Search results for "Stochastic simulation"
showing 10 items of 14 documents
Economic performance and risk of farming systems specialized in perennial crops: An analysis of Italian hazelnut production
2019
Abstract Assessing farm profitability and economic risk is important to support farmers' decisions. Several factors affect yields and product prices, in turn influencing farmers' income level and economic risk. However, the literature has often neglected to explicitly account for the role of product quality. This is particularly important for crops such as hazelnut because farmers' prices vary according to the quality of the harvested product. Furthermore, it seems fundamental to disentangle the role of parameters influencing farm results, noticeably yield, product price and quality. This is because farmers select their risk management tools to satisfy their needs, but these are often suita…
MDA: a MATLAB-based program for morphospace-disparity analysis
2003
A MATLAB® program that examines patterns of state-space occupation is described. Four subroutines are available with which to visualize morphospace patterns: (i) in terms of their features such as dispersion, aggregation and location, thereby allowing users to extract complementary quantitative information about how the state-space is structured, and (ii) in terms of changes in those patterns that can be compared with other biotic (e.g., extinction, origination rates) or abiotic (e.g., environmental proxy) information. The program incorporates many of the latest and most widely used statistical parameters for describing multivariate spaces. The parameters are estimated on the basis of boots…
Multivariate Gaussian criteria in SMAA
2006
Abstract We consider stochastic multicriteria decision-making problems with multiple decision makers. In such problems, the uncertainty or inaccuracy of the criteria measurements and the partial or missing preference information can be represented through probability distributions. In many real-life problems the uncertainties of criteria measurements may be dependent. However, it is often difficult to quantify these dependencies. Also, most of the existing methods are unable to handle such dependency information. In this paper, we develop a method for handling dependent uncertainties in stochastic multicriteria group decision-making problems. We measure the criteria, their uncertainties and…
Forecasting industry sector default rates through dynamic factor models
2008
In this paper we use a reduced-form model for the analysis of portfolio credit risk. For this purpose, we fit a dynamic factor model to a large data set of default rate proxies and macro-variables for Italy. Multiple step ahead density and probability forecasts are obtained by employing both the direct and indirect methods of prediction together with stochastic simulation of the dynamic factor model. We first find that the direct method is the best performer regarding the out-of-sample projection of financial distressful events. In a second stage of the analysis, we find that reducedform portfolio credit risk measures obtained through the dynamic factor model are lower than those correspond…
Forecasting Financial Crises and Contagion in Asia using Dynamic Factor Analysis
2009
Abstract In this paper we use principal components analysis to obtain vulnerability indicators able to predict financial turmoil. Probit modelling through principal components and also stochastic simulation of a Dynamic Factor model are used to produce the corresponding probability forecasts regarding the currency crisis events affecting a number of East Asian countries during the 1997–1998 period. The principal components model improves upon a number of competing models, in terms of out-of-sample forecasting performance.
Application of Monte Carlo technique to evaluate the power injectable on electrical grid by wind farms
2008
This paper is part of a research aimed at assessing the impact of wind generation on the transmission grid of Sicily, second among the Italian regions for wind power installed. To assess the maximum degree of wind generation penetrability in full compliance with the safe operation of the system, it seemed necessary to investigate the reports of contemporary winds and their territorial correlations when load assumes the peak or the minimum. Given the nature of the problem, it has been used a method of analysis based on the application of stochastic simulation techniques type Monte Carlo. In the paper, after describing the current state of wind energy generation in Sicily and development scen…
Forecasting Financial Crises and Contagion in Asia Using Dynamic Factor Analysis
2009
In this paper we use principal components analysis to obtain vulnerability indicators able to predict financial turmoil. Probit modelling through principal components and also stochastic simulation of a Dynamic Factor model are used to produce the corresponding probability forecasts regarding the currency crisis events affecting a number of East Asian countries during the 1997-1998 period. The principal components model improves upon a number of competing models, in terms of out-of-sample forecasting performance.
Hedging of Spatial Temperature Risk with Market-Traded Futures
2011
The main objective of this work is to construct optimal temperature futures from available market-traded contracts to hedge spatial risk. Temperature dynamics are modelled by a stochastic differential equation with spatial dependence. Optimal positions in market-traded futures minimizing the variance are calculated. Examples with numerical simulations based on a fast algorithm for the generation of random fields are presented.
COMPARATIVE ASSESSMENT OF SEVERAL MULTI-CRITERIA DECISION ANALYSIS TOOLS FOR MANAGEMENT OF CONTAMINATED SEDIMENTS
2007
Over the past several decades, environmental decision-making strategies have evolved into increasingly more sophisticated, information-intensive, and complexapproaches including expert judgment, cost-benefit analysis, toxicological risk assessment, comparative risk assessment, and a number of methods forincorporating public and stakeholder values. This evolution has led to an improved array of decision-making aids, including the development of Multi-CriteriaDecision Analysis (MCDA) tools that offer a scientifically sound decision analytical framework. The existence of different MCDA methods and the availability of corresponding software contribute to the possibility of practical implementat…
Stochastic order characterization of uniform integrability and tightness
2013
We show that a family of random variables is uniformly integrable if and only if it is stochastically bounded in the increasing convex order by an integrable random variable. This result is complemented by proving analogous statements for the strong stochastic order and for power-integrable dominating random variables. Especially, we show that whenever a family of random variables is stochastically bounded by a p-integrable random variable for some p>1, there is no distinction between the strong order and the increasing convex order. These results also yield new characterizations of relative compactness in Wasserstein and Prohorov metrics.