nep-rmg New Economics Papers
on Risk Management
Issue of 2014‒03‒22
twelve papers chosen by
Stan Miles
Thompson Rivers University

  1. Commodity Price Correlation and Time varying Hedge Ratios By Amine Lahiani; Khaled Guesmi
  2. Market Discipline at Thai Banks before the Asian Crisis By Jiranyakul, Komain; Opiela, Timothy
  3. A New Bootstrap Test for the Validity of a Set of Marginal Models for Multiple Dependent Time Series: an Application to Risk Analysis By David Ardia; Lukasz Gatarek; Lennart F. hoogerheide
  4. Outliers in multivariate Garch models By Aurea Grané; Belén Martín-Barragán; Helena Veiga
  5. bank capital regulation model By cho, hyejin
  6. Livestock Gross Margin-Dairy Insurance: An Assessment of Risk Management and Potential Supply Impacts By Mosheim, Roberto; Blaney, Don; Burdine, Kenny; Maynard, Leigh
  7. An unsupervised parallel genetic cluster algorithm for graphics processing units By Dieter Hendricks; Dariusz Cieslakiewicz; Diane Wilcox; Tim Gebbie
  8. Liquidity-adjusted Intraday Value at Risk modeling and Risk Management: an Application to Data from Deutsche Börse By Georges Dionne; Maria Pacurar; Xiaozhou Zhou
  9. Rating Agencies By Harold Cole; Thomas F. Cooley
  10. Co-movements between Germany and International Stock Markets: Some New Evidence from DCC-GARCH and Wavelet Approaches By Gazi Salah Uddin; Mohamed Arouri; Aviral Kumar Tiwari
  11. Optimal Use of Put Options in a Stock Portfolio By Peter N, Bell
  12. Banking Fragility in Colombia: An Empirical Analysis Based on Balance Sheets By Ignacio Lozano; Alexander Guarín

  1. By: Amine Lahiani; Khaled Guesmi
    Abstract: This paper examines the price volatility and hedging behavior of commodity futures indices and stock market indices. We investigate the weekly hedging strategies generated by return-based and range-based asymmetric dynamic conditional correlation (DCC) processes. The hedging performances of short and long hedgers are estimated with a semi-variance, low partial moment and conditional value-at-risk. The empirical results show that range-based DCC model outperforms return-based DCC model for most cases.
    Keywords: Range-based Dynamic Conditional Correlation; Downside Risk; Transaction Costs
    Date: 2014–02–25
  2. By: Jiranyakul, Komain; Opiela, Timothy
    Abstract: This paper tests the effect of systemic risk on deposit market discipline by interacting proxies for systemic risk with bank-specific default-risk variables. Discipline is measured by estimating a supply of deposit funds function at Thai banks from 1992 to 1997. The results show that supply decreases as bank-specific risk increases. Also, the sensitivity of funds to changes in bank-specific risk increases as systemic risk rises. Additionally, depositors decrease their sensitivity to deposit rates, decreasing the ability of banks to offset deposit drains by raising rates. Although banking system risk increases, discipline decreases the share of deposits at the riskiest banks.
    Keywords: Market discipline, market monitoring, systemic risk, banking and currency crises
    JEL: E44 G21
    Date: 2014–03
  3. By: David Ardia; Lukasz Gatarek; Lennart F. hoogerheide
    Abstract: A novel simulation-based methodology is proposed to test the validity of a set of marginal time series models, where the dependence structure between the time series is taken ‘directly’ from the observed data. The procedure is useful when one wants to summarize the test results for several time series in one joint test statistic and p-value. The proposed test method can have higher power than a test for a univariate time series, especially for short time series. Therefore our test for multiple time series is particularly useful if one wants to assess Value-at-Risk (or Expected Shortfall) predictions over a small time frame (e.g., a crisis period). We apply our method to test GARCH model specifications for a large panel data set of stock returns.
    Keywords: Bootstrap test, GARCH, Marginal models,Multiple time series, Value-at-Risk
    JEL: C1 C12 C22 C44
    Date: 2014
  4. By: Aurea Grané; Belén Martín-Barragán; Helena Veiga
    Abstract: Outliers of moderate magnitude cause large changes in financial time series of prices andreturns and affect both the estimation of parameters and volatilities when fitting a GARCH-typemodel. The multivariate setting is still to be studied, but similar biases and impacts oncorrelation dynamics are believed to exist. The accurate estimation of the correlation structure iscrucial in many applications, such as portfolio allocation and risk management. This paperfocuses on these issues by studding the impact of additive outliers (isolated and patches of leveloutliers and volatility outliers) on the estimation of correlations when fitting well knownmultivariate GARCH models and by proposing a general detection algorithm based on waveletsthat can be applied to a large class of multivariate volatility models. This procedure can be alsointerpreted as a model miss-specification test since it is based on residual diagnostics. Theeffectiveness of the new proposal is evaluated by an intensive Monte Carlo study before it isapplied to daily stock market indices. The simulation studies show that correlations are highlyaffected by the presence of outliers and that the new method is both effective and reliable, sinceit detects very few false outliers.
    Keywords: Additive Outliers, Correlations, Volatilities, Wavelets
    JEL: C10 C13 C53 C58 G17
    Date: 2014–02
  5. By: cho, hyejin
    Abstract: The motivation of this article is to induce the bank capital management solution for banks and regulation bodies on commercial bank. The goal of the paper is intended to mitigate the risk of banking area and also provide the right incentive for banks to support the real economy.
    Keywords: Demand Deposit, Risks of on-the-balance-sheet and off-the-balance sheet, Portfolio composition, minimum equity capital regulation.
    JEL: G00
    Date: 2014–03–12
  6. By: Mosheim, Roberto; Blaney, Don; Burdine, Kenny; Maynard, Leigh
    Abstract: Public risk management policies for dairy producers have the potential to induce expansion in milk supplies, which might lower farm-level prices and offset risk-reduction benefits. An evaluation of USDA’s Livestock Gross Margin-Dairy (LGM-Dairy) insurance program finds economic downside risk significantly reduced, with potential to induce modest supply expansion (0 to 3 percent) if widely adopted. Supply impacts are likely limited due to relatively low participation levels and a minimal (“inelastic”) supply response to risk. LGM-Dairy is more flexible and convenient than other risk management tools, such as hedging directly in futures or options markets, especially for small farms.
    Keywords: dairy, gross margins, risk management, LGM-Dairy, insurance, milk supplies, livestock, Agricultural and Food Policy, Livestock Production/Industries,
    Date: 2014–03
  7. By: Dieter Hendricks; Dariusz Cieslakiewicz; Diane Wilcox; Tim Gebbie
    Abstract: During times of stock market turbulence, monitoring the intraday clustering behaviour of financial instruments allows one to better understand market characteristics and systemic risks. While genetic algorithms provide a versatile methodology for identifying such clusters, serial implementations are computationally intensive and can take a long time to converge to the global optimum. We implement a Master-Slave parallel genetic algorithm (PGA) with a Marsili and Giada log-likelihood fitness function to identify clusters within stock correlation matrices. We utilise the Nvidia Compute Unified Device Architecture (CUDA) programming model to implement a PGA and visualise the results using minimal spanning trees (MSTs). We demonstrate that the CUDA PGA implementation runs significantly faster than the test case implementation of a comparable serial genetic algorithm. This, combined with fast online intraday correlation matrix estimation from high frequency data for cluster identification, may enhance near-real-time risk assessment for financial practitioners.
    Date: 2014–03
  8. By: Georges Dionne; Maria Pacurar; Xiaozhou Zhou
    Abstract: This paper develops a high-frequency risk measure, the Liquidity-adjusted Intraday Value at Risk (LIVaR). Our objective is to explicitly consider the endogenous liquidity dimension associated with order size. Taking liquidity into consideration when using intraday data is important because significant position changes over very short horizons may have large impacts on stock returns. By reconstructing the open Limit Order Book (LOB) of Deutsche Börse, the changes of tick-by-tick ex-ante frictionless return and actual return are modeled jointly using a Log-ACD-VARMA-MGARCH structure. This modeling helps to identify the dynamics of frictionless and actual returns, and to quantify the risk related to the liquidity premium. From a practical perspective, our model can be used not only to identify the impact of ex-ante liquidity risk on total risk, but also to provide an estimation of VaR for the actual return at a point in time. In particular, there will be considerable time saved in constructing the risk measure for the waiting cost because once the models have been identified and estimated, the risk measure over any time horizon can be obtained by simulation without re-sampling the data and re-estimating the model.
    Keywords: Liquidity-adjusted Intraday Value at Risk, Tick-by-tick data, Log-ACD-VARMA-MGARCH, Ex-ante Liquidity premium, Limit Order Book
    JEL: C22 C41 C53 G11
    Date: 2014
  9. By: Harold Cole; Thomas F. Cooley
    Abstract: For decades credit rating agencies were viewed as trusted arbiters of creditworthiness and their ratings as important tools for managing risk. The common narrative is that the value of ratings was compromised by the evolution of the industry to a form where issuers pay for ratings. In this paper we show how credit ratings have value in equilibrium and how reputation insures that, in equilibrium, ratings will reflect sound assessments of credit worthiness. There will always be an information distortion because of the fact that purchasers of ratings need not reveal them. We argue that regulatory reliance on ratings and the increasing importance of risk-weighted capital in prudential regulation have more likely contributed to distorted ratings than the matter of who pays for them. In this respect, much of the regulatory obsession with the conflict created by issuers paying for ratings is a distraction.
    JEL: G1 G24
    Date: 2014–03
  10. By: Gazi Salah Uddin; Mohamed Arouri; Aviral Kumar Tiwari
    Abstract: The analysis of co-movements of stock market returns is a fundamental issue in finance. The aim of this paper is to examine the co-movement between Germany and major International Stock Markets in the time–frequency space. Our sample period goes from 01 June 1992 to 26 March 2013 and includes the financial crisis that erupted in US financial institutions in the summer of 2007 and spread beyond the US to other developed economies in the first half of 2008. We use DCC-GARCH and wavelet-based measures of co-movements which make it possible to find a balance between the time and frequency domain features of the data. The results suggest that the difference in the co-movement dynamics could be the result of the different natures of the financial crises or a change in regime. The finding of this paper has relevant policy implications in asset allocation and risk management in designing international portfolios for investment decisions.
    Keywords: DCC-GARCH; Co-movement; Wavelet coherence; Germany
    JEL: G15 C40 F30
    Date: 2014–02–25
  11. By: Peter N, Bell
    Abstract: In this paper I consider a portfolio optimization problem where an agent holds an endowment of stock and is allowed to buy some quantity of a put option on the stock. This basic question (how much insurance to buy?) has been addressed in insurance economics through the literature on rational insurance purchasing. However, in contrast to the rational purchasing literature that uses exact algebraic analysis with a binomial probability model of portfolio value, I use numerical techniques to explore this problem. Numerical techniques allow me to approximate continuous probability distributions for key variables. Using large sample, asymptotic analysis I identify the optimal quantity of put options for three types of preferences over the distribution of portfolio value. The location of the optimal quantity varies across preferences and provides examples of important concepts from the rational purchasing literature: coinsurance for log utility (q* 1). I calculate the shape of the objective function and show the optimum is well defined for mean-variance utility and quantile-based preferences in an asymptotic setting. Using resampling, I show the optimal values are stable for the mean-variance utility and the quantile-based preferences but not the log utility. For the optimal value with mean-variance utility I show that the put option affects the probability distribution of portfolio value in an asymmetric way, which confirms that it is important to analyze the optimal use of derivatives in a continuous setting with numerical techniques.
    Keywords: Portfolio; optimization; financial derivative; put option; quantity; expected utility; numerical analysis
    JEL: C02 C15 C63 G11 G22
    Date: 2014–03–13
  12. By: Ignacio Lozano; Alexander Guarín
    Abstract: In this paper, we study the empirical relationship between credit funding sources and the financial vulnerability of the Colombian banking system. We propose a statistical model to measure and predict banking-fragility episodes associated with credit funding sources classified into retail deposits and wholesale funds. We compute the probability of financial fragility for both the aggregated banking system and the individual banks. Our approach performs a Bayesian averaging of estimated logit regression models with monthly balance sheet data between 1996 and 2013. The results show the increasing use of wholesale funding to support credit expansion is a potential source of financial fragility. Therefore, monitoring credit funding sources could provide an additional tool to warn against banking disruptions. Classification JEL: C11, C23, C52, C53, G01, G20, G21
    Date: 2014–03

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