M-bands wavelet multiresolution analysis of assets

BenGhoul M., Ayadi W., Alwadi S.

ITALIAN JOURNAL OF PURE AND APPLIED MATHEMATICS, no.45, pp.699-721, 2021 (ESCI) identifier identifier

  • Publication Type: Article / Article
  • Publication Date: 2021
  • Journal Indexes: Emerging Sources Citation Index (ESCI), Scopus, Compendex, zbMATH
  • Page Numbers: pp.699-721
  • Keywords: wavelets, decomposition, time series, financial ratios, multiscale analysis, VAR, stock returns, STOCK, RETURNS
  • Anadolu University Affiliated: Yes


Given that the predictability of financial assets is indispensable to optimize the allocation of the investors' portfolio, a large literature review was dedicated to the question of predictability. Indeed, different studies have examined the relationship between the expected returns and the financial and macroeconomic variables to determine the most predictive indicators, notably the impact of the variables fluctuations on the prediction of the expected returns. Consequently, this paper consists on investigating the impact of the fluctuations in the aggregate price-earnings ratio at different timescales on the stock returns by using financial data from the USA. The data frequency is quarterly from 1952 to 2011. By aggregating the price-earnings ratio via multiresolution wavelets analysis, the results of the estimation of the Vector Autoregressive Model (VAR) demonstrated that the cycles in the price-earnings ratio presented strong predictors for the stock returns at short and intermediate horizons.