The study aims at forecasting the return volatility of the cryptocurrencies using several machine learning algorithms, like neural network autoregressive (NNETAR), cubic smoothing spline (CSS), and group method of data handling neural network (GMDH-NN) algorithm. The data used in this study is...

The ınvestment decisions of institutional and individual investors in financial markets are largely influenced by market uncertainty and volatility of the investment instruments. Thus, the prediction of the uncertainty and volatilities of the prices and returns of the investment instruments...

This paper examines the effects of the Standard and Poor’s 500 (SP500) stock index crash during the global financial crisis and the COVID-19 pandemic periods on the South African top sector indices (basic materials, consumer goods, consumer services, financials, healthcare, industrials,...

This document presents a multivariate analysis of the relationship among daily returns of pension funds in Mexico from 1997 to 2019. We provide evidence of a positive relationship among daily returns through five statistical methods. We find Granger causality of the returns of some funds to...

In this paper, we study the effectiveness of FX interventions in Chile since adopting a fully flexible exchange rate regime in the late 1990s. In particular, we ask whether these interventions have dumped excess exchange rate volatility and reduced its probability of being in a high volatility...

This paper provides several estimates of the GARCH models' parameters for the S&P500 index, based on returns and CBOE VIX. Using a daily sample collected from 2007 to 2022, we can conclude that adding the VIX information improves the estimates of the long-term volatility. By providing an...