The Use of Varma Models in Forecasting Macroeconomic Indicators
نویسنده
چکیده
Although the scalar components methodology used to build VARMA models is rather difficult, the VAR models application being easier in practice, the forecasts based on the first models have a higher degree of accuracy. This statement is demonstrated for variables like the 3-month Treasury bill rate and the spread between the 10 year government bond yield, where the quarterly data are from the U.S. economy (horizon: first quarter of 2001 – second quarter of 2013). It was used a better measure of accuracy than those used in literature till now, the generalized forecast error of second moment, that was adapted to measure relative accuracy. Received: July, 2013 1st Revision: September, 2013 Accepted: October, 2013 DOI: 10.14254/2071789X.2013/6-2/9 JEL Classification: C11, C13, C51
منابع مشابه
VARMA versus VAR for Macroeconomic Forecasting
In this paper, we argue that there is no compelling reason for restricting the class of multivariate models considered for macroeconomic forecasting to VARs given the recent advances in VARMA modelling methodology and improvements in computing power. To support this claim, we use real macroeconomic data and show that VARMA models forecast macroeconomic variables more accurately than VAR models.
متن کاملForecasting U.S. Recessions with Macro Factors
Dynamic latent factors estimated from panels of macroeconomic indicators are used to predict future NBER recession dates. Three monthly macro factors are considered: (1) a bond and exchange rates factor extracted from 22 financial time series; (2) a stock market factor extracted from 4 stock market indicators; (3) a real factor extracted from 4 macroeconomic time series. Three main results emer...
متن کاملForecasting the Equity Risk Premium: The Role of Technical Indicators
While macroeconomic variables have been used extensively to forecast the U.S. equity risk premium and build models to explain it, relatively little attention has been paid to the technical stock market indicators widely employed by practitioners. Our paper fills this gap by studying the forecasting ability of a variety of technical indicators in comparison to that of a number of well-known macr...
متن کاملCombining Diffusion Models and Macroeconomic Indicators with a Modified Genetic Programming Method: Implementation in Forecasting the Number of Mobile Telecommunications Subscribers in OECD Countries
This paper proposes a modified Genetic Programming method for forecasting the mobile telecommunications subscribers’ population.Themethod constitutes an expansion of the hybridGenetic Programming (hGP)method improved by the introduction of diffusion models for technological forecasting purposes in the initial population, such as the Logistic, Gompertz, and Bass, as well as the Bi-Logistic and L...
متن کاملWeighted-covariance Factor Decomposition of Varma Models Applied to Forecasting Quarterly U.s. Gdp at Monthly Intervals
We develop and apply a method, called weighted-covariance factor decomposition (WCD), for reducing large estimated vector autoregressive moving-average (VARMA) data models of many "important" and "unimportant" variables to smaller VARMAfactor models of "important" variables and significant factors. WCD has four particularly notable features, compared to frequently used principal components deco...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2015