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ARCH 与随机波动率模型中的标准化误差AI 解读

It is well-known that conditional heteroskedasticity thickens the tails of the unconditional distribution of an error term relative to its conditional distribution. To what extent do imperfect forecasts of the conditional variance undo this tail thickening? This note considers the effect of changing the quality of the information embodied in a forecast of a conditional variance. Adding noise of a certain form thickens the tails of the normalized errors, but decreasing the…

遍历平稳时间序列的非参数推断AI 解读

The setting is a stationary, ergodic time series. The challenge is to construct a sequence of functions, each based on only finite segments of the past, which together provide a strongly consistent estimator for the conditional probability of the next observation, given the infinite past. Ornstein gave such a construction for the case that the values are from a finite set, and recently Algoet extended the scheme to time series with coordinates in a Polish space. The present…

An experiment is performed to assess the prevalence of instability in univariate and bivariate macroeconomic time series relations and to ascertain whether various adaptive forecasting techniques successfully handle any such instability. Formal tests for instability and out-of-sample forecasts from sixteen different models are computed using a sample of seventy-six representative U.S. monthly postwar macroeconomic time series, constituting 5,700 bivariate forecasting…

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美国东南部木材企业采伐决策研究AI 解读

In the forestry literature, stochastic extensions of the classic Faustmann model have become the predominant models of optimal harvesting on even-aged timber stands. A recent attempt to estimate a stochastic version of the Faustmann model left several puzzling results unexplained (Provencher, 1995). This paper reports on new estimation and analyses undertaken to resolve these puzzles. Of particular note is the result that the value of using correct price forecasts in the…

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近单位根解释变量模型中的推断AI 解读

This paper examines regression tests of whether x forecasts y when the largest autoregressive root of the regressor is unknown. It is shown that previously proposed two-step procedures, with first stages that consistently classify x as I(1) or I(0), exhibit large size distortions when regressors have local-to-unit roots, because of asymptotic dependence on a nuisance parameter that cannot be estimated consistently. Several alternative procedures, based on Bonferroni and…

使用前馈与循环神经网络预测汇率AI 解读

Abstract In this paper we investigate the out‐of‐sample forecasting ability of feedforward and recurrent neural networks based on empirical foreign exchange rate data. A two‐step procedure is proposed to construct suitable networks, in which networks are selected based on the predictive stochastic complexity (PSC) criterion, and the selected networks are estimated using both recursive Newton algorithms and the method of nonlinear least squares. Our results show that PSC is a…

贝叶斯模型选择与预测及其实证应用AI 解读

This paper builds on some recent work by the author and Werner Ploberger (1991, 1994) on the development of ‘Bayes models’ for time series and on the authors' model selection criterion ‘PIC’. The PIC criterion is used in this paper to determine the lag order, the trend degree and the presence or absence of a unit root in an autoregression with deterministic trend. A new forecast-encompassing test for Bayes models is developed which allows one Bayes model to be compared with…

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利用线性模型与人工神经网络评估期限结构信息的模型选择方法AI 解读

We take a model selection approach to the question of whether forward interest rates are useful in predicting future spot rates, using a variety of out-of-sample forecast-based model selection criteria: forecast mean squared error, forecast direction accuracy, and forecast-based trading system profitability. We also examine the usefulness of a class of novel prediction models called 'artificial neural networks,' and investigate the issue of appropriate window sizes for…

预测准确性的比较AI 解读

We propose and evaluate explicit tests of the null hypothesis of no difference in the accuracy of two competing forecasts. In contrast to previously developed tests, a wide variety of accuracy measures can be used (in particular, the loss function need not be quadratic and need not even be symmetric), and forecast errors can be non-Gaussian, nonzero mean, serially correlated, and contemporaneously correlated. Asymptotic and exact finite-sample tests are proposed, evaluated,…

误设 ARCH 模型的滤波与预测：第二篇AI 解读

A companion paper (Nelson, 1992) showed that in data observed at high frequencies, an ARCH model may perform well in estimating the conditional variance of a process, even when the ARCH model is severely misspecified. While such models may perform reasonably well at filtering (i.e., at estimating unobserved instantaneous conditional variances), they may perform disastrously at medium- and long-term forecasting of the process and its volatility. In this paper, we develop…

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长期因果关系AI 解读

The definition of causation, discussed in Granger (1980) and elsewhere, has been widely applied in economics and in other disciplines. For this definition, a series y t is said to cause x t +l if it contains information about the forecastability for x t +l contained nowhere else in some large information set, which includes x t − j , j ≥ 0. However, it would be convenient to think of causality being different in extent or direction at seasonal or low frequencies, say, than…

将定性调查回答转化为定量预期的方法：澳大利亚制造业应用AI 解读

Abstract This paper analyses and extends alternative procedures for converting qualitative expectations responses to quantitative expectations. A number of conversion procedures is investigated, including the probability model, the time‐varying parameter probability model, and the regression approach. The informational content of the survey expectations is compared with simple time series models. It is found that the expectations models are superior for many series, both in…

协整系统中的预测AI 解读

Abstract We consider the implications for forecast accuracy of imposing unit roots and cointegrating restrictions in linear systems of I (1) variables in levels, differences, and cointegrated combinations. Asymptotic formulae are obtained for multi‐step forecast error variances for each representation. Alternative measures of forecast accuracy are discussed. Finite sample behaviour in a bivariate model is studied by Monte Carlo using control variables. We also analyse the…

扩展记忆变量之间非线性关系的建模AI 解读

A definition of extended memory is provided, generalizing the ideas of long memory and persistence, based on the properties of forecasts over long horizons. Specification of nonlinear models with variables having extended memory is considered in terms of the balance of an equation and it is suggested that many more types of misspecification can occur than with usual situations and could produce important specification errors. Tests of linearity and standard methods of…

模型不确定性的评估与传播AI 解读

SUMMARY In most examples of inference and prediction, the expression of uncertainty about unknown quantities y on the basis of known quantities x is based on a model M that formalizes assumptions about how x and y are related. M will typically have two parts: structural assumptions S, such as the form of the link function and the choice of error distribution in a generalized linear model, and parameters θ whose meaning is specific to a given choice of S. It is common in…

利用奥卡姆窗口进行图模型选择并处理模型不确定性AI 解读

We consider the problem of model selection and accounting for model uncertainty in high-dimensional contingency tables, motivated by expert system applications. The approach most used currently is a stepwise strategy guided by tests based on approximate asymptotic P values leading to the selection of a single model; inference is then conditional on the selected model. The sampling properties of such a strategy are complex, and the failure to take account of model uncertainty…

美国人口的随机预测：超越高、中、低情景AI 解读

Conventional population projections use “high,” “medium,” and “low” scenarios to indicate uncertainty, but probability interpretations are rarely given, and in any event the resulting ranges for vital rates, births, deaths, age groups sizes, age ratios, and population size cannot possibly be probabilistically consistent with one another. This article presents and implements a new method for making stochastic population forecasts that provide consistent probability intervals.…

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量化初始值对非线性预测的影响AI 解读

SUMMARY Motivated by the m-step-ahead prediction problem in non-linear time series, a brief sketch of stochastic chaotic systems is provided. The accuracy of the prediction depends on the initial value, which is a typical feature of non-linear but not necessarily chaotic models. However, if the model is chaotic, small noise can be amplified very quickly through time evolution at some initial values, thereby decreasing dramatically the reliability of the prediction. Further,…