Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

The tail dependence structure between investor sentiment and commodity markets.

ABSTRACT: A growing body of literature considers investor sentiment as the partial driver of change in commodity prices. In contrast with previous studies that have almost exclusively focused on linear relationship, this empirical paper investigates the entire dynamic dependence of the quantile of investor sentiment and that of ten important commodities. To do so, we use the novel quantile cross-spectral dependence approach of Baruník and Kley (2019) and the nonparametric causality-in-quantiles test proposed by Balcilar et al. (2017a) over the period 1998-2018. Overall, the results show that the inter-dependence between sentiment and commodity differs according to return quantile and time frequency.

SUBMITTER: Maghyereh A

PROVIDER: S-EPMC7393079 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

The tail dependence structure between investor sentiment and commodity markets.

Maghyereh Aktham A Abdoh Hussein H

Resources policy 20200731

A growing body of literature considers investor sentiment as the partial driver of change in commodity prices. In contrast with previous studies that have almost exclusively focused on linear relationship, this empirical paper investigates the entire dynamic dependence of the quantile of investor sentiment and that of ten important commodities. To do so, we use the novel quantile cross-spectral dependence approach of Baruník and Kley (2019) and the nonparametric causality-in-quantiles test propo ...[more]

PMID: 34173416

Similar Datasets

Predictive effect of investor sentiment on current and future returns in emerging equity markets.

Project description:This study uses Non-linear Predictive Regression Analysis to analyze the effect of investor sentiment on the returns of the selected developing equity markets, including Brazil, South Africa, Indonesia, India, China, Russia, and Pakistan. The Principal Component Analysis is applied to construct an Investor Sentiment Index. In most selected countries, investor sentiment substantially affects contemporaneous market returns, and this effect remains persistent in the short term. However, it becomes less prominent over time. It suggests that stakeholders should give importance to the investors' sentiments while making investment decisions.

| S-EPMC10194879 | biostudies-literature

Forward looking statement, investor sentiment and stock liquidity.

Project description:Information is a critical element of capital markets, and liquidity is the lifeblood of capital markets. Relative to historical information, forward-looking information is of significant value to investors. Based on textual analysis calculations, we selected Chinese A-share listed companies as a research sample to explore the impact of forward-looking information disclosure level on stock liquidity. It is found that the higher the level of forward-looking information disclosure, the better the stock liquidity. Investor sentiment is the transmission mechanism through which the forward looking statement disclosure level affects stock liquidity. The heterogeneity analysis shows that the level of forward-Looking statement disclosure has a more significant effect on stock liquidity improvement for state-owned enterprises and enterprises in low-market regions than those in regions with high marketization levels. The article expands and enriches the research on forward-looking information disclosure, and also has some reference value for regulators to formulate laws and regulations and regulate forward-looking information disclosure.

| S-EPMC10130223 | biostudies-literature

A dynamic analysis of the relationship between investor sentiment and stock market realized volatility: Evidence from China.

Project description:Investor sentiment is a research focus in behavior finance. This paper chooses five proxy variables according to China's reality and uses a two-step principal component analysis to construct an investor sentiment index. The five proxy variables are the number of new stock accounts, turnover ratio, margin balance, net active purchasing amount, and investor attention. In the final part of this study, using the price data from the Shanghai and Shenzhen Security Exchange, this paper investigates the dynamic relationship between investor sentiment and stock market realized volatility based on the thermal optimal path. The empirical results show that when the market fluctuates severely, investor sentiment leads stock market realized volatility over one or two steps. The prediction power is also checked. The results indicate that investor sentiment indeed forecasts the realized volatility. This research supports regulators and financial institutions in taking advanced measures.

| S-EPMC7717912 | biostudies-literature

Stock price movement prediction based on Stocktwits investor sentiment using FinBERT and ensemble SVM.

Project description:Investor sentiment plays a crucial role in the stock market, and in recent years, numerous studies have aimed to predict future stock prices by analyzing market sentiment obtained from social media or news. This study investigates the use of investor sentiment from social media, with a focus on Stocktwits, a social media platform for investors. However, using investor sentiment on Stocktwits to predict stock price movements may be challenging due to a lack of user-initiated sentiment data and the limitations of existing sentiment analyzers, which may inaccurately classify neutral comments. To overcome these challenges, this study proposes an alternative approach using FinBERT, a pre-trained language model specifically designed to analyze the sentiment of financial text. This study proposes an ensemble support vector machine for improving the accuracy of stock price movement predictions. Then, it predicts the future movement of SPDR S&P 500 Index Exchange Traded Funds using the rolling window approach to prevent look-ahead bias. Through comparing various techniques for generating sentiment, our results show that using the FinBERT model for sentiment analysis yields the best results, with an F1-score that is 4-5% higher than other techniques. Additionally, the proposed ensemble support vector machine improves the accuracy of stock price movement predictions when compared to the original support vector machine in a series of experiments.

| S-EPMC10280432 | biostudies-literature

Trade policy announcements can increase price volatility in global food commodity markets.

Project description:Many countries use trade policy to insulate their domestic markets from price volatility. However, there is a widespread concern that such policies-particularly export restrictions-may amplify global price volatility, adversely affecting other countries. Here, using an original dataset on trade policy announcements on wheat and maize encompassing the food price crises of 2007-2008 and 2010-2011, we show that the announcement of trade policy changes can increase global price volatility. This effect applies not only to export restrictions but also to import liberalization measures and is most pronounced when markets are tight (stocks are low). Policymakers should work towards increasing stock levels to mitigate price volatility effects of trade policy changes. When markets are tight, export restrictions and import liberalizations should be avoided.

| S-EPMC10154237 | biostudies-literature

Impact persistence of stock market risks in commodity markets: Evidence from China.

Project description:The risk spillover among financial markets has been noticeably investigated in a burgeoning number of literature. Given those doctrines, we scrutinize the impact persistence of volatility spillover and illiquidity spillover of Chinese commodity markets in this paper. Based on the sample from 2010 to 2020, we reveal that there is a cross-market spillover of volatility and illiquidity in China and also, interactions between volatility and illiquidity in different financial markets are pronounced. More importantly, we demonstrate that different commodity markets have different responsiveness to stock market shocks, which embeds their market characteristics. Specifically, we discover that the majority of the traders in gold market might be hedger and therefore gold market is more sensitive to stock market illiquidity shock and thus the shock impact in persistent. On the other hand, agricultural markets like corn and soybean markets might be dominated by investors and thus those markets respond to the stock market volatility shocks and the shock impact in persistent over 10 periods given the first period of risk shock happening. In fact, different Chinese commodity markets' responsiveness towards Chinese stock market risk shocks indicates the stock market risk impact persistence in Chinese commodity markets. This result can help policymakers to understand the policy propagation effect according to this risk spillover channel and risk impact persistence mechanism in China.

| S-EPMC8575302 | biostudies-literature

Time-frequency domain analysis of investor fear and expectations in stock markets of BRIC economies.

Project description:The purpose of this study is to provide insight into the lead-lag relationships between the BRIC stock index and its constituents. In addition, we assess the comovements between the US volatility index (VIX) as a measure of investor uncertainty and fear and stock returns of BRIC economies. Therefore, the bi-wavelet and wavelet multiple correlations approaches are utilised. Findings from the bi-wavelet technique indicate that there are high interdependencies between the BRIC index and its constituents throughout the time-frequency domain. In addition, comovements between the BRIC index and its constituents was positive and significant. Notwithstanding, we find the BRIC index to be the first variable to respond to shocks when all the study variables were considered in the wavelet multiple cross-correlations. Similarly, the stock market of Brazil is the next to respond to shocks. On the other hand, the stock market of Russia lags in the long-term when the BRIC index was excluded from the wavelet multiple cross-correlations. We also find a uni-directional causality between the VIX and the BRIC stocks in the medium-, and long-terms. Specifically, the US VIX significantly drives the BRIC stocks and considered to be negative. Findings from the study imply that global investors can select any of the stock markets in BRIC to allocate their investments due to their strong interdependencies which may facilitate trade and investments. However, portfolio diversification, safe haven or hedge benefits within this region may be minimal due to their high integration with the BRIC index which demonstrates positive significant comovements. The findings present relevant inferences for portfolio diversification, policy decisions, and risk management schemes. It is recommended that investors hedge against volatilities in the BRIC stock markets using the US VIX.

| S-EPMC8564565 | biostudies-literature

A dataset on tail risk of commodities markets.

Project description:This article contains the datasets related to the research article "The long and short of commodity tails and their relationship to Asian equity markets"(Powell et al., 2017) [1]. The datasets contain the daily prices (and price movements) of 24 different commodities decomposed from the S&P GSCI index and the daily prices (and price movements) of three share market indices including World, Asia, and South East Asia for the period 2004-2015. Then, the dataset is divided into annual periods, showing the worst 5% of price movements for each year. The datasets are convenient to examine the tail risk of different commodities as measured by Conditional Value at Risk (CVaR) as well as their changes over periods. The datasets can also be used to investigate the association between commodity markets and share markets.

| S-EPMC5612784 | biostudies-literature

The dynamic impact of investor climate sentiment on the crude oil futures market: Evidence from the Chinese market.

Project description:Climate risk has become a hot topic of global concern. This paper aims to explore the impact of investor climate sentiment (ICS) on China' s crude oil futures market, covering the period from March 27, 2018, to December 30, 2022. Firstly, this paper employs the Thermal Optimal Path (TOP) method and discovers that the guiding effect of ICS on the volatility of crude oil futures (RVoil) intensifies over time, progressively becoming a pivotal factor in determining volatility. Secondly, based on the lead-lag relationship between ICS and RVoil, this study divides the sample period into five stages and confirms through the HAR model that ICS has a significant inhibitory effect on crude oil volatility during the guiding phase. In addition, incorporating ICS into the HAR model not only improves the model' s goodness of fit but also significantly reduces the prediction error in out-of-sample forecasts. Finally, by comparing with the full-sample analysis, the volatility prediction results of the segmented samples show that during the guiding phase, the predictive power of ICS for crude oil market volatility is significantly improved. Even in the non-guiding phase, ICS can reduce the prediction error to a certain extent. This result further highlights the advantages of the TOP method in revealing the impact of ICS on the prediction of crude oil volatility.

| S-EPMC11819534 | biostudies-literature

Cross-country information transmissions and the role of commodity markets: A multichannel Markov switching approach.

Project description:This paper examines the interrelationships among 9 advanced economies using a novel multichannel approach to investigate, beyond the usual causal relationships, the time-varying dimension of the channels conveying causal relationships. The model is derived from the well-known Markov Switching setting and account for systems described by multiple variables. A Markov switching causality measure is adapted to account for information transmissions between distinct multivariate systems. Each country is described by 5 different fundamental variables reflecting its state. Our multichannel causality measure is then applied on these sets of time series to determine, over time, the main channels through which the information is transmitted between the different countries. In a second step, we investigate the relationships existing between these countries and the commodity markets and look at the possible use of the commodity markets as an indirect channel of information transmission between countries.

| S-EPMC6095546 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data