I use Google News TM to study the relation between news volumes and stock market volatilities. More than nine million stock market-related news stories in English and (Mandarin) Chinese are collected and the dynamics of the news volume and the stock market volatility is compared in both the...

In this paper we employ the news aggregator GoogleTM News to demonstrate a strong link between the volatility in the stock market and the amount of news available to market participants. The paper also highlights some other areas, in finance and elsewhere, where news aggregators could be useful.

In this paper, the news aggregator Google News is used to assess the impact of worldwide news on the volatility of the Chinese stock market. Although we find a strong link between the global stock market volatility and the amount of stock market-related news available worldwide, the link between...

In this paper we employ the news aggregator GoogleTM News to demonstrate a strong link between the volatility in the stock market and the amount of news available to market participants. The paper also highlights some other areas, in finance and elsewhere, where news aggregators could be useful.

I use Google News TM to study the relation between news volumes and stock market volatilities. More than nine million stock market-related news stories in English and (Mandarin) Chinese are collected and the dynamics of the news volume and the stock market volatility is compared in both the...

We look at the link between the volatility in the Bitcoin market and the volatility in other related traditional markets, i.e. the gold, currency and stock market. We also try to answer if the volatility in the Bitcoin market can be explained by retail investor-driven internet search volumes or,...

In this paper we employ the news aggregator Google News to demonstrate a strong link between the volatility in the stock market and the amount of news available to market participants. The paper also highlights some other areas, in finance and elsewhere, where news aggregators could be useful.

Current models for predicting volatility do not incorporate information flow and are solely based on historical volatilities. We suggest a method to quantify the semantic content of words in news articles about a company and use this as a predictor of its stock volatility. The results show that...

This paper examines the forecasting properties of a Markov regime-switching model applied to Swedish interest rate volatility. A Monte Carlo testing procedure is used to arrive at a three state specification that is able to capture the high degree of leptokurtosis in the data without additional...