This study introduces a novel two-step machine learning methodology to generate high-frequency (daily and weekly) inflation forecasts in developing economies, where official statistics are typically available only at a monthly frequency and with delays. High-frequency forecasting here is...

This study provides a comprehensive evaluation of six volatility forecasting models applied to twelve dominant and less dominant cryptocurrencies across multiple time horizons using high-frequency intraday data. The exponential generalized autoregressive conditional heteroskedastic (EGARCH),...