Alternative strategies for predicting stock market volatility are examined. In out-of-sample forecasting experiments implied-volatility information, derived from contemporaneously observed option prices or history-based volatility predictors, such as GARCH models, are investigated, to determine...

In this study, we apply a rolling window approach to wavelet-filtered (denoised) S&P500 returns (2000–2020) to obtain time varying Hurst exponents. We analyse the dynamics of the Hurst exponents by applying statistical tests (e.g., for stationarity, Gaussianity and self-similarity), a...

In the present study, we investigate the market weak efficiency hypothesis (MEH) in the case of the Tunisian exchange market. For this aim, we use fractional cointegration tests based essentially on estimation of an error correction bivariate ARFIMA model. The cointegration tests are conducted...