In this paper we examine the volatility of aggregate output and employment in Australia with the aid of a frequency filtering method (the Butterworth filter) that allows each time series to be decomposed into trend, cycle and noise components. This analysis is compared with more traditional...

This paper analyzes the causal relationships between returns and volatilities of assets prices in U.S. and French markets. The period for the study has been taken from January 1997 to December 2000, using daily and weekly data. Initial results show that U.S. stock prices "Granger-cause" French...

The purpose of the paper is to present the fundamental equation in tourism finance that connects tourism research to empirical finance and financial econometrics. The energy industry, which includes, oil, gas and bio-energy fuels, together with the tourism industry, are two of the most important...

This paper examines how the size of the rolling window, and the frequency used in moving average (MA) trading strategies, affects financial performance when risk is measured. We use the MA rule for market timing, that is, for when to buy stocks and when to shift to the risk-free rate. The...

This paper explores the influences of financial deepening on growth and its volatility. Following a review of the theoretical literature that has attempted to explain these relationships, the paper presents time series evidence for the cases of Mexico and the US. The results suggest that, in the...

Time series data affect many aspects of our lives. This paper highlights ten things we should all know about time series, namely: a good working knowledge of econometrics and statistics, an awareness of measurement errors, testing for zero frequency, seasonal and periodic unit roots, analysing...

The purpose of the paper is to present the fundamental equation in tourism finance that connects tourism research to empirical finance and financial econometrics. The energy industry, which includes, oil, gas and bio-energy fuels, together with the tourism industry, are two of the most important...

This paper provides a general framework that enables many existing inference methods for predictive accuracy to be used in applications that involve forecasts of latent target variables. Such applications include the forecasting of volatility, correlation, beta, quadratic variation, jump...

Time series data affect many aspects of our lives. This paper highlights ten things we should all know about time series, namely: a good working knowledge of econometrics and statistics, an awareness of measurement errors, testing for zero frequency, seasonal and periodic unit roots, analysing...

Time series data affect many aspects of our lives. This paper highlights ten things we should all know about time series, namely: a good working knowledge of econometrics and statistics, an awareness of measurement errors, testing for zero frequency, seasonal and periodic unit roots, analysing...