879 resultados para Tail index


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In this work project we study the tail properties of currency returns and analyze whether changes in the tail indices of these series have occurred over time as a consequence of turbulent periods. Our analysis is based on the methods introduced by Quintos, Fan and Phillips (2001), Candelon and Straetmans (2006, 2013), and their extensions. Specifically, considering a sample of daily data from December 31, 1993 to February 13, 2015 we apply the recursive test in calendar time (forward test) and in reverse calendar time (backward test) and indeed detect falls and rises in the tail indices, signifying increases and decreases in the probability of extreme events.

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2000 Mathematics Subject Classification: 62G32, 62G05.

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Extreme value theory (EVT) deals with the occurrence of extreme phenomena. The tail index is a very important parameter appearing in the estimation of the probability of rare events. Under a semiparametric framework, inference requires the choice of a number k of upper order statistics to be considered. This is the crux of the matter and there is no definite formula to do it, since a small k leads to high variance and large values of k tend to increase the bias. Several methodologies have emerged in literature, specially concerning the most popular Hill estimator (Hill, 1975). In this work we compare through simulation well-known procedures presented in Drees and Kaufmann (1998), Matthys and Beirlant (2000), Beirlant et al. (2002) and de Sousa and Michailidis (2004), with a heuristic scheme considered in Frahm et al. (2005) within the estimation of a different tail measure but with a similar context. We will see that the new method may be an interesting alternative.

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This paper contributes to the literature on both embodied technical progress and firm dynamics, by formulating an endogenous growth model where selection and imitation play a fundamental role in helping capital good producers to learn about the productivity of technologies embodied in new plants. By calibrating the model to some key aggregates particularly relevant for the embodied capital literature, among them the growth rate of the relative investment price, the model quantitatively replicates the main facts associated to firm dynamics, such as the entry rate and the tail index of the establishment size distribution. In line with the previous literature, it also predicts a contribution to productivity growth of embodied technical progress and selection of around 60%

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We provide an incremental quantile estimator for Non-stationary Streaming Data. We propose a method for simultaneous estimation of multiple quantiles corresponding to the given probability levels from streaming data. Due to the limitations of the memory, it is not feasible to compute the quantiles by storing the data. So estimating the quantiles as the data pass by is the only possibility. This can be effective in network measurement. To provide the minimum of the mean-squared error of the estimation, we use parabolic approximation and for comparison we simulate the results for different number of runs and using both linear and parabolic approximations.

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This paper compares a number of different extreme value models for determining the value at risk (VaR) of three LIFFE futures contracts. A semi-nonparametric approach is also proposed, where the tail events are modeled using the generalised Pareto distribution, and normal market conditions are captured by the empirical distribution function. The value at risk estimates from this approach are compared with those of standard nonparametric extreme value tail estimation approaches, with a small sample bias-corrected extreme value approach, and with those calculated from bootstrapping the unconditional density and bootstrapping from a GARCH(1,1) model. The results indicate that, for a holdout sample, the proposed semi-nonparametric extreme value approach yields superior results to other methods, but the small sample tail index technique is also accurate.

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Extreme stock price movements are of great concern to both investors and the entire economy. For investors, a single negative return, or a combination of several smaller returns, can possible wipe out so much capital that the firm or portfolio becomes illiquid or insolvent. If enough investors experience this loss, it could shock the entire economy. An example of such a case is the stock market crash of 1987. Furthermore, there has been a lot of recent interest regarding the increasing volatility of stock prices. ^ This study presents an analysis of extreme stock price movements. The data utilized was the daily returns for the Standard and Poor's 500 index from January 3, 1978 to May 31, 2001. Research questions were analyzed using the statistical models provided by extreme value theory. One of the difficulties in examining stock price data is that there is no consensus regarding the correct shape of the distribution function generating the data. An advantage with extreme value theory is that no detailed knowledge of this distribution function is required to apply the asymptotic theory. We focus on the tail of the distribution. ^ Extreme value theory allows us to estimate a tail index, which we use to derive bounds on the returns for very low probabilities on an excess. Such information is useful in evaluating the volatility of stock prices. There are three possible limit laws for the maximum: Gumbel (thick-tailed), Fréchet (thin-tailed) or Weibull (no tail). Results indicated that extreme returns during the time period studied follow a Fréchet distribution. Thus, this study finds that extreme value analysis is a valuable tool for examining stock price movements and can be more efficient than the usual variance in measuring risk. ^

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Most species of lizards will shed their tails at the point of contact when grasped by a predator. We investigated the energetic consequences of tail loss by measuring lipids in a scincid lizard that stores energy in its tail for reproduction. Most of the lipids were concentrated in the proximal portion of the tail. Thus, partial tail loss may not severely affect energy stores if the distal portion of the tail is shed in predatory encounters. We also found that the width of the tail was a reliable non-invasive index of energy reserves in this species. (C) 2003 Elsevier Science Inc. All rights reserved.

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This article proposes computing sensitivities of upper tail probabilities of random sums by the saddlepoint approximation. The considered sensitivity is the derivative of the upper tail probability with respect to the parameter of the summation index distribution. Random sums with Poisson or Geometric distributed summation indices and Gamma or Weibull distributed summands are considered. The score method with importance sampling is considered as an alternative approximation. Numerical studies show that the saddlepoint approximation and the method of score with importance sampling are very accurate. But the saddlepoint approximation is substantially faster than the score method with importance sampling. Thus, the suggested saddlepoint approximation can be conveniently used in various scientific problems.

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In this paper, a hydroelectric power plant with long tail-race tunnel has been modelled for assessing its contribution to secondary regulation reserve. Cavitation problems, caused by the discharge conduit length, are expected downstream the turbine where low pressure appears during regulation manoeuvres. Therefore, governor's gains should be selected taking into account these phenomena. On the other hand, regulation services bidden by the plant operator should fulfil TSO (Transmission System Operator) quality requirements. A methodology for tuning governor PI gains is proposed and applied to a Hydro power plant in pre-design phase in northwest area of Spain. The PI gains adjustment proposed provides a proper plant response, according to some established indexes, while avoiding cavitation phenomena.

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This article shows a general way to implement recursive functions calculation by linear tail recursion. It emphasizes the use of tail recursion to perform computations efficiently.