Abstract This paper empirically examines the likelihood of any long-run relationship between real exchange rate and real interest rate (RERI) differentials in China using vector autoregressive model (VAR) and hybrid cointegration methodology. The preliminary results based on some limited monthly data are indicative of a rather weak long run relationship. However, the empirical investigation als...

This paper takes a somewhat different approach from the recent literature in estimating exchange rate equations. It assumes uncovered interest rate parity and models how expectations are formed. Agents are assumed to base their expectations of future interest rates and prices, which are needed in the determination of the exchange rate, on predictions from a ten equation VAR model. The overall m...

We model the conditional mean and volatility of stock returns as a latent vector autoregressive (VAR) process to study the contemporaneous and intertemporal relationship between expected returns and risk in a flexible statistical framework and without relying on exogenous predictors. We find a strong and robust negative correlation between the innovations to the conditional moments that leads t...

This paper applies the hybrid dynamic general-equilibrium, vector autoregressive (DGE-VAR) model developed by Ireland (1999) to Canadian time series. It presents the first Canadian evidence that a hybrid DGE-VAR model may have better out-of-sample forecasting accuracy than a simple, structure-free VAR model. The evidence suggests that estimated DGE models have the potential to add good forecast...

The decomposition-based vector autoregressive model (DVAR) provides a new framework for scrutinizing the efficiency of technical analysis in forecasting stock returns. However, its relationships with other technical indicators still remain unknown. This paper investigates the relationships of DVAR model with the Japanese Candlestick indicators using simulations, theoretical explanations and emp...

According to the Harberger-Laursen-Metzler (HLM) effect an exogenous increase in the terms of trade faced by a small open economy leads to an improvement in that country’s trade balance. In this paper structural vector autoregression techniques are used to investigate whether there is any systematic pattern in the responses of the trade balance to terms of trade shocks for a large number of sma...

We measure the effects of COVID-19 outbreak on uncertainty, and we assess consequences uncertainty for key economic variables. use a large, heteroskedastic vector autoregression (VAR) in which error volatilities share two common factors, interpreted as macro financial uncertainty. Macro are allowed to contemporaneously affect macroeconomy conditions, with changes component providing contemporan...

Univariate autoregressive (AR) models can be extended to the multivariate case to study dynamic interrelationships among several variables, all viewed as endogenous. The resulting vector autoregression (V AR) models describe the evolution over time of a vector of n variables yt = (y1t y2t...ynt)0 as a function of its past realizations yt−1,yt−2, ... and a vector of stochastic terms ut = (u1t u2...

Previously, quality control and improvement researchers discussed multivariate control charts for independent processes and univariate control charts for autocorrelated processes separately. We combine the two topics and propose vector autoregressive (VAR) control charts for multivariate autocorrelated processes. In addition, we estimateAR(p) models instead ofARMAmodels for the systematic cause...

This study extends the existing forecasting accuracy debate in the tourism literature by examining the forecasting performance of various vector autoregressive (VAR) models. In particular, this study seeks to ascertain whether the introduction of the Bayesian restrictions (priors) to the unrestricted VAR process would lead to an improvement in forecasting performance in terms of achieving a hig...