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on Risk Management |
| By: | CHOLLETE, Loran (Norwegian School of Economics and Business Administration (NHH)); HEINEN, Andréas (Universidad Carlos III de Madrid); VALDESOGO, Alfonso (Université catholique de Louvain (UCL). Center for Operations Research and Econometrics (CORE)) |
| Abstract: | In order to capture observed asymmetric dependence in international financial returns, we construct a multivariate regime-switching model of copulas. We model dependence with one Gaussian and one canonical vine copula regime. Canonical vines are constructed from bivariate conditional copulas and provide a very flexible way of characterizing dependence in multivariate settings. We apply the model to returns from the G5 and Latin American regions, and document two main findings. First, we discover that models with canonical vines generally dominate alternative dependence structures. Second, the choice of copula is important for risk management, because it modifies the Value at Risk (VaR) of international portfolio returns. |
| Keywords: | asymmetric dependence, canonical vine copula, international returns, regime-switching, risk management, Value-at-Risk. |
| JEL: | C32 C35 G10 |
| Date: | 2008–03 |
| URL: | http://d.repec.org/n?u=RePEc:cor:louvco:2008013&r=rmg |
| By: | Marie Brière (Centre Emile Bernheim, Solvay Business School, Université Libre de Bruxelles, Brussel and Credit Agricole Asset Management SGR, Paris.); Alexandre Burgues (Credit Agricole Asset Management SGR, Paris.); Ombretta Signori (Credit Agricole Asset Management SGR, Paris.) |
| Abstract: | This paper examines the advantages of incorporating equity volatility exposure into a global balanced portfolio. We consider two sets of strategies: long implied volatility and long volatility risk premium strategies. To calibrate and assess the risk/return profile of the portfolio, we present an analytical framework, offering pragmatic solutions for long-term investors seeking exposure to volatility. The benefit of volatility exposure for a conventional portfolio is shown through a mean / Value-at-Risk portfolio optimization. Pure volatility investment makes it possible to partially hedge downside equity risk, thus reducing the risk profile of the portfolio. Investing in the volatility risk premium substantially increases returns for a given level of risk. A well calibrated combination of the two strategies allows for enhanced absolute and risk-adjusted returns for the portfolio. |
| Keywords: | variance swap, volatility risk premium, higher moments, portfolio choice, Value at Risk |
| JEL: | G11 G12 G13 |
| Date: | 2008–11 |
| URL: | http://d.repec.org/n?u=RePEc:sol:wpaper:08-034&r=rmg |
| By: | Brajesh Kumar, Singh Priyanka |
| Abstract: | This paper is based on an empirical study of volatility, risk premium and seasonality in risk-return relation of the Indian stock and commodity markets. This investigation is conducted by means of the General Autoregressive Conditional Heteroscedasticity in the mean model (GARCH-in-Mean) introduced by Engle et al. (1987). A systematic approach to model volatility in returns is presented. Volatility clustering and asymmetric nature is examined for Indian stock and commodity markets. The risk-return relationship and seasonality in risk-return are also investigated through GARCH-in-Mean modeling in which seasonal dummies are used for return as well as volatility equation. The empirical work has been carried out on market index S&P CNX Nifty for a period of 18 years from January 1990 to December 2007. Gold prices from 22nd July 2005 to 20th February 2008 and Soybean from October 2004 – December 2007 are also considered. The stock and commodity markets returns show persistence as well as clustering and asymmetric properties. Risk-return relationship is positive though insignificant for Nifty and Soybean where as significant positive relationship is found in the case of Gold. Seasonality in risk and return is also found which suggests the asymmetric nature of return, i.e. negative correlation between return and its volatility. |
| Date: | 2008–04–29 |
| URL: | http://d.repec.org/n?u=RePEc:iim:iimawp:2008-04-04&r=rmg |
| By: | Diana Barro (Department of Applied Mathematics, University of Venice); Antonella Basso (Department of Applied Mathematics, University of Venice) |
| Abstract: | This contribution presents a network of interdependent firms in which the spatial diffusion of the business relations is described by an entropy spatial interaction model. This network is used in a credit risk model in order to take into account the counterparty risk and describe the resulting contagion effects. |
| Keywords: | credit risk contagion, networks, counterparty risk, entropy spatial models |
| JEL: | D61 C63 |
| Date: | 2008–11 |
| URL: | http://d.repec.org/n?u=RePEc:vnm:wpaper:171&r=rmg |
| By: | Sipos, Gabriela Lucia; Ciurea, Jeanina Biliana |
| Abstract: | Starting an innovation project assumes to state some competitive objectives referring to the allocated budget, time limit for project’s ending and also to the quality and performance parameters of the new obtained product. Referring to the innovation project development, the risk of unfulfilling the stated competitive objectives referrers to the exceeding the project’s budget and terms, and also to unfitting in the quality and performance parameters established in the innovation project planning stage. The large diversity of risk sources can be expressed by the possibility of appearance of some unexpected variations of the cost, time and quality of the new products. The innovation projects risk is settled by the variations of the cost, time and quality objectives effective values comparing to the planned values. Those variations are determined by purely random factors. The innovation projects characterized by uniform variations of the cost, time and quality objectives effective values around the mean are considered to be under statistic control. Those projects’ risk may be quantified and the risk impact over the project can be limited. The innovation projects characterized by fluctuant variations of the cost, time and quality objectives effective values around the mean are considered to be out of statistic control. The aim of this paper is to present two categories of statistic methods for innovation projects risk quantifying. The first statistic methods that quantify the risk of unfitting the quantitative objectives referrers to the time risk, cost risk and the risk of unfitting established performance parameters. The second category of methods represents statistic methods that quantify the risk of unfitting the qualitative objectives of the projects – the risk of appearance major quality deficiencies. |
| Keywords: | innovation project; risk evaluation; cost; time and quality objectives |
| JEL: | O32 G32 |
| Date: | 2008–02 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:11663&r=rmg |
| By: | Medina, F.; Iglesias, A. |
| Abstract: | Organic farmers must face different risks than conventional farmers Due to the special features of management of their productive system, and due to the specific characteristics of their cultivations. This study analyses the specific risks that organic farmers must manage as well as the different strategies that there are developing nowadays. Even if the Spanish farmers rely on the insurance system to manage their risks, today organic farmers do not have specific insurance products to manage them. The methodology and results presented in this study include a risk analysis carried out by evaluating statistical, probabilistic, and stochastic properties of the organic production data. We evaluate and discuss the aspects of our study that relate to other international studies. Productions considered in this research are olives, vineyard and cereals. Specific risk management strategies developed by organic farmers Â€Ó in contrast with conventional farmers Â€Ó have been identified and quantified, showing the different attitudes based on their risk perception and the potential vulnerability of their farms. Agricultural insurance tool for organic farmers in Spain has been studied and analyzed as an important risk management. |
| Keywords: | Risk management, organic farming, stochastic simulation, risk strategies and agricultural insurance, Farm Management, Risk and Uncertainty, |
| Date: | 2008 |
| URL: | http://d.repec.org/n?u=RePEc:ags:eaae08:44065&r=rmg |
| By: | Morales, C; Garrido, A.; Palinkas, P.; Szekely, C. |
| Abstract: | This paper explores and analyzes farmers€٠risk perceptions, risk management instruments€٠demand and usage in five Member States (Hungary, Spain, the Netherlands, Germany and Poland). A survey completed by 1047 representative farmers of these EU Member Status collected information that allowed us to set apart two focus areas: the first looks at the declared importance of several sources of farms€٠risk and income instability, and at the actual means that farmers pursue to manage and face them. The second area focuses on the demand for risk management instruments. The paper€ٳ objective is to determine the factors that explain farmers€٠responses in the first area, and based on those factors, analyse the demands for two instruments (insurance, and future & option markets). After carrying out basic descriptive statistic analyses, we perform factor analysis in order to establish the linkages between the perceptions and ranking of risks with the declared strategies to manage them. Logit models were fit to determine potential demand of insurance, and futures & options based on the three factors, and other variables like activity types and other controls, like nationality. Results from the factor analysis show that the perception of risk and actual use of risk management are very diverse. Logit models show that insurance is clearly an alternative instrument to diversification, but its demand is poorly explained by the other factors. Furthermore the demand for the use of futures and options is explained by the three factors, with the volatility factor, positively linked; market access /contractual risks; and diversification, negatively linked. In conclusion, policy makers should proceed with caution selecting the most adequate risk management instruments for farmers. It appears that the expected demand of risk management tools does not fit perfectly with the stated perception of risks. |
| Keywords: | risk, risk management, farmer€ٳ perception., Risk and Uncertainty, |
| Date: | 2008 |
| URL: | http://d.repec.org/n?u=RePEc:ags:eaae08:43956&r=rmg |
| By: | Pyykkonen, P.; Yrjola, T.; Latukka, A. |
| Abstract: | As a consequence of rapid structural change and new investment support scheme agricultural debts have increased and concentrated heavily in Finland. In addition, New Basel Accord (Basel II) regulating the bank business requires more in-depth credit risk assessment from banks. Therefore, there are both endogenous and exogenous reasoning for researching the agricultural credit risks. The purpose of the study is to find out the factors that affect financial risks in agriculture as well as possible change in credit risks. Credit scores depicting the magnitude of financial risk for 664 Finnish FADN farms are calculated and an econometric model is applied to clarify which farm specific factors influence the credit score. According to the study increasing farm size decreases financial risks. Furthermore, higher yields that also reflect higher professional skills of the farmer decreases financial risks. In contrast, increasing debts also increase credit risks. In addition, cereal farms tend to have higher credit risks than animal farms. The latter is due to negative profitability development as a consequence of deteriorated grain prices. Even though credit risks in general have increased the number of farms facing substantial financial problems has not increased. However, given the perpetual economic development and structural change in Finnish farming industry the agricultural credit risks will increase. Hence, the lenders would be condemned to apply stricter criteria when granting loans and debt will not be granted to some smaller farms. |
| Keywords: | Credit risks, financing, Agricultural Finance, |
| Date: | 2008 |
| URL: | http://d.repec.org/n?u=RePEc:ags:eaae08:44048&r=rmg |
| By: | Bachev, H.; Nanseki, T. |
| Abstract: | This paper identifies and assesses the efficiency of major modes for risk governance in Bulgarian dairy farming. Firstly, New Institutional Economics is incorporated and framework for analyzing governance of natural, market, private, and social (institutional) risks presented. Next, major types of risks faced by the dairy farms are specified and dominant market, private, public and hybrid modes of risk governance assessed. Finally, principal forms of risks caused by the dairy farms are identified, and efficiency of governing structure assessed. The development of Bulgarian dairy farming has been associated with quite specific risk structures facing by and causing from this sector. The huge market and institutional instability and uncertainty, and the high transaction costs, blocked evolution of effective market and collective modes for risk protection. A variety of private modes (internal organization, vertical integration, interlinking) emerged to deal with the significant natural, market, private, and social risks faced by the dairy farms and the other affected agents. Nevertheless, diverse risks associated with the dairy farming have not been effectively governed and persist during transition now. That is a consequence of ineffective public (Government, international assistance) intervention to correct market and private sector failures in the risk governance. The later have had considerable negative impacts on the evolution of farms, development of markets, structure of production and consumption, state of environment etc. Certain risks related to the dairy sector €ܤisappearedÂ€Ý due to the lack of effective risk governance and the declining dairy farming. That would lead to further deformation in development of the dairy and related sectors unless effective public measures are taken to mitigate existing problems and risks. |
| Keywords: | risk management, dairy, Bulgaria, Livestock Production/Industries, Risk and Uncertainty, |
| Date: | 2008 |
| URL: | http://d.repec.org/n?u=RePEc:ags:eaae08:44136&r=rmg |