33,343 research outputs found
Measuring financial risk : comparison of alternative procedures to estimate VaR and ES
We review several procedures for estimating and backtesting two of the most
important measures of risk, the Value at Risk (VaR) and the Expected
Shortfall (ES). The alternative estimators differ in the way the specify and
estimate the conditional mean and variance and the conditional distribution
of returns. The results are illustrated by estimating the VaR and ES of
daily S&P500 returns
A predictive model of the export behaviour of small and medium sized firms: an applic.
Based on an extensive theoretical review, the aim of this paper is to carry out a closer examination of the differences between exporters according to their commitment to the international market. Once the main disparities are identified by means of a non-parametric test, a logistic analysis based upon data collected from small and medium sized manufacturing firms is conducted in order to construct a classificatory model.Export behaviour; Manufacturing; Small to medium-sized firms; Logistic regression; Ma
Further insights into exporter profiles: a classificatory model
One of the most relevant developments in the recent decades has been the progressive internationalisation of the world economy. To a great extent, physical borders have been removed by technological advancement, and this fact has made possible a rapprochement between countries and their respective cultures. For firms, this situation offers a range of possibilities owing to market increase. But, at the same time, domestic firms will have to face a rise in competition, and, probably, a market share decrease caused by the presence of foreign firms in their local market. Thus, to ensure survival, international expansion of firmsâ activities becomes a necessity more than just an option. Despite this evidence, not all firms feel inclined to tackle their internationalisation process. Even between firms already sending their products abroad, it is possible to distinguish those ones that are fully engaged in export activity from those that just consider it an occasional task. That is to say, all exporters have neither the same international orientation, nor show the same export intensity. Consequently, grouping exporters in a single category could be misleading and could also hinder obtaining solid results in this research area. Furthermore, such a classification can counteract the efficiency of governmental export assistance programmes.The aim of this paper is to carry out a closer examination of the differences between active and passive exporters. With this purpose in mind, we first submit the considered variables to a non-parametric test in order to select those ones that better differentiate between both groups of exporters. Once the most relevant disparities are discovered, the significant variables are used to elaborate a classificatory model via a logistic function. The empirical analysis is based upon data collected from small and medium sized manufacturing firms located in Castilla-La Mancha, an inland region of Spain. The results indicate that a firmâs international experience and export intensity, and managersâ perceptions of foreign trade barriers are the most effective variables for distinguishing active from passive exporters. The obtained model accurately classifies 93% of cases. Finally, these findings allow us to formulate some policy recommendations that, probably, will increase the efficiency of export promotion expenditures.
Bootstrap prediction intervals for VaR and ES in the context of GARCH models
In this paper, we propose a new bootstrap procedure to obtain prediction intervals of future Value at Risk (VaR) and Expected Shortfall (ES) in the context of univariate GARCH models. These intervals incorporate the parameter uncertainty associated with the estimation of the conditional variance of returns. Furthermore, they do not depend on any particular assumption on the error distribution. Alternative bootstrap intervals previously proposed in the literature incorporate the first but not the second source of uncertainty when computing the VaR and ES. We also consider an iterated smoothed bootstrap with better properties than traditional ones when computing prediction intervals for quantiles. However, this latter procedure depends on parameters that have to be arbitrarily chosen and is very complicated computationally. We analyze the finite sample performance of the proposed procedure and show that the coverage of our proposed procedure is closer to the nominal than that of the alternatives. All the results are illustrated by obtaining one-step-ahead prediction intervals of the VaR and ES of several real time series of financial returns.Expected Shortfall, Feasible Historical Simulation, Hill estimator, Parameter uncertainty, Quantile intervals, Value at Risk
Yield management research through the analysis of scientific journals: preliminary results
The aim of this paper is to analyse articles relating to Yield Management published in a selection
of journals at international level during the period 1996-2002. These will then subsequently be
classified in accordance with List of Tourism Characteristic Products (drawn up by the World
Tourism Organization and included in the Tourism Satellite Account), with a view to determining,
on the one hand, which sectors data on Yield Management application is available for and, on the
other, exploring new sectors that can be studied and researched. This paper forms part of a broader
based paper which analyses publications relating to Yield Management in texts and monographs.
The general goal of this line of research is to offer future researchers a methodical and exhaustive
analysis of bibliography and research work done on the subject
GARCH models with leverage effect : differences and similarities
In this paper, we compare the statistical properties of some of the most popular GARCH models with leverage effect when their parameters satisfy the positivity, stationarity and nite fourth order moment restrictions. We show that the EGARCH specication is the most exible while the GJR model may have important limitations when restricted to have nite kurtosis. On the other hand, we show empirically that the conditional standard deviations estimated by the TGARCH and EGARCH models are almost identical and very similar to those estimated by the APARCH model. However, the estimates of the QGARCH and GJR models differ among them and with respect to the other three specications.EGARCH, GJR, QGARCH, TGARCH, APARCH
Is stochastic volatility more flexible than garch?
This paper compares the ability of GARCH and ARSV models to represent adequately the main empirical properties usually observed in high frequency financial time series: high kurtosis, small first order autocorrelation of squared observations and slow decay towards zero of the autocorrelation coefficients of squared observations. We show that the ARSV(1) model is more flexible than the GARCH(1,1) model in the sense that it is able to generate series with higher kurtosis and smaller first order autocorrelation of squares for a wider variety of parameter specifications. Our results may help to clarify some puzzles raised in the empirical analysis of real financial time series
Detecting level shifts in the presence of conditional heteroscedasticity.
The objective of this paper is to analyze the finite sample performance of two variants of the likelihood ratio test for detecting a level shift in uncorrelated conditionally heteroscedastic time series. We show that the behavior of the likelihood ratio test is not appropriate in this context whereas if the test statistic is appropriately standardized, it works better. We also compare two alternative procedures for testing for several level shifts. The results are illustrated by analyzing daily returns of exchange rates
Evaluation of Organic Substrates and Microorganisms as Bio-Fertilisation Tool in Container Crop Production
Microorganisms are only effective when adequate conditions for their survival and development are provided. Among the factors that influence its effectiveness includes the type of soil or culture substrate, which works as an energy source reserve. Therefore, a tomato and a melon crop were established in different cycles to assess the effect of the physicochemical properties of organic substrates based on coconut fibre and vermicompost in three proportions, 0:100, 40:60 and 60:40 (% v:v), on the microbial activity in the rhizosphere when the bacteria Azotobacter vinelandii, Bacillus megaterium and Frateuria aurantia were applied. Concentrations of NO3â, H2PO4â, K+ and Ca2+ in the petiole cellular extract (PCE) were quantified at 60, 90 and 120 days after transplantation (DAT) for tomato and 45 and 65 DAT for melon. We analysed dehydrogenase activity (DHA), acid phosphatase activity (FTA) and ÎČ-glucosidase activity (ÎČ-GLU). In order to maintain optimal volumetric moisture for the survival of microorganisms, automatic control was used to manage the irrigation frequency between 22%â28%. The results showed that physicochemical substrate properties, by incorporating 40% vermicompost into the coconut fibre mixture, increased enzymatic activity. Plants that were inoculated with Azotobacter vinelandii and Frateuria aurantia showed an improvement in NO3â and K+ assimilation achieving highest yields
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