. This means that the decision should be based on signals from a pre-determined set of early warning indicators, but that there should also be room for discretion, as there is always uncertainty associated with the use of early warning indicators. The European Systemic Risk Board (ESRB) recommends that the authorities use the deviation of the credit-to-GDP ratio from its long term trend value (credit-to-GDP gap) as the primary indicator in setting the CCB. In addition, designated authorities should use in their decision making indicators that measure private sector credit developments and debt burden, overvaluation of property prices, external imbalances, mispricing of risk, and strength of bank balance sheets. Based on an empirical analysis of data on EU countries and a large assortment of potential indicators, we propose a set of suitable early warning indicators for each of these categories.
    Keywords: countercyclical capital buffer, macroprudential policy, early warning indicators
    JEL: G01 G28
    Date: 2015–03–16
  9. By: Jiranyakul, Komain
    Abstract: This study examines the sensitivity of the Thai stock market to nominal and real interest rate, and exchange rate risks during January 2005 and December 2013 using quantile regression. The analysis focuses on sectoral level and one main index in the stock market. The empirical results show that the stock market is more sensitive to exchange rate risk than interest rate risk. However, the impacts of these risks are different across equity index returns. The results from this study give implication for risk management of portfolio mangers and investors.
    Keywords: Equity index returns, interest rate risk, exchange rate risk, quantile regression
    JEL: C21 G12 G32
    Date: 2016–05
  10. By: Takashi Shinzato
    Abstract: The portfolio optimization problem in which the variances of the return rates of assets are not identical is analyzed in this paper using the methodology of statistical mechanical informatics, specifically, replica analysis. We define two characteristic quantities of an optimal portfolio, namely, minimal investment risk and concentrated investment level, in order to solve the portfolio optimization problem and analytically determine their asymptotical behaviors using replica analysis. Moreover, numerical experiments were performed, and a comparison between the results of our simulation and those obtained via replica analysis validated our proposed method.
    Date: 2016–05
  11. By: Russell, Levi A.; Langemeier, Michael R.; Ibendahl, Gregory A.; Biermacher, Jon T.
    Keywords: ethanol, downside risk, risk, Agricultural and Food Policy, Risk and Uncertainty, Q18, G31,
    Date: 2016
  12. By: Asian Development Bank (ADB); Asian Development Bank (ADB) (Sustainable Development and Climate Change Department, ADB); Asian Development Bank (ADB) (Sustainable Development and Climate Change Department, ADB); Asian Development Bank (ADB)
    Abstract: Disaster risk financing instruments provide funding for disaster relief, early recovery, and reconstruction. Adequate financing arrangements are essential in ensuring timely recovery in the wake of disasters and in minimizing their impact on socioeconomic development. This paper presents a summary of a technical assistance project on the development of disaster risk financing solutions for the cities of Can Tho and Hue and, by extension, for other cities in Viet Nam. Many of Viet Nam’s cities face significant risk from natural hazards such as typhoons, flooding, landslide, and drought. The project included the development of disaster risk models, financing gap analysis, and review of legislative and regulatory considerations. Disaster risk financing solutions were identified, focusing on insurance, credit, and capital market instruments.
    Keywords: can tho, hue, viet nam, vietnam, disaster risk financing, insurance, natural hazard, typhoon, flood, disaster, reconstruction, japan fund for poverty reduction, jfpr
    Date: 2015–11
  13. By: Michael, Bryane; Zhao, Simon
    Abstract: How far do China’s property prices need to drop in order to send the country into a recession? What does this question tell us about the way Bubble Economies work? In this paper, we develop a theory of Bubble Economics – non-linear and often “systemic” (in the mathematical sense of the word) forces which cause significant misallocations of resources. Our theory draws on the standard elements of most stories of Bubble Economics, looking at the way banking, construction, savings/investment, local government and equities sectors interact. We find that Bubble Economies’ GDP growth can depend on property prices changes differently at different times -- depending on risks building up in the economy. We argue that a tacit, implicit Bubble Risk Factor might provide a way of understanding a key variable academics and practitioners omit when they try to explain how economies (mis)allocate resources during bubbles. A 15%-20% property price drop could cause recession, if China’s economy resembles other large economies having already experienced property-related asset crises. However, a 40% decline would not be out of the question.
    Keywords: China recession,bubble economics,fragility,housing bubble
    JEL: D58 N15 L85 G01
    Date: 2016
    Date: 2016
  15. By: Hasan, Iftekhar; Wu, Deming
    Abstract: ​We test five hypotheses on whether banks use CDS to hedge corporate loans, provide credit enhancements, obtain regulatory capital relief, and exploit banking relationship and private information. Linking large banks’ CDS positions and syndicated lending on individual firms, we observe strong evidence for the credit enhancement and regulatory capital relief hypotheses, but mixed evidence for the hedging, banking relationship, and private information hypotheses. Banks buy and sell more CDS on their borrowers, but their net CDS positions and lending status are largely unrelated. We find no evidence of bank using CDS to exploit private information.
    Keywords: hedging, credit enhancement, regulatory capital relief, banking relationship, private information
    JEL: G14 G21 G23 G28 G32
    Date: 2016–04–29

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