Investor sentiment, realized volatility and stock returns

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Wafa Abdelmalek
Keyword(s):  
Stock Returns ◽  
Investor Sentiment ◽  
Realized Volatility ◽  
Causality Test ◽  
Content Type ◽  
Volatility Index ◽  
Negative Sentiment ◽  
Work Supports ◽  
The Relationship ◽  
Future Realized Volatility

PurposeThis paper examines the relationship between volatility, sentiment and returns in terms of levels and changes for both lower and higher data frequencies using quantile regression (QR) method.Design/methodology/approachIn the first step, the study applies the Granger causality test to understand the causal relationship between realized volatility, returns and sentiment as levels and changes. In the second step, the study employs a QR method to investigate whether investor sentiment and returns can predict realized volatility. This regression method gives robust results irrespective of distributional assumptions and to outliers in the dependent variable.FindingsEmpirical results show that the VIX volatility index is a better fear gauge of market-wide investors' sentiments and has a predictive power for future realized volatility in terms of levels and changes for both higher and lower data frequencies. This study provides evidence that the relationship between realized volatility, investor sentiment and returns, respectively, is not symmetric for all quantiles of QR, as opposed to OLS regression. Furthermore, this work supports the behavioral theory beyond leverage hypothesis in explaining the asymmetric relation between returns and volatility at higher and lower data frequencies.Originality/valueThis paper adds to the limited understanding of investor sentiment’s impact on volatility by proposing a QR model which provides a more complete picture of the relationship at all parts of the volatility distribution for both higher and lower data frequencies and in terms of levels and changes. To the author knowledge, this is the first paper to study the volatility responses to positive and negative sentiment changes for developed market and to use both lower and higher data frequencies as well as data in terms of levels and changes.

scholarly journals The Linkage between Sentiments and Stock Market Dynamics New Evidence from Iran

2020 ◽  
Vol 9 (2) ◽  
pp. 29
Author(s):  
Heshmatollah Asgari ◽  
Hamed Najafi
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Screening Method ◽  
Market Price ◽  
Investor Sentiment ◽  
Financial Assets ◽  
Causality Test ◽  
Research Criteria ◽  
The Impact ◽  
The Relationship

In recent years, the issue of financial behaviour and the impact of investors’ sentiments on their decision making have become such a popular issue. The sentiments of financial activists affect the market price of financial assets and particularly stocks, and therefore it is included in the new pricing models of capital assets. In this article, we seek the effect of investors’ sentiments on the dynamics of the Iranian stock market (TSE). To do this, among the companies accepted in the stock market we select 120, considering the research criteria and screening method, we examined TSE specifics throughout 2010-2018 using regression analysis and causality test. Our results show that firstly investors’ sentiments have a direct effect on the stock returns and there is a bilateral relationship between them. Secondly, inflation has the opposite effect and economic growth has a direct and positive effect on the relationship between investor sentiment and stock returns. Finally, government spending has no significant effect on the relationship between investor sentiment and stock returns.

On the dynamic relationship between gold investor sentiment index and stock market

2019 ◽  
Vol 16 (3) ◽  
pp. 372-392
Author(s):  
Chaiyuth Padungsaksawasdi
Keyword(s):  
Panel Data ◽  
Stock Market ◽  
Stock Returns ◽  
Stock Return ◽  
Investor Sentiment ◽  
Realized Volatility ◽  
Gold Price ◽  
Content Type ◽  
Industry Level ◽  
Dynamic Relationship

Purpose Considering the unique data of the gold investor sentiment index in Thailand, the purpose of this paper is to investigate the bivariate dynamic relationship between the gold investor sentiment index and stock market return, as well as that between the gold investor sentiment index and stock market volatility, using the panel vector autoregression (PVAR) methodology. The author presents and discusses the findings both for the full sample and at the industry level. The results support prior literature that stocks in different industries do not react similarly to investor sentiment. Design/methodology/approach The PVAR methodology with the GMM estimation is found to be superior to other static panel methodologies due to considering both unobservable time-invariant and time-variant factors, as well as being suitable for relatively short time periods. The panel data approach improves the statistical power of the tests and ensures more reliable results. Findings In general, a negative and unidirectional association from gold investor sentiment to stock returns is observed. However, the gold sentiment-stock realized volatility relationship is negative and bidirectional, and there exists a greater impact of a stock’s realized volatility on gold investor sentiment. Importantly, evidence at the industry level is stronger than that at the aggregate level in both return and volatility cases, confirming the role of gold investor sentiment in the Thai stock market. The capital flow effect and the contagion effect explain the gold sentiment-stock return relationship and the gold sentiment-stock volatility relationship, respectively. Research limitations/implications The gold price sentiment index can be used as a factor for stock return predictability and stock realized volatility predictability in the Thai equity market. Practical implications Practitioners and traders can employ the gold price sentiment index to make a profit in the stock market in Thailand. Originality/value This is the first paper to use panel data to investigate the relationships between the gold investor sentiment and stock returns and between the gold investor sentiment and stocks’ realized volatility, respectively.

scholarly journals Does Fear has Stronger Impact than Confidence on Stock Returns? The Case of Asia-Pacific Developed Markets

2020 ◽  
Vol 67 (2) ◽  
pp. 157-175
Author(s):  
Ngoc Bao Vuong ◽  
Yoshihisa Suzuki
Keyword(s):  
Stock Returns ◽  
Investor Sentiment ◽  
Return Predictability ◽  
Asia Pacific ◽  
Market Returns ◽  
Investor Confidence ◽  
Developed Markets ◽  
Volatility Index ◽  
The Impact ◽  
The Relationship

Employing data from Australia, Hong Kong, and Japan over the period between January 2004 to December 2017, this study investigates the relationship between investor sentiment and stock returns. We analyze two reversed sentiment indicators, namely Consumer Confidence Index (CCI) and Volatility Index (VIX), in two conversing situations: low and high sentiment. The empirical evidence suggests that sentiment has a significant link with concurrent returns, but its influence seems to wipe out quickly as the little to no return predictability is detected. More importantly, we find that “investor fear gauge” (VIX) generates a more significant contemporaneous effect on market returns than investor confidence. The impact on future returns, on the contrary, is inconclusive since low CCI and VIX dominate the opposite ones most of the time.

The relationship between financial development and economic growth in Eswatini (formerly Swaziland)

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Siphe-okuhle Fakudze ◽  
Asrat Tsegaye ◽  
Kin Sibanda
Keyword(s):  
Economic Growth ◽  
Granger Causality ◽  
Financial Development ◽  
Granger Causality Test ◽  
Causality Test ◽  
Content Type ◽  
Distributed Lag ◽  
Long Run ◽  
Short Run ◽  
The Relationship

PurposeThe paper examined the relationship between financial development and economic growth for the period 1996 to 2018 in Eswatini.Design/methodology/approachThe Autoregressive Distributed Lag bounds test (ARDL) was employed to determine the long-run and short-run dynamics of the link between the variables of interest. The Granger causality test was also performed to establish the direction of causality between financial development and economic growth.FindingsThe ARDL results revealed that there is a long-run relationship between financial development and economic growth. The Granger causality test revealed bidirectional causality between money supply and economic growth, and unidirectional causality running from economic growth to financial development. The results highlight that economic growth exerts a positive and significant influence on financial development, validating the demand following hypothesis in Eswatini.Practical implicationsPolicymakers should formulate policies that aims to engineer more economic growth. The policies should strike a balance between deploying funds necessary to stimulate investment and enhancing productivity in order to enliven economic growth in Eswatini.Originality/valueThe study investigates the finance-growth linkage using time series analysis. It determines the long-run and short-run dynamics of this relationship and examines the Granger causality outcomes.

Impact of oil volatility shocks on global emerging market stock returns

2017 ◽  
Vol 13 (5) ◽  
pp. 578-591 ◽  
Author(s):  
Probal Dutta ◽  
Md Hasib Noor ◽  
Anupam Dutta
Keyword(s):  
Stock Returns ◽  
Emerging Market ◽  
Equity Returns ◽  
Oil Price ◽  
Financial Assets ◽  
Stock Market Returns ◽  
Content Type ◽  
Volatility Index ◽  
Jump Model ◽  
Oil Price Risk

Purpose The purpose of this paper is to investigate whether the crude oil volatility index (OVX) plays any key role in explaining the trend in emerging market stock returns from a global standpoint. Design/methodology/approach At the empirical stage, different forms of the GARCH-jump model have been estimated. Findings The findings confirm the effects of OVX on equity returns. In addition, the results document that there exist time-varying jumps in the stock market returns. Besides, the impacts of OVX shocks appear to be symmetric. The analysis further shows that the magnitude of OVX impact is marginally bigger than that of the conventional oil price shocks. Originality/value Since various financial assets are traded on the basis of oil and equity markets, investors, for instance, could use the findings of this study for taking proper investment decisions and gaining better portfolio diversification benefits. Additionally, policymakers could utilize the results to develop effective measures and strategies in order to minimize the oil price risk.

scholarly journals The Impact of Investor Sentiment on Return of Different Industries in Pakistan

2017 ◽  
pp. 1-23
Author(s):  
Sumayya Chughtai Et al.,
Keyword(s):  
Stock Returns ◽  
Principle Component Analysis ◽  
Negative Relationship ◽  
Investor Sentiment ◽  
Differential Impact ◽  
Future Period ◽  
Market Sentiment ◽  
Available Information ◽  
The Impact ◽  
The Relationship

We classify stocks in different industries to measure industrial sentiment based on principle component analysis in order to examine whether investor sentiment exerts a differential impact on stock returns across different industries. After having constructed industry-level sentiment indices we construct a composite investor sentiment index. Our results suggest that investor sentiment negatively affects current as well as future stock returns in Pakistan over the examined period. However, we find that the influence of investor sentiment varies substantially across different industries. We also find that the market sentiment index has a negative relationship with both current and future stock returns. We also show that the direction of the relationship between return and sentiment remains same for the current and future period. This indicates that investors overreact to the available information and mispricing exists for a prolonged time. Our results confirm that sentiment driven mispricing persists for upcoming time and stock markets are not fully efficient to adjust instantaneously.

A new look at the meeting clustering effect

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ángel Pardo ◽  
Eddie Santandreu
Keyword(s):  
Stock Returns ◽  
Stock Exchange ◽  
Abnormal Returns ◽  
Relevant Information ◽  
Investor Attention ◽  
Content Type ◽  
Potential Link ◽  
Clustering Effect ◽  
Trading Volumes ◽  
The Relationship

PurposeThe study aims to test the existence of a meeting clustering effect in the Spanish Stock Exchange (SSE).Design/methodology/approachThis paper studies the relationship between the clustering of annual general meetings and stock returns in the SSE. A multivariate analysis is carried out in order to analyse the relationship between monthly returns and the clustering of general meetings in the SSE.FindingsThe authors show that meeting clustering exists and that some months exhibit significant and positive additional returns related to the holding of ordinary or extraordinary general meetings.Research limitations/implicationsThe authors have explored some possible explanations for the meeting clustering effect, such as a potential link with the “Halloween” effect or the presence of higher-than-normal levels of volatility, trading volumes or investor attention. However, none of these can explain the meeting clustering effect that emerges as a new anomaly in the SSE.Practical implicationsThe authors have documented significant and positive abnormal returns in some months that coincide with the holding of general meetings. Therefore, the holding of ordinary and/or extraordinary meetings in some months involves the release of relevant information for investors.Originality/valueThis study complements the financial literature because it is focused on the clustering of meetings and its effect on a stock market whose legal order is based on civil law. This fact allows us to shed new light on meeting clustering and its effect on other types of markets.

The complex relationship between inflation and equity returns

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jinan Liu ◽  
Apostolos Serletis
Keyword(s):  
Central Bank ◽  
Stock Returns ◽  
Empirical Studies ◽  
Equity Returns ◽  
Empirical Literature ◽  
Complex Relationship ◽  
Inflation Uncertainty ◽  
Stock Market Returns ◽  
Content Type ◽  
The Relationship

PurposeTo investigate the complex relationship between inflation, inflation uncertainty and equity returns.Design/methodology/approachThis paper uses a bivariate VARMA, GARCH-in-mean, asymmetric BEKK model to investigate the relationship between inflation, inflation uncertainty and equity returns.FindingsUsing monthly inflation and equity returns data for the G7 and EM7 economies, we find that the effects of inflation and inflation uncertainty on equity returns vary across countries.Research limitations/implicationsThe mixed evidence we find potentially reflects the changing dynamics, policy regimes, economic shocks and country-specific factors (such as differences in the financing patterns of enterprises and the legal and financial environments) across the G7 and EM7 countries.Practical implicationsWe contribute to the empirical literature in the following ways. First, we rely on a wide sample of countries, including both developed and emerging economies. Second, we extend previous research by estimating a GARCH-in-mean model of monthly equity returns in which both realized returns and their conditional volatility are allowed to vary with inflation. Previous articles that studied the relationship between inflation and stock market returns generally sought time-invariant effects of inflation on stock returns.Social implicationsThe paper helps to reconcile the divergent results of previous empirical studies and distinguish between alternative explanations of the relationship between inflation and equity returns.Originality/valueOur study provides an improved comprehension of the ambiguous relationship between inflation, inflation uncertainty and equity returns under various central bank mandates and different levels of central bank independence. The mixed empirical evidence across countries we present provides insights for the macroeconomic models that consider the relationship between uncertainty and macroeconomic performance as a fundamental building block. Therefore, our empirical study calls for further work on the relationship between inflation, inflation uncertainty and equity returns.

Investor Sentiment and Stock Returns

2015 ◽  
pp. 315-328
Author(s):  
Serkan Yılmaz Kandır ◽  
Veli Akel ◽  
Murat Çetin
Keyword(s):  
Stock Returns ◽  
Investor Sentiment ◽  
Consumer Confidence ◽  
Cointegration Test ◽  
Sample Period ◽  
Monthly Data ◽  
Out Of Sample ◽  
Confidence Index ◽  
The Relationship

In this chapter, the authors investigate the relationship between investor sentiment and stock returns in an out of sample market, namely Borsa Istanbul. The authors use the Consumer Confidence Index as an investor sentiment proxy, while utilizing BIST Second National Index as a measure of small capitalized stock returns. The sample period spans from January 2004 to May 2014. By using monthly data, the authors employ cointegration test and error–correction based Granger causality models. The authors' findings suggest that there is a long-term relationship between investor sentiment and stock returns in Borsa Istanbul. Moreover, a unidirectional causal relationship from investor sentiment to stock returns is also found.

scholarly journals The correlation and volatility between bitcoin and the blockchain index

2020 ◽  
Vol 4 (2) ◽  
pp. 103-115
Author(s):  
Tuotuo Qi ◽  
Tianmei Wang ◽  
Jianming Zhu ◽  
Ruyu Bai
Keyword(s):  
Granger Causality ◽  
Design Methodology ◽  
Granger Causality Test ◽  
External Shocks ◽  
Class Model ◽  
Causality Test ◽  
Content Type ◽  
Blockchain Technology ◽  
The World ◽  
The Relationship

Purpose The encrypted money market has attracted the attention of investors all over the world. Among the encrypted currency, bitcoin is undoubtedly the most popular. Because blockchain technology is the crucial support of bitcoin, exploring the relationship between bitcoin and the blockchain index is necessary. Design/methodology/approach This paper uses the Granger causality test to explore the correlation between bitcoin and the blockchain index. Furthermore, their volatility is analyzed by a GARCH-class model. Findings The results show that no significant correlation exists between bitcoin and the blockchain index; external shocks aggravate the volatility of bitcoin and the blockchain index, and the volatility has a certain degree of sustainability; and blockchain index has obvious leverage, namely, its decline has a stronger impact. Originality/value The volatility of bitcoin and the blockchain index is crucial for investors.

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