Authors and guest post by Eren Ocakverdi This blog piece intends to introduce a new add-in (i.e. GASMODELU) that estimates selected univariate GARCH models within the Generalized Autoregressive Score (GAS) framework. Table of Contents Introduction GAS Model Specification Application to USDTRY currency Files References Introduction Creal et. al. (2013) proposed a class of observation-driven time series models referred to as generalized autoregressive score (GAS) models. The observation-driven approach allows the use of lagged dependent variables or contemporaneous and lagged exogenous var ..read more

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Authors and guest post by Eren Ocakverdi This blog piece intends to introduce a new add-in (i.e. HXPRINCOMP) that implements the procedure developed by Hamilton and Xi (2022). Table of Contents Introduction Principal components analysis on cyclical component Application to U.S. Treasury Yields Application to large macroeconomic data sets Files References Introduction In their paper, Hamilton and Xi (2022) propose a novel methodology when the goal is to extract the common factors behind the cyclical components of each of the series studied. They argue that focusing on the cyclical compone ..read more

Authors and guest post by Eren Ocakverdi This blog piece intends to introduce a new add-in (i.e. SSPACEGARCH) that extends the current capability of EViews’ available features for the estimation of univariate state space models. Table of Contents Introduction A workaround to control for the changing variance problem Application to a CAPM-type specification Code Discretion Introduction Linear State Space Models (LSSM) assume that the error variance of the measurement/signal equation is constant. In practice, however, there are situations where this may not be the case and the variance of ..read more

Authors and guest post by Eren Ocakverdi This blog piece intends to introduce a new add-in (i.e. BOXCOX) that can be used in applying power transformations to the series of interest and provides alternative methods to estimate the optimal lambda parameter to be used in transformation. Table of Contents Introduction Box-Cox family of transformations Application to Turkey’s tourism data Files References Introduction A stationary time series requires stable mean and variance, which can then be modelled through ARMA-type models. If a series does not have a finite variance, it violates this c ..read more

EViews 12 has added several new enhancements to ENET (elastic net) such as the ability to add observation and variable weights and additional cross-validation methods. In this blog post we will show one of the new methods for time series cross-validation. The demonstration will compare the forecasting performance of rolling window cross-validation with models constructed from least squares as well as a simple split of our dataset into training and test sets. We will be evaluating the out-of-sample prediction abilities of this new technique on some important macroeconomic variables. The analy ..read more

The 2021/03/03 update to EViews 12 has two new smaller Variable Selection features. These will help you extract information on the outcome of any selection method and obtain diagnostics on the selection process for a subset of methods.  The first new feature is a way to extract lists of the search variables that have been kept or rejected by the selection procedure. Naturally, they are the data members @varselkept and @varselrejected. For any Equation object (say, “EQ”) that has been estimated with any of the variable selection techniques, the calls   eq.@varselkept    ..read more

In this blog post we will show how Lasso variable selection works in EViews by comparing it with a baseline least squares regression. We will be evaluating the prediction and variable selection properties of this technique on the same dataset used in the well-known paper “Least Angle Regression” by Efron, Hastie, Johnstone, and Tibshirani. The analysis will show the generally superior in-sample fit and out-of-sample forecast performance of Lasso variable selection compared with a baseline least squares model. Lasso variable selection, new to EViews 12 and also known as the Lasso-OLS hybrid ..read more

Authors and guest post by Eren Ocakverdi This blog piece intends to introduce a new add-in (i.e. SKEWEDUGARCH) that extends the current capability of EViews’ available features for the estimation of univariate GARCH models. Table of Contents Introduction Skewed Student’s-t Distribution Application to USDTRY currency Files References Introduction Volatility is an important concept in itself, but it has a special place in finance as it is usually associated with risk. Although investors believe in higher risk higher reward, it is not an easy task to exploit this trade-off. Price of an asse ..read more

One of the potential pitfalls when working with time series datasets is that the data may have temporary or permanent changes to its levels. These changes could be single time-period outliers, or a fundamental structural shift. EViews 12 introduces a new technique to detect and model these outliers and structural changes through indicator saturation. in the recently released EViews 12, we thought we'd give another demonstration. Table of Contents Indicator Saturation AutoSearch/GETS An Application with Consumption and Income Indicator Saturation Identifying changes in data is essential i ..read more