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on Risk Management |
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Issue of 2014‒03‒22
twelve papers chosen by |
| 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 |
| URL: | http://d.repec.org/n?u=RePEc:ipg:wpaper:2014-142&r=rmg |
| 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 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:54492&r=rmg |
| 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 |
| URL: | http://d.repec.org/n?u=RePEc:lvl:lacicr:1413&r=rmg |
| 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 |
| URL: | http://d.repec.org/n?u=RePEc:cte:wsrepe:ws140503&r=rmg |
| 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 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:54365&r=rmg |
| 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 |
| URL: | http://d.repec.org/n?u=RePEc:ags:uersrr:164606&r=rmg |
| 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 |
| URL: | http://d.repec.org/n?u=RePEc:lvl:lacicr:1414&r=rmg |
| By: | Giuseppe arbia |
| Abstract: | This article proposes a new method for the estimation of the parameters of a simple linear regression model which accounts for the role of co-moments in non-Gaussian distributions being based on the minimization of a quartic loss function. Although the proposed method is very general, we examine its application to finance. In fact, in this field the contribution of the co-moments in explaining the return-generating process is of paramount importance when evaluating the systematic risk of an asset within the framework of the Capital Asset Pricing Model (CAPM). The suggested new method contributes to this literature by showing that, in the presence of non-normality, the regression slope can be expressed as a function of the co-kurtosis between the returns of a risky asset and the market proxy. The paper provides an illustration of the method based on some empirical financial data referring to 40 industrial sector assets rates of the Italian stock market. |
| Date: | 2014–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1403.4171&r=rmg |
| 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 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:19972&r=rmg |
| By: | Robert E. Marks (School of Economics, Australian School of Business, the University of New South Wales) |
| Abstract: | The purpose of this research is to search for the best (highest performing) risk profile of agents who successively choose among risky prospects. An agent’s risk profile is his attitude to perceived risk, which can vary from risk preferring to risk neutral (an expected-value decision maker) to risk averse. We use the Genetic Algorithm to search in the complex stochastic space of repeated lotteries. We find that agents with a CARA utility function learn to possess risk-neutral risk profiles. Since CARA utility functions are wealth-independent, this is not surprising. When agents have wealth-dependent, CRRA utility functions, however, they also learn to possess risk profiles that are about risk neutral (from slightly risk-averse to even slightly risk-preferring), which is surprising. |
| Keywords: | risk profile, decision-making under uncertainty, simulation |
| JEL: | D81 |
| Date: | 2014–01 |
| URL: | http://d.repec.org/n?u=RePEc:swe:wpaper:2014-10&r=rmg |
| 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 |
| URL: | http://d.repec.org/n?u=RePEc:ipg:wpaper:2014-143&r=rmg |
| 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 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:54394&r=rmg |