This article presents an estimation and analysis of the Hurst exponent for Australian stocks using the wavelet technique. Consistent with Mulligan's (2004) study of US technology stocks, we find that the Hurst exponent varies over the cross-section of stocks. We also analyse Mulligan's (2004)...

This paper investigates association between portfolio returns and higher-order systematic co-moments at different timescales obtained through wavelet multi-scaling- a technique that decomposes a given return series into different timescales enabling investigation at different return intervals....

Using a wavelet-based maximum likelihood fractional integration estimator, we test long memory (return predictability) in the returns at the market, industry and firm level. In an analysis of emerging market daily returns over the full sample period, we find that long-memory is not present and...

This paper investigates association between portfolio returns and higher-order systematic co-moments at different timescales obtained through wavelet multi-scaling- a technique that decomposes a given return series into different timescales enabling investigation at different return intervals....

In this paper we propose a procedure based on the subsampling techniques for the comparison of stationary time series that are not necessarily independent. We study a test based on the Euclidean distance between the autocorrelation functions of two series. Consistency of the proposed method is...

This paper utilises wavelet analysis, which is becoming popular in economics and finance, to estimate the hedge ratios for spot positions on the West Texas Intermediate crude oil, soybeans and the S&P500 index. This technique is combined with a two-stage regime switching threshold model to...

Purpose – The purpose of this paper is to examine the volatility of daily returns in a sample of developed and emerging equity markets at different time scales through wavelet decomposition. Such information is vital for international investors who have different time horizons for their...

In analysing ECG data, the main aim is to differentiate between the signal patterns of healthy subjects and those of individuals with specific heart conditions. We propose an approach for classifying multivariate ECG signals based on discriminant and wavelet analyses. For this purpose we use...