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筒仓仓顶钢罩棚作为一种附属设施,在粮食物流方面得到广泛应用,由于粮食自身通风需要,排到室内的热废空气,也应该及时排到室外,本文就该系统自然通风换气的设计进行了有益的探讨。     

Econometric modelling in finance and risk management: An overview

This paper gives an overview about the sixteen papers included in this special issue. The papers in this special issue cover a wide range of topics. Such topics include discussing a class of tests for correlation, estimation of realized volatility, modeling time series and continuous-time models with long-range dependence, estimation and specification testing of time series models, estimation in a factor model with high-dimensional problems, finite-sample examination of quasi-maximum likelihood estimation in an autoregressive conditional duration model, and estimation in a dynamic additive quantile model.     

Estimation in threshold autoregressive models with a stationary and a unit root regime

This paper treats estimation in a class of new nonlinear threshold autoregressive models with both a stationary and a unit root regime. Existing literature on nonstationary threshold models has basically focused on models where the nonstationarity can be removed by differencing and/or where the threshold variable is stationary. This is not the case for the process we consider, and nonstandard estimation problems are the result.     

Specification testing in discretized diffusion models: Theory and practice

We propose two new tests for the specification of both the drift and the diffusion functions in a discretized version of a semiparametric continuous-time financial econometric model. Theoretically, we establish some asymptotic consistency results for the proposed tests. Practically, a simple selection procedure for the bandwidth parameter involved in each of the proposed tests is established based on the assessment of the power function of the test under study. To the best of our knowledge, this is the first approach of this kind in specification of continuous-time financial econometrics. The proposed theory is supported by good small and medium-sample studies.     

Empirical Comparisons in Short-Term Interest Rate Models Using Nonparametric Methods

This study applies the nonparametric estimation procedure tothe diffusion process modeling the dynamics of short-term interestrates. This approach allows us to operate in continuous time,estimating the continuous-time model, despite the use of discretedata. Three methods are proposed. We apply these methods totwo important financial data. After selecting an appropriatebandwidth for each dataset, empirical comparisons indicate thatthe specification of the drift has a considerable impact onthe pricing of derivatives through its effect on the diffusionfunction. In addition, a novel nonparametric test has been proposedfor specification of linearity in the drift. Our simulationdirects us to reject the null hypothesis of linearity at the5% significance level for the two financial datasets.     

Econometric estimation in long-range dependent volatility models: Theory and practice

It is commonly accepted that some financial data may exhibit long-range dependence, while other financial data exhibit intermediate-range dependence or short-range dependence. These behaviours may be fitted to a continuous-time fractional stochastic model. The estimation procedure proposed in this paper is based on a continuous-time version of the Gauss–Whittle objective function to find the parameter estimates that minimize the discrepancy between the spectral density and the data periodogram. As a special case, the proposed estimation procedure is applied to a class of fractional stochastic volatility models to estimate the drift, standard deviation and memory parameters of the volatility process under consideration. As an application, the volatility of the Dow Jones, S&P 500, CAC 40, DAX 30, FTSE 100 and NIKKEI 225 is estimated.     

An adaptive empirical likelihood test for parametric time series regression models

We propose an adaptive empirical likelihood (EL) test for a parametric regression model against a class of alternatives for weakly dependent time series observations. The test is formulated by maximizing a standardized version of the EL statistic over a set of smoothing bandwidths. It is demonstrated that the proposed test is able to distinguish the null hypothesis from a series of local alternatives at an optimal rate.     

Nonparametric simultaneous testing for structural breaks

In this paper we consider a regression model with errors that are martingale differences. This modeling includes the regression of both independent and time series data. The aim is to study the appearance of structural breaks in both the mean and the variance functions, assuming that such breaks may occur simultaneously in both the functions. We develop nonparametric testing procedures that simultaneously test for structural breaks in the conditional mean and the conditional variance. The asymptotic distribution of an adaptive test statistic is established, as well as its asymptotic consistency and efficiency. Simulations illustrate the performance of the adaptive testing procedure. An application to the analysis of financial time series also demonstrates the usefulness of the proposed adaptive test in practice.     

Estimation of technical change and price elasticities: a categorical time–varying coefficient approach

We propose a categorical time-varying coefficient translog cost function, where each coefficient is expressed as a nonparametric function of a categorical time variable, thereby allowing each time period to have its own set of coefficients. Our application to U.S. electricity firms reveals that this model offers two major advantages over the traditional time trend representation of technical change: (1) it is capable of producing estimates of productivity growth that closely track those obtained using the Törnqvist approximation to the Divisia index; and (2) it can solve a well-known problem commonly referred to as “the problem of trending elasticities”.