We test for the performance of a series of volatility forecasting models (GARCH 1,1; EGARCH 1,1; CGARCH) in the context of several indices from the two oldest cross-border exchanges (Euronext; OMX). Our findings overall indicate that the EGARCH (1,1) model outperforms the other two, both before...

March 2020 packed 2 ½ years of normal U.S. stock market volatility into one month, making it the most volatile month on record. Daily variability clocked in at 6%, six times higher than the average over the past 90 years. How should an investor respond to such volatility? In this article we...

The study examined high volatile assets, specifically the currency exchange rate of the open financial market. Takes into consideration the five most traded paired currencies of the global financial market. And observed, generally, the data set of the unit currency exchange rate exhibit...

The methodology presented provides a quantitative way to characterize investor behavior and price dynamics within a particular asset class and time period. The methodology is applied to a data set consisting of over 250,000 data points of the S&P 100 stocks during 2004-2018. Using a two-way...

In this paper, we used the GARCH (1,1) and GARCH-M (1,1) models to investigate volatility and persistence at daily frequency for European and US financial markets. In the study we included fourteen stock indices (twelve Europeans and two Americans), during March 2013 - January 2017. The results...

The main aim of this paper is to verify the dynamic interdependence and transmission of volatility from the American (SP500) to the Brazilian stock market (IBOVESPA and sectoral indexes). Estimates were performed by GARCH/BEKK methodology, considering the period from January 2007 to December...

This paper investigates whether news suggestive of irrationality within financial markets have an impact on stock returns. We construct a lexicon of words for 'market irrationality' and score daily news articles based on the number and proportion of words they contain from the lexicon. We find...

This paper aims to examine the relation between idiosyncratic volatility (IVOL) and stock returns with full-sample and conditional alpha sub-samples in Vietnam stock market covering the period from January 2008 to December 2018. We test the IVOL effect on stock returns employing Fama-Macbeth...

This study aims at comparing Google Search Volume Indices (GSVIs—including market crash and bear market) and VIX (Investor Fear Gauge Index) in terms of explaining the S&P 500 returns. The VIX is found a more robust predictor of stock market returns than Google indices, and it does granger...

Behavioral finance argues that some properties of asset prices are most reasonably considered as deviations from fundamental value and they are caused by the presence of traders who are not fully rational hence called noise traders. Noise trader approach assumes that sentiment traders exert...