Journal ArticleDOI
How does news sentiment impact asset volatility? Evidence from long memory and regime-switching approaches
TLDR
In this article, the authors examined the dynamic relationship between firm-level return volatility and public news sentiment using the new RavenPack News Analytics ⿿ Dow Jones Edition database that captures over 1200 types of firm-specific and macroeconomic news releases and their sentiment scores at high frequencies.About:
This article is published in The North American Journal of Economics and Finance.The article was published on 2013-12-01. It has received 95 citations till now. The article focuses on the topics: News analytics & Volatility (finance).read more
Citations
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Co-movements and spillovers of oil and renewable firms under extreme conditions: New evidence from negative WTI prices during COVID-19.
TL;DR: Positive and economically meaningful spillovers from falling oil prices to both renewable energy and coal markets are found, however, this result is only found for the narrow portion of the authors' sample surrounding the negative WTI event.
Journal ArticleDOI
The impact of sentiment and attention measures on stock market volatility
TL;DR: This article analyzed the impact of sentiment and attention variables on the stock market volatility by using a novel and extensive dataset that combines social media, news articles, information consumption, and search engine data.
Posted Content
The impact of macroeconomic news on quote adjustments, noise and informational volatility
TL;DR: In this article, the impact of macroeconomic news on the informational and noise-driven components in high-frequency quote processes and their conditional variances was studied and the authors found that news-affected responses in all volatility components are influenced by order flow imbalances.
Journal ArticleDOI
Asymmetric volatility response to news sentiment in gold futures
TL;DR: This article studied the relationship between the sentiment of newswire messages and the volatility of returns in the gold futures market and found that negative news has a significantly greater impact on volatility than does positive news.
Journal ArticleDOI
Long memory and regime switching: A simulation study on the Markov Regime-Switching ARFIMA model
Yanlin Shi,Kin-Yip Ho +1 more
TL;DR: In this article, the authors proposed the MRS-ARFIMA model to distinguish between long memory and regime switching via the Autoregressive Fractionally Integrated Moving Average (ARIMA) and Markov Regime-Switching (MRS) models, respectively.
References
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Journal ArticleDOI
A new look at the statistical model identification
TL;DR: In this article, a new estimate minimum information theoretical criterion estimate (MAICE) is introduced for the purpose of statistical identification, which is free from the ambiguities inherent in the application of conventional hypothesis testing procedure.
Journal ArticleDOI
Estimating the Dimension of a Model
TL;DR: In this paper, the problem of selecting one of a number of models of different dimensions is treated by finding its Bayes solution, and evaluating the leading terms of its asymptotic expansion.
Estimating the dimension of a model
TL;DR: In this paper, the problem of selecting one of a number of models of different dimensions is treated by finding its Bayes solution, and evaluating the leading terms of its asymptotic expansion.
Journal ArticleDOI
Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation
TL;DR: In this article, a new class of stochastic processes called autoregressive conditional heteroscedastic (ARCH) processes are introduced, which are mean zero, serially uncorrelated processes with nonconstant variances conditional on the past, but constant unconditional variances.
Journal ArticleDOI
Generalized autoregressive conditional heteroskedasticity
Tim Bollerslev,Tim Bollerslev +1 more
TL;DR: In this paper, a natural generalization of the ARCH (Autoregressive Conditional Heteroskedastic) process introduced in 1982 to allow for past conditional variances in the current conditional variance equation is proposed.