scholarly journals Stock Prediction Based on News Text Analysis

2021 ◽  
Vol 25 (5) ◽  
pp. 581-591
Author(s):  
Wentao Gu ◽  
◽  
Linghong Zhang ◽  
Houjiao Xi ◽  
Suhao Zheng
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
News Media ◽  
Short Term Memory ◽  
Investor Sentiment ◽  
Principal Component ◽  
Online News ◽  
Stock Market Returns ◽  
Financial News ◽  
Sentiment Lexicon

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.

scholarly journals The Measurement Method of Investor Sentiment and Its Relationship with Stock Market

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Jiangshan Hu ◽  
Yunyun Sui ◽  
Fang Ma
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Investor Sentiment ◽  
Principal Component ◽  
Market Volatility ◽  
Response Analysis ◽  
Stock Market Volatility ◽  
Market Returns ◽  
Stock Market Returns ◽  
The Impact

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.

scholarly journals Stock Returns and The Weather Effect: the Case of Ghana

2020 ◽  
Author(s):  
Sampson Atuahene ◽  
Kong Yusheng ◽  
Geoffrey Bentum-Micah
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Exchange ◽  
Investor Sentiment ◽  
Weather Conditions ◽  
Market Returns ◽  
Stock Market Returns ◽  
Economic Significance ◽  
Weather Changes ◽  
Brokerage Firms

In every economy, Stock markets are part of the key elements the build it up. A few decades ago, there has been a significant change in Ghana stock market returns (GSE). Our study examines the statistical and economic significance of investor sentiment, based on weather conditions/changes, on stock market returns. OLS models, assisted by unit root tests were employed in analyzing the data obtained from the Ghana stock exchange platform from 2000 to 2017. From our literature review, we discovered that investors’ perceptions play a central role in finalizing the direction of stock market returns. Regarding our empirical results, we tested whether weather variations influence the investment decisions of investors; we discovered that temperature and cloud cover significantly influences stock market returns. This is because of mood changes is associated with weather conditions variations. However, sunshine per our regression coefficient shows a statistically insignificant impact on investors’ investment choices. Precipitation to a large extend influence stock market activities further affecting its results negatively as our regression results depicted. We concluded stock brokerage firms, companies, and investors (foreign/local) must incorporate weather changes/effects when strategizing about their investment outcomes.

scholarly journals HETEROGENEITY OF SENTIMENT RISK IN MALAYSIAN STOCK MARKET

2016 ◽  
Vol 1 (1) ◽  
Author(s):  
Jasman Tuyon ◽  
Zamri Ahmad ◽  
Mohd Fahmi Ghazali
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Small Firms ◽  
Full Range ◽  
Investor Sentiment ◽  
Theoretical Understanding ◽  
Stock Market Returns ◽  
Regression Methods ◽  
Return Distributions ◽  
Conditional Means

Behavioral risks including investor sentiment plays an important roles in Asia’s stock market behaviors but theoretically and empirically not well understood in traditional conditional means statistic partly due to its heterogeneity roles. In contrast to the existing studies, this paper examine the heterogeneity roles of investor sentiment proxies (i.e. CSI, BCS, and FKLI) in influencing various aggregate stock market indices in Malaysia. The proposed sentiment proxies relation to stock returns are statistically analyzed using mean-based (OLS) and quantile based (QR) regression methods to uncover the relationships accross full range of stock market returns conditional distributions. In the analysis, we examine the possible multidimensional association of various conditional of sentiments (i.e. average, sentiment states, market states, and interaction between sentiment and market states) on size (i.e. big firms vs. small firms) and industry (i.e. defensive vs. speculative) segmented data. The OLS analysis does not provides conclusive significant association of sentiment to returns but the QR analysis reveal emerging patterns of sentiment heterogeneity roles. Specifically, the QR analysis reveal an asymmetric association between sentiment to returns with U-curve pattern from negative magnitude in the lower quantiles and positive magnitude in the upper quantiles. The findings not only consistent with the current hypothesis that sentiment risk is strongly affected the small firms and speculative industry but also the big firms. The sentiment-return associations are statistically significant in extreme lower quantiles and in extreme upper quantiles of return distributions. These patterns are consistent with theoretical postulates of prospect theory and evidence of assymetric overreaction of Asia investors to sentiment news. Overall, the findings from this paper provides new insights for theoretical understanding and practical application of sentiment risk in stock market.

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
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Risk Premium ◽  
Investor Sentiment ◽  
Price Volatility ◽  
Principal Component ◽  
Technical Analysis ◽  
Relative Strength ◽  
Least Square ◽  
The Impact

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).

scholarly journals Do Overnight Returns Truly Measure Firm-Specific Investor Sentiment in the KOSPI Market?

2019 ◽  
Vol 11 (13) ◽  
pp. 3718 ◽  
Author(s):  
Sang Ik Seok ◽  
Hoon Cho ◽  
Chanhi Park ◽  
Doojin Ryu
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Investor Sentiment ◽  
Market Returns ◽  
Short Term ◽  
Stock Market Returns ◽  
Different Types ◽  
Korean Stock Market ◽  
Korean Market

This study analyzes the effect of overnight returns on subsequent stock market returns and investigates whether they do capture investor sentiment in the Korean stock market. Recent study showed that overnight returns are similar to existing sentiment measures, and, thus, are suitable for measuring firm-specific investor sentiment in the U.S. market. Similarly, we found that, for firms in the Korean market, high overnight returns are followed by higher stock returns in the short term (i.e., two or three trading days) but lower stock returns in the long term. However, these effects do not differ for different types of firms (i.e., hard-to-value firms), whereas classical firm-specific sentiment indicators capture these differences. Overall, we found that overnight returns do not truly measure firm-specific investor sentiment in the Korean stock market even though they are partially related to investor sentiment.

A quantile regression approach to evaluate the relative impact of global and local factors on the MENA stock markets

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Slah Bahloul ◽  
Nawel Ben Amor
Keyword(s):  
Stock Market ◽  
Quantile Regression ◽  
Stock Returns ◽  
Stock Markets ◽  
Financial Integration ◽  
Ordinary Least Squares ◽  
Market Returns ◽  
Stock Market Returns ◽  
Content Type ◽  
The Impact

PurposeThis paper investigates the relative importance of local macroeconomic and global factors in the explanation of twelve MENA (Middle East and North Africa) stock market returns across the different quantiles in order to determine their degree of international financial integration.Design/methodology/approachThe authors use both ordinary least squares and quantile regressions from January 2007 to January 2018. Quantile regression permits to know how the effects of explanatory variables vary across the different states of the market.FindingsThe results of this paper indicate that the impact of local macroeconomic and global factors differs across the quantiles and markets. Generally, there are wide ranges in degree of international integration and most of MENA stock markets appear to be weakly integrated. This reveals that the portfolio diversification within the stock markets in this region is still beneficial.Originality/valueThis paper is original for two reasons. First, it emphasizes, over a fairly long period, the impact of a large number of macroeconomic and global variables on the MENA stock market returns. Second, it examines if the relative effects of these factors on MENA stock returns vary or not across the market states and MENA countries.

Weather, investor psychology and stock returns: evidence from Fiji's stock market

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Janesh Sami
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Sunshine Duration ◽  
Market Returns ◽  
Modeling Framework ◽  
Stock Market Returns ◽  
Content Type ◽  
Asset Pricing Models ◽  
Weather Changes ◽  
Practical Implications

PurposeThis paper investigates whether weather affects stock market returns in Fiji's stock market.Design/methodology/approachThe author employed an exponential general autoregressive conditional heteroskedastic (EGARCH) modeling framework to examine the effect of weather changes on stock market returns over the sample period 9/02/2000–31/12/2020.FindingsThe results show that weather (temperature, rain, humidity and sunshine duration) have robust but heterogenous effects on stock market returns in Fiji.Research limitations/implicationsIt is useful for scholars to modify asset pricing models to include weather-related variables (temperature, rain, humidity and sunshine duration) to better understand Fiji's stock market dynamics (even though they are often viewed as economically neutral variables).Practical implicationsInvestors and traders should consider their mood while making stock market decisions to lessen mood-induced errors.Originality/valueThis is the first attempt to examine the effect of weather (temperature, rain, humidity and sunshine duration) on stock market returns in Fiji's stock market.

Do Indian stock market sentiments impact contemporaneous returns?

2018 ◽  
Vol 7 (3) ◽  
pp. 332-346
Author(s):  
Divya Aggarwal ◽  
Pitabas Mohanty
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Temporal Dynamics ◽  
Stock Exchange ◽  
Principal Component ◽  
Stock Index ◽  
Content Type ◽  
Investor Sentiments ◽  
Indian Stock Market ◽  
The Impact

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.

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