Background Traditional asset pricing models face challenges from financial anomalies, prompting exploration through behavioural finance theory. This study analyses the nuanced relationship between individual investor sentiment and key stock market variables. Objectives To assess the impact of...

News carry information of market moves. The gargantuan plethora of opinions, facts and tweets on financial business offers the opportunity to test and analyze the influence of such text sources on future directions of stocks. It also creates though the necessity to distill via statistical...

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...

Volatility is an important component of asset pricing; an increase in volatility on markets can trigger changes in the risk distribution of financial assets. In conventional financial theory, investors are considered to be rational and any changes in relevant risk are assumed to be a result of...

Several studies have attributed the high excess returns of the momentum strategy in the equity market to investor behavioral biases. However, whether momentum effects occur because of investor underreaction or because of investor overreaction remains a question. Using a simple model to...

Using a very large data set with more than 9,700 stocks listed on NYSE, AMEX and NASDAQ, we analyze overnight price jumps and report short-term investor overreaction to information shocks and document return reversal and predictability up to five days. For negative and positive overnight jumps,...

As noise traders affect stock market by trading, sentiment, as a signal of noise, may have relationships with trading volume. This paper explores the effect of sentiment on the stock market's trading volume. Increase in Volatility Index (VIX) can explain the percentage increase in trading...

Based on data on users' daily adoption of securities service mobile applications, we measure investors' financial attention frequency, which reflects how often they use such apps, to obtain information on their frequency of opening these apps and online duration. We find that financial attention...

The present research investigates the impact of trading volume on stock return volatility using data from the Greek banking system. For our analysis, the empirical study uses daily measures of volatility constructed from intraday data for the period 5 January 2001-30 December 2020. This period...

The objective of this article is to investigate the volatility asymmetry, volatility-volume relationship by considering trading volume as a mixing variable, and the risk-return relationship in the Indian stock market. Daily data from January 2, 1997 to May 30, 2013 for S&P CNX Nifty are used for...