Unobserved component models with asymmetric conditional variances

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Unobserved component models with asymmetric conditional variances

Unobserved component models with GARCH disturbances are extended to allow for asymmetric responses of conditional variances to positive and negative shocks. The asymmetric conditional variance is represented by a member of the QARCH class of models. The proposed model allows to distinguish whether the possibly asymmetric conditional heteroscedasticity affects the short-run or the long-run distu...

متن کامل

Martingale unobserved component models

I discuss models which allow the local level model, which rationalised exponentially weighted moving averages, to have a time-varying signal/noise ratio. I call this a martingale component model. This makes the rate of discounting of data local. I show how to handle such models effectively using an auxiliary particle filter which deploys M Kalman filters run in parallel competing against one an...

متن کامل

Geometric ergodicity of nonlinear autoregressive models with changing conditional variances

The authors give easy-to-check sufficient conditions for the geometric ergodicity and the finiteness of the moments of a random process xt = φ(xt−1, . . . , xt−p)+ tσ(xt−1, . . . , xt−q) in which φ : IR → IR, σ : IR → IR and ( t) is a sequence of independent and identically distributed random variables. They deduce strong mixing properties for this class of nonlinear autoregressive models with ...

متن کامل

Prediction in dynamic models with time-dependent conditional variances*

This paper considers forecasting the conditional mean and variance from a single-equation dynamic model with autocorrelated disturbances following an ARMA process, and innovations with time-dependent conditional heteroskedasticity as represented by a linear GARCH process. Expressions for the minimum MSE predictor and the conditional MSE are presented. We also derive the formula for all the theo...

متن کامل

Measuring the German Output Gap Using Unobserved Component Models

2 Annual and quarterly data on German GDP are decomposed into a nonstationary trend, a stationary cycle and a seasonal component using Kalman filtering and smoothing techniques. The computed trend components of the unobserved component models are then used to calculate annual and quarterly output gap measures for the German economy.

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Computational Statistics & Data Analysis

سال: 2006

ISSN: 0167-9473

DOI: 10.1016/j.csda.2004.12.009