Multi-model transfer function approach tuned by PSO for predicting stock market implied volatility explained by uncertainty indexes.

This paper studies the forecasting power of uncertainty emanating from the commodities market, energy market, economic policy, and geopolitical threats to the CBOE Volatility Index (VIX). In this study, the relationship between the various uncertainty metrics throughout the period 2012-2022, using a multi-model transfer function technique optimized by particle swarm optimization (PSO) is estimated. Furthermore, we utilize PSO for parameter optimization within the multi-model framework, improving model performance and convergence speed.

Fresh evidence on connectedness between prominent markets during COVID-19 pandemic.

Various empirical studies have examined the nexus between financial markets, but this study focused on the comovement among prominent markets. Our study examines the interrelationship among main financial markets, i.e.

Revisiting efficiency in MENA stock markets during political shocks: evidence from a multi-step approach.

In this paper, we attempt to investigate the efficiency of emerging stock markets by considering the advent of dramatic country-specific events. In other words, we analyze and rank the weak-form efficiency levels of emerging stock markets based on a multi-step approach. Our findings support evidence of multifractality and anti-persistent movements of returns, implying a departure from the weak-form efficiency hypothesis.