scholarly journals Investor sentiment measurement based on technical analysis indicators affecting stock returns: Empirical evidence on VN100

2021 ◽  
Vol 18 (4) ◽  
pp. 297-308
Author(s):  
Lai Cao Mai Phuong ◽  
Vu Cam Nhung

The purpose of this study is to examine whether investor sentiment as measured by technical analysis indicators has an impact on stock returns. The research period is from 2015 to mid-2020. 1-year government bond yields, financial data, transaction data of 57 companies in the VN100 basket, and VNIndex are analyzed. The investor sentiment variable is measured by each technical analysis indicator (Relative Strength Index – RSI, Psychological Line Index – PLI), and the general sentiment variable is established based on extracting the principal component from individual indicators. The paper uses two regression methods – Fama-MacBeth and Generalized Least Square (GLS) – for five different research models. The results show that sentiment plays an important role in stock returns in the Vietnamese stock market. Even controlling the factors such as cash flow per share, firm size, market risk premium, and stock price volatility in the studied models, the impact of sentiment is significant in both the model using individual technical indicators and the model using the general sentiment variable. Furthermore, investor sentiment has a stronger power to explain excess stock returns than their trading behavior. The implication from the results shows that the Vietnamese stock market is inefficient, in which psychology is a very important issue and participants need to pay due attention to this factor. AcknowledgmentThis study was funded by the Industrial University of Ho Chi Minh City (IUH), Vietnam (grant number: 21/1TCNH03).

Accounting ◽  
2021 ◽  
pp. 451-456
Author(s):  
Lai Cao Mai Phuong

This article examines how investor sentiment affects stock returns on Vietnam's stock market. Investor sentiment index is measured by a relative strength index (RSI) of 57 companies listed on the Ho Chi Minh Stock Exchange from January 1, 2015 to July 31, 2020. Control variables include investors' stock trading behavior, firm size, and cash flow per share. Using Fama-MacBeth regression estimation and general least square estimation (GSL) on a daily basis, both methods find the sentiment of high investors producing higher stock returns, on the contrary, the sentiment of low investors erodes stock returns. Different from the results of Brown and Cliff (2004) [Brown, G. W., & Cliff, M. T. (2004). Investor sentiment and the near-term stock market. Journal of empirical finance, 11(1), 1-27], the article found that the investor sentiment factor plays the most important role in explaining the return of the stock market compared to the rest of the factors.


2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Jiangshan Hu ◽  
Yunyun Sui ◽  
Fang Ma

Investor sentiment is a hot topic in behavioral finance. How to measure investor sentiment? Is the influence of investor sentiment on the stock market symmetrical? That is all we need to think about. Therefore, this paper firstly selects five emotional proxy variables and constructs an investor sentiment composite index by principal component analysis. Secondly, the MS-VAR model is employed to study the dynamic relationship among investor sentiment, stock market returns, and volatility. Using the model MSIH (2)-VAR (2), we found that the relationship among the investor sentiment, stock returns, and volatility is different in different regimes. The results of orthogonal cumulative impulse response analysis showed that the shock to investor sentiment has a significant impact on stock market returns, and this impact in the bullish stock market is significantly higher than in the bearish stock market. The impact of the shock to stock market returns on investor sentiment and stock market volatility is relatively significant. The shock to stock market volatility has significant effects on the stock market returns. Overall, the influence of investor sentiment on the stock market is asymmetric; that is, in different regimes of the stock market, the impact of investor sentiment on the stock market is different. Realizing this, investors can better understand and grasp the market, guiding their own investment behavior. Other researchers can also further study the measurement of investor sentiment on this basis to better guide investors’ behavior.


2018 ◽  
Vol 7 (3) ◽  
pp. 332-346
Author(s):  
Divya Aggarwal ◽  
Pitabas Mohanty

Purpose The purpose of this paper is to analyse the impact of Indian investor sentiments on contemporaneous stock returns of Bombay Stock Exchange, National Stock Exchange and various sectoral indices in India by developing a sentiment index. Design/methodology/approach The study uses principal component analysis to develop a sentiment index as a proxy for Indian stock market sentiments over a time frame from April 1996 to January 2017. It uses an exploratory approach to identify relevant proxies in building a sentiment index using indirect market measures and macro variables of Indian and US markets. Findings The study finds that there is a significant positive correlation between the sentiment index and stock index returns. Sectors which are more dependent on institutional fund flows show a significant impact of the change in sentiments on their respective sectoral indices. Research limitations/implications The study has used data at a monthly frequency. Analysing higher frequency data can explain short-term temporal dynamics between sentiments and returns better. Further studies can be done to explore whether sentiments can be used to predict stock returns. Practical implications The results imply that one can develop profitable trading strategies by investing in sectors like metals and capital goods, which are more susceptible to generate positive returns when the sentiment index is high. Originality/value The study supplements the existing literature on the impact of investor sentiments on contemporaneous stock returns in the context of a developing market. It identifies relevant proxies of investor sentiments for the Indian stock market.


2020 ◽  
Vol 9 (2) ◽  
pp. 29
Author(s):  
Heshmatollah Asgari ◽  
Hamed Najafi

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.


2017 ◽  
Vol 16 (3) ◽  
pp. 219-245 ◽  
Author(s):  
Sidika Gulfem Bayram

This study investigates the dynamic relationship between rational and irrational consumer-business sentiments and stock returns in an emerging stock market, Turkey. Consumer and business sentiments are divided into two components: rational and irrational sentiments. Then, the dynamic interactions and the impact of the sentiments on stock returns are examined. The fundamental economic variables used in the study consist of business conditions, economic risk premium, country risk, exchange rate risk, country growth rate, inflation rate, and terms of trade. The results show that Istanbul Stock Exchange (ISE)-100 index returns are positively and significantly affected by the rational sentiments of both consumers and businesses. JEL Classification: G02, G12, G150


Author(s):  
Wentao Gu ◽  
◽  
Linghong Zhang ◽  
Houjiao Xi ◽  
Suhao Zheng

With the vigorous development of information technology, the textual data of financial news have grown massively, and this ever-rich online news information can influence investors’ decision-making behavior, which affects the stock market. Thus, online news is an important factor affecting market volatility. Quantifying the sentiment of news media and applying it to stock-market prediction has become a popular research topic. In this study, a financial news sentiment lexicon and an auxiliary lexicon applicable to the financial field are constructed, and a sentiment index (SI) is constructed by defining the weight of semantic rules. Then, a comprehensive sentiment index (CSI) is constructed via principal component analysis of the sentiment index and structured stock-market trading data. Finally, these two sentiment indices are added to the generalized autoregressive conditional heteroscedastic (GARCH) and the Long short-term memory (LSTM) models to predict stock returns. The results indicate that the prediction results of LSTM models are better than those of GARCH models. Compared with general-purpose lexicons, the financial lexicons constructed in this study are more stable, and the inclusion of a comprehensive investor sentiment index improves the accuracy of measuring sentiment information. Thus, the proposed lexicons allow more comprehensive measurement of the effects of external sentiment factors on stock-market returns and can improve the prediction effect of stock-return models.


2021 ◽  
Vol 12 ◽  
Author(s):  
Sze Ting Chen ◽  
Kai Yin Allison Haga

Purpose: Investor sentiment, the willingness of market participants to invest, is a difficult concept to measure. Exploring the relationship between investor sentiment and stock returns can reveal how investor sentiment affects the operation of the stock market. Such an understanding can assist market participants in making more rational investment decisions based on market laws. Such an understanding can also assist regulators in their roles of supervision and policy making.Methodology: Although the E-GARCH model has the advantage of considering volatility clustering, it has not previously been used to investigate the impact of investor sentiment changes on the Shanghai Composite Index's market return. This research therefore applies the E-GARCH approach to data from 2015 to 2018, to explore the influence of investor sentiment on the return rate of the Shanghai Composite Index.Main Findings: There are three main findings. First, when the investor sentiment is increased by the same amount, the rate of return before a stock market crash will have a smaller increase than the rate of change after the crash, which is a new finding. Second, the rate of return on stocks is susceptible to emotional sentiment, rather than simply depending on stock price. Third, the tendency of retail investors to follow the crowd is less in periods of pessimism than it is in periods of optimism, which, in turn, can push up stock yields.Application: Based on these research results, this article can provide insights to understand how investors' subjective judgments on future earnings affect their investment behavior and how great the impact is on the market. At the same time, it can help investors make more rational investment decisions based on an understanding of market laws, and help regulators with guidance for their supervision and policy making.Originality/Value: This paper contributes to the theory of the investor sentiment index, improving the index construction method by adding two sentiment proxy indicators: investor activity ACT and stock market leverage level. After constructing the sentiment index and comparing it with the stock market index (Shanghai Composite Index), the fit is found to be improved.


2019 ◽  
Vol 46 (3) ◽  
pp. 401-420
Author(s):  
Ahmed Bouteska

Purpose The purpose of this paper is to study a novel and direct measurement of investor sentiment index in the Tunisian stock market that overcomes the weaknesses of a well-known investor sentiment index by Baker and Wurgler (2006, 2007). Design/methodology/approach Based on the data of 43 firms of the Tunisian stock market index (Tunindex) over the period 2004–2016, the author constructs a monthly investor sentiment that reflects both the economic fundamentals and the investor sentiment components. Seven indirect indicators collected from investor sentiment literature and Tunisian stock exchange were analyzed. Specifically, after accounting to remove the sentiment component for macroeconomic factors, the author estimates each sentiment proxy with a number of controlling variables. The residual from the estimation is used to define the author’s measure of excessive investor sentiment. To determine the best timing of sentiment indicators, the author employs a factor sentiment series as the first principal component of these total seven sentiment proxies and their lags of a month. Furthermore, by capturing the highest saturations with the first factor analysis, the author regressed each selected indicator’s lead or one-month lag in a second linear principal component analysis to reach the author’s Tunisian market’s total sentiment index. Findings The results show that all employed indicators may reflect the investor sentiment on the Tunisian stock market. The findings also indicate significant evidence that the author’s sentiment index takes into consideration the political and economic events such as the Jasmine Revolution experienced by Tunisia during the period from January 2, 2004 to December 30, 2016. Moreover, investor sentiment index flow appears to be one leading mechanism for the performance of Tunindex. Originality/value Results found have clearly shown that the author’s seven indirect indicators can reflect investor sentiment in the Tunisian context. The various sentiment proxies are bullish indicators of investor sentiment. Brown and Cliff (2004) argue that the higher bull/bear ratio, the more investor sentiment is bullish. An important value of price–earnings ratio implies that the level of investor confidence as for change in market is also important. Liquidity measured by trading volume, market turnover ratio and liquidity ratio reflects individual investor sentiment. Otherwise, it seems that investors only invest when they are optimistic and reduce market liquidity once they became pessimistic. The monthly response rate to initial public offerings (IPOs) represents a bullish sentiment indicator. Indeed, the more optimistic investors are, the higher the response rate to IPOs. Investor satisfaction also reflects investor sentiment. In other words, a high level of satisfaction translates an important level of optimism. In addition, the author also recognizes that the authors’ Tunisian sentiment index follow general trend of stock market prices and appears to be an important determinant of Tunindex returns during the period of study, from January, 2004 to December, 2016. The author suggests investor sentiment can help predict Tunindex returns, distinguishing between turbulent and tranquil periods in the financial market. The graphical illustration of monthly investor sentiment index shows that it captures extreme events such as the Tunisian revolution of January, 2011, also known as the Jasmine revolution which marked the start of the Arab Spring and the consequences of economic and political turmoil in Tunisia that have disrupted economic activity in the next few years. Like all research work, the current research paper has certain limitations. The choice of control variables allowing the author to separate sentiment component of that fundamental might be criticized. Moreover, there is no unanimous number of control variables but they are chosen according to data availability. The author also believes that one of the study’s weaknesses is that the author has not examined the impact of investor sentiment on the Tunisian stock market. For future interesting avenues of research, the author proposes, first, to study the effect of investor sentiment on financial asset returns and check, second, if sentiment factor constitutes an additional source of business risk valued by the marketplace.


2015 ◽  
Vol 10 (3) ◽  
pp. 504-520 ◽  
Author(s):  
Mustafa Sayim ◽  
Hamid Rahman

Purpose – The purpose of this paper is to examine the impact of Turkish individual investor sentiment on the Istanbul Stock Exchange (ISE) and to investigate whether investor sentiment, stock return and volatility in Turkey are related. Design/methodology/approach – This study used the monthly Turkish Consumer Confidence Index, published by the Turkish Statistical Institute, as a proxy for individual investor sentiments. First, Turkish market fundamentals were regressed on investor sentiments in order to capture the effects of macroeconomic risk factors on investor sentiments. Then, it used the impulse response functions (IRFs) generated from the vector autoregression (VAR) model to examine the effect of unanticipated movements in Turkish investor sentiment to both stock returns and volatility of the ISE. Findings – The generalized IRFs from VAR shows that unexpected changes in rational and irrational investor sentiment have a significant positive impact on ISE returns. This suggests that a positive investor sentiment tends to increase ISE returns. The study also documents that unanticipated increase in the rational component of Turkish investor sentiment has a negative significant effect on ISE volatility. This might indicate that investors have optimistic expectations of the economy overall with respect to market fundamentals in Turkey. This optimism can result in creating positive expectations, reducing uncertainty, and reducing the volatility of stock market returns. Research limitations/implications – The study was applied only for the period 2004-2010 on the ISE stock returns and volatility. Practical implications – Regardless, investors should know the impact of irrational investor sentiments while establishing investment strategies. The results of this study may also help policy makers stabilize investor sentiments to reduce stock market volatility and uncertainty. Originality/value – This paper adds to the limited understanding of investor sentiment impact on stock return and volatility in an emerging market context.


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