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降秩回归模型中的秩检验AI 解读

There has recently been renewed research interest in the development of tests of the rank of a matrix. This article evaluates the performance of some asymptotic tests of rank determination in reduced rank regression models together with bootstrapped versions through simulation experiments. The bootstrapped procedures significantly improve on the performance of the corresponding asymptotic tests. The article also presents a Monte Carlo exercise comparing the forecasting…

利用大量预测变量的主成分进行预测AI 解读

This article considers forecasting a single time series when there are many predictors (N) and time series observations (T). When the data follow an approximate factor model, the predictors can be summarized by a small number of indexes, which we estimate using principal components. Feasible forecasts are shown to be asymptotically efficient in the sense that the difference between the feasible forecasts and the infeasible forecasts constructed using the actual values of the…

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金融波动率：导论AI 解读

Abstract It is now 20 years since the publication of Engle's ( 1982 ) seminal paper, which introduced ARCH to the world. The ARCH paper had an enormous influence on both theoretical and applied econometrics, and was influential in the establishment of the discipline of Financial Econometrics. In this paper we provide an introduction to the special issue on modelling and forecasting financial volatility, which commemorates the Twentieth Anniversary of the publication of ARCH.…

绝对收益水平跳变的建模与预测AI 解读

Abstract Due to high and low volatility periods, time series of absolute returns experience temporary level shifts which differ in length and size. In this paper we modify the basic Censored Latent Effects Autoregressive [CLEAR] model, such that it can describe and forecast the location and size of such level shifts. For our particular application, we assume that technical trading variables may have explanatory value for future level shifts, where these effects may differ…

关于风险的若干评论AI 解读

Abstract Investor risk is a complicated concept in practice and is not well captured by measures of volatility as is well understood by uncertainty theory. Rather than asking statisticians to attempt to measure risk, it may be better to listen to decision theorists, but their suggestions are not very practical. Diversification is clearly helpful in reducing risk but the risk level of one portfolio cannot be measured without knowing the risks of other major portfolios. A…

删失潜在效应自回归模型及其美国失业应用AI 解读

Abstract A model is proposed to describe observed asymmetries in postwar unemployment time series data. We assume that recession periods, when unemployment increases rapidly, correspond with unobserved positive shocks. The generating mechanism of these latent shocks is a censored regression model, where linear combinations of lagged explanatory variables lead to positive shocks, while otherwise shocks are equal to zero. We apply this censored latent effects autoregression to…

This paper studies the error in forecasting an autoregressive process with a deterministic component. We show that when the data are strongly serially correlated, forecasts based on a model that detrends the data using OLS before estimating the autoregressive parameters are much less precise than those based on an autoregression that includes the deterministic components, and the asymptotic distribution of the forecast errors under the two‐step procedure exhibits bimodality.…

强依赖过程的频域预测与信号提取AI 解读

We frequently observe that one of the aims of time series analysts is to predict future values of the data. For weakly dependent data, when the model is known up to a finite set of parameters, its statistical properties are well documented and exhaustively examined. However, if the model was misspecified, the predictors would no longer be correct. Motivated by this observation and because of the interest in obtaining adequate and reliable predictors, Bhansali (1974, Journal…

After a forecast failure, a respecification is usually necessary to account for the data ex post, in which case there is a gain in knowledge as a result of the forecast failure. Using Norwegian consumption as an example, we show that the financial deregulation in the mid‐1980s led to forecast failure both for consumption functions (CFs) and Euler equations (EEs). We argue in the paper that such forecast failures would appear to be at odds with an underlying DGP belonging to…

短期利率的马尔可夫切换与随机波动率扩散模型AI 解读

This article empirically compares the Markov-switching and stochastic volatility diffusion models of the short rate. The evidence supports the Markov-switching diffusion model. Estimates of the elasticity of volatility parameter for single-regime models unanimously indicate an explosive volatility process, whereas the Markov-switching models estimates are reasonable. It is found that either Markov switching or stochastic volatility, but not both, is needed to adequately fit…

基于扩散指数的宏观经济预测AI 解读

This article studies forecasting a macroeconomic time series variable using a large number of predictors. The predictors are summarized using a small number of indexes constructed by principal component analysis. An approximate dynamic factor model serves as the statistical framework for the estimation of the indexes and construction of the forecasts. The method is used to construct 6-, 12-, and 24-month ahead forecasts for eight monthly U.S. macroeconomic time series using…

利率的状态切换AI 解读

We examine the econometric performance of regime-switching models for interest rate data from the United States, Germany, and the United Kingdom. Regime-switching models forecast better out-of-sample than single-regime models, including an affine multifactor model, but do not always match moments very well. Regime-switching models incorporating international short-rate and term spread information forecast better, match sample moments better, and classify regimes better than…

有序响应模型中的平移限制与半参数估计AI 解读

We develop a √n-consistent and asymptotically normal estimator of the parameters (regression coefficients and threshold points) of a semiparametric ordered response model under the assumption of independence of errors and regressors. The independence assumption implies shift restrictions allowing identification of threshold points up to location and scale. The estimator is useful in various applications, particularly in new product demand forecasting from survey data subject…

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 of 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,…

向量自回归与现实AI 解读

This article questions the statistical significance of variance decompositions and impulse response functions for unrestricted vector auto regressions. It suggests that previous authors have failed to provide confidence intervals for variance decompositions and impulse response functions. Two methods of computing such confidence intervals are developed: first, using a normal approximation; second, using bootstrapped resampling. An example from Sims's work is used to…

领先指标究竟领先什么AI 解读

Abstract We propose an optimal filter to transform the Conference Board Composite Leading Index (CLI) into recession probabilities in the US economy. We also analyse the CLI's accuracy at anticipating US output growth. We compare the predictive performance of linear, VAR extensions of smooth transition regression and switching regimes, probit, non‐parametric models and conclude that a combination of the switching regimes and non‐parametric forecasts is the best strategy at…

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嵌套模型的预测精度相等与预测涵盖检验AI 解读

We examine the asymptotic and finite-sample properties of tests for equal forecast accuracy and encompassing applied to 1-step ahead forecasts from nested parametric models. We first derive the asymptotic distributions of two standard tests and one new test of encompassing. Tables of asymptotically valid critical values are provided. Monte Carlo methods are then used to evaluate the size and power of the tests of equal forecast accuracy and encompassing. The simulations…

标普 100 波动率预测：隐含波动率与高频收益的增量信息AI 解读

The information content of implied volatilities and intraday returns is compared, in the context of forecasting index volatility over horizons from 1 to 20 days. Forecasts of two measures of realised volatility are obtained after estimating ARCH models using daily index returns, daily observations of the VIX index of implied volatility and sums of squares of 5-min index returns. The in-sample estimates show that nearly all relevant information is provided by the VIX index…

可预测性的度量：理论与宏观经济应用AI 解读

Abstract We propose a measure of predictability based on the ratio of the expected loss of a short‐run forecast to the expected loss of a long‐run forecast. This predictability measure can be tailored to the forecast horizons of interest, and it allows for general loss functions, univariate or multivariate information sets, and covariance stationary or difference stationary processes. We propose a simple estimator, and we suggest resampling methods for inference. We then…

逻辑斯蒂混合自回归模型AI 解读

We generalise the mixture autoregressive, MAR, model to the logistic mixture autoregressive with exogenous variables, LMARX, model for the modelling of nonlinear time series. The models consist of a mixture of two Gaussian transfer function models with the mixing proportions changing over time. The model can also be considered as a generalisation of the self‐exciting threshold autoregressive, SETAR, model and the open‐loop threshold autoregressive, TARSO, model. The…