scholarly journals Building stock market resilience through digital transformation: using Google trends to analyze the impact of COVID-19 pandemic

2020 ◽  
Vol 14 (1) ◽  
Author(s):  
Ding Ding ◽  
Chong Guan ◽  
Calvin M. L. Chan ◽  
Wenting Liu
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Digital Transformation ◽  
Google Trends ◽  
Building Stock ◽  
Market Sentiment ◽  
Price Performance ◽  
Novel Coronavirus ◽  
The Impact

Abstract As the 2019 novel coronavirus disease (COVID-19) pandemic rages globally, its impact has been felt in the stock markets around the world. Amidst the gloomy economic outlook, certain sectors seem to have survived better than others. This paper aims to investigate the sectors that have performed better even as market sentiment is affected by the pandemic. The daily closing stock prices of a total usable sample of 1,567 firms from 37 sectors are first analyzed using a combination of hierarchical clustering and shape-based distance (SBD) measures. Market sentiment is modeled from Google Trends on the COVID-19 pandemic. This is then analyzed against the time series of daily closing stock prices using augmented vector autoregression (VAR). The empirical results indicate that market sentiment towards the pandemic has significant effects on the stock prices of the sectors. Particularly, the stock price performance across sectors is differentiated by the level of the digital transformation of sectors, with those that are most digitally transformed, showing resilience towards negative market sentiment on the pandemic. This study contributes to the existing literature by incorporating search trends to analyze market sentiment, and by showing that digital transformation moderated the stock market resilience of firms against concern over the COVID-19 outbreak.

scholarly journals The Impact of COVID-19 on the Stock Price of Socially Responsible Enterprises: An Empirical Study in Taiwan Stock Market

2021 ◽  
Vol 18 (4) ◽  
pp. 1398
Author(s):  
Kuo-Jung Lee ◽  
Su-Lien Lu
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Abnormal Returns ◽  
Recovery Phase ◽  
Socially Responsible ◽  
Cumulative Impact ◽  
Study Approach ◽  
Price Performance ◽  
The Impact

This study examines the impact of the COVID-19 outbreak on the Taiwan stock market and investigates whether companies with a commitment to corporate social responsibility (CSR) were less affected. This study uses a selection of companies provided by CommonWealth magazine to classify the listed companies in Taiwan as CSR and non-CSR companies. The event study approach is applied to examine the change in the stock prices of CSR companies after the first COVID-19 outbreak in Taiwan. The empirical results indicate that the stock prices of all companies generated significantly negative abnormal returns and negative cumulative abnormal returns after the outbreak. Compared with all companies and with non-CSR companies, CSR companies were less affected by the outbreak; their stock prices were relatively resistant to the fall and they recovered faster. In addition, the cumulative impact of the COVID-19 on the stock prices of CSR companies is smaller than that of non-CSR companies on both short- and long-term bases. However, the stock price performance of non-CSR companies was not weaker than that of CSR companies during times when the impact of the pandemic was lower or during the price recovery phase.

scholarly journals The effects of dividend policy to stock prices of listed companies in Vietnam stock market

2020 ◽  
Author(s):  
Thị Lam Hồ ◽  
Thùy Phương Trâm Hồ
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Dividend Policy ◽  
Corporate Value ◽  
Business Managers ◽  
Dividend Payment ◽  
Share Prices ◽  
Finance Management ◽  
The Impact

Dividend policy is one of the most important policies in corporate finance management. Understanding the impact of dividend policy on the distribution of profits, corporate value and thus on the stock price is important for business managers to make policies and for investors to make investment decisions. This study is conducted to evaluate the impact of dividend policy on share prices for companies listed on Vietnam’s stock market in the period from 2010 to 2018, based on the availability of continuous dividend payment data. Using the FGLS method with panel data of 100 companies listed on the HoSE and HNX, we find evidence of the impact of dividend policy on stock prices, supporting supports the bird in the hand and the signal detection theories. The findings of this study help to suggest a few recommendations for business managers and investors.

scholarly journals Causal Relation Between Stock Market Performance and Firm Investment in China: Mediating Role of Information Asymmetry

SAGE Open ◽  
2019 ◽  
Vol 9 (4) ◽  
pp. 215824401988514
Author(s):  
Ghulam Hussain Khan Zaigham ◽  
Xiangning Wang ◽  
Haji Suleman Ali
Keyword(s):  
Information Asymmetry ◽  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Causal Relation ◽  
Negative Relationship ◽  
Manufacturing Firms ◽  
Price Performance ◽  
Stock Market Performance ◽  
The Impact

The main objectives of this study are to examine the impact of stock price performance on firm’s investment and to investigate the counter impact of changes in investment expenditures on stock price performance. The random effects model was applied on the panel data of Chinese manufacturing firms listed at the Shanghai Stock Exchange and the Shenzhen Stock Exchange during the period 2002 to 2016. The sample contains 398 firms with 5,970 observations. Although there is a statistically significant and negative relationship between stock price and investment expenditures, the impact of stock price on investment expenditures is far greater than that of investment expenditures on stock price. Information asymmetry positively mediates both investment sensitivity to stock prices and stock prices sensitivity to investment. This study is a valuable contribution toward the analysis of investment decision making by manufacturing firms in China. It also provides guidelines for investors to assess the informational status of the capital market before making investment decisions and to comprehensively understand the different decisions made by firms with regard to the issue of new stocks and the indirect information attached with such issues.

Short Selling and Price Pressures in the Korean Stock Market

2015 ◽  
Vol 23 (2) ◽  
pp. 265-287
Author(s):  
Yeongseop Rhee ◽  
Sang Buhm Hahn
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Short Selling ◽  
Market Liquidity ◽  
Dynamic Panel Model ◽  
Market Sentiment ◽  
Order Imbalance ◽  
Price Decline ◽  
Korean Stock Market

This paper examines short-selling activity focusing on its behavior during non-normal times of occasional excesses in the Korean stock market. Using the methodology explained by Brunnermeier and Pederson (2005) and Shkilko et al. (2009; 2012), we first examine whether short-selling is predatory on those event days of large price reversals. Overall there is little predatory abnormal short-selling in the pre-rebound phase and we can observe active contrarian short-selling in the post-rebound phase. When we compared aggressiveness between short-selling and non-short-selling using order imbalance variables, we found that non-short selling is much more aggressive than short selling in the Korean stock market. From the observation of market liquidity measured by quoted spreads, we could find that market liquidity is somewhat limited during price decline stages while it slightly improves during price reversal phases. Also, using dynamic panel model, we test the influences of those variables on stock price changes and disaggregate the compound effect of short-selling reflected in trading volume itself into differentiated ones not only through pure trading channel but also through other complicated channels such as market sentiment change. Main findings from the regression results are as follows : In the Korean stock market, short sellers seem to behave as a contrarian trader rather than a momentum trader; seller-initiated aggressive trading, whether it is by short-selling or non-short-selling, leads to negative order imbalance and price decline; market liquidity is limited by short-selling and further pressure on price decline is added in the pre-rebound stage; and stock prices are affected not only through pure selling (buying) channel but also through other channels in the Korean stock market.

Life-cycle asset allocation and the peso problem: does ambiguity aversion matter?

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nuno Silva
Keyword(s):  
Life Cycle ◽  
Stock Market ◽  
Asset Allocation ◽  
Stock Prices ◽  
Stock Price ◽  
Ambiguity Aversion ◽  
Content Type ◽  
Portfolio Decisions ◽  
State Of The Economy ◽  
The Impact

PurposeThe study aims to show that ambiguity aversion exerts a non-negligible effect on the investors' decisions, especially due to the possibility of sharp declines in stock prices.Design/methodology/approachThe vast majority of previous studies on life-cycle consumption and asset allocation assume that the equity premium is constant. This study evaluates the impact of rare disasters that shift the stock market to a low return state on investors' consumption and portfolio decisions. The author assumes that investors are averse to ambiguity relative to the current state of the economy and must incur a per period cost to participate in the stock market and solve their optimal consumption and asset allocation problem using dynamic programming.FindingsThe results show that most young investors choose not to invest in stocks because they have low accumulated wealth and the potential return from their stock market investments would not cover the participation costs. Furthermore, ambiguity-averse investors hold considerably fewer stocks throughout their lifetime than ambiguity-neutral ones. The fraction of wealth invested in stocks over the typical consumer's life is hump-shaped: it is low for a young individual, peaks at his early 30s and then decreases until his retirement age.Originality/valueTo the best of the author’s knowledge, this is the first study that assesses the impact of negative stock price jumps on the optimal portfolio of an ambiguity-averse investor.

The corporate governance endgame – minority squeeze-out regulation and post-deal litigation in Germany

2017 ◽  
Vol 43 (1) ◽  
pp. 95-123 ◽  
Author(s):  
Ettore Croci ◽  
Eric Nowak ◽  
Olaf Ehrhardt
Keyword(s):  
Detailed Analysis ◽  
Stock Prices ◽  
Stock Price ◽  
Minority Shareholders ◽  
Content Type ◽  
Stock Market Reaction ◽  
Price Performance ◽  
Cash Compensation ◽  
Squeeze Out ◽  
The Impact

Purpose The purpose of this paper is to examine minority squeeze-outs and their regulation in Germany, a country where majority shareholders have extensively used this tool since its introduction in 2002. Using unique hand-collected data, the authors carry out the first detailed analysis of the German squeeze-out offers from the announcement to the outcome of post-deal litigation, examining also the determinants of the decision to squeeze-out minority investors. Design/methodology/approach Using unique data on court rulings and compensations, the authors analyze a sample of 324 squeeze-outs of publicly listed companies from 2002 to 2011 to carry out the first detailed analysis of the squeeze-out procedure and the post-deal litigation. The authors employ the event study methodology to assess the stock market reaction around the announcement of the squeeze-out. Findings Large firms with foreign large shareholders are the most likely to be delisted. Positive stock price performance increases the likelihood of a squeeze-out, but operating performance has the opposite effect. Stock prices react positively to squeeze-out announcements, in particular when the squeeze-out does not follow a previous takeover offer. Post-deal litigation is widespread: nearly all squeeze-outs are legally challenged by minority shareholders. Additional cash compensation is larger in appraisal procedures, but actions of avoidance are completed in less time. Overall, the evidence suggests that starting post-deal litigation by challenging the cash compensation offered in a squeeze-out delivers high returns for minority investors. Research limitations/implications The lack of data concerning the identity of minority shareholders in firms undergoing a squeeze-out does not allow a proper investigation of the incentives of the different types of investors. Practical implications The paper provides evidence about the incentives of the different players in a squeeze-out offer. The findings of the paper could be helpful in assessing the impact of the squeeze-out rule. The results also contribute to the understanding of minority investors’ incentives to start post-deal litigation. Originality/value This paper provides new evidence about post-deal litigation, in particular how investors use the procedures that the system provides them to protect themselves against controlling shareholders. The paper examines all the phases of the squeeze-out procedure and challenges.

Impact on Stock Price by the Inclusion to and Exclusion from CNX Nifty Index

2012 ◽  
Vol 13 (1) ◽  
pp. 39-50 ◽  
Author(s):  
M. Selvam ◽  
G. Indhumathi ◽  
J. Lydia
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Research Study ◽  
Stock Exchange ◽  
Valuation Effect ◽  
Index Maintenance ◽  
Indian Stock Market ◽  
The Impact ◽  
Indian Perspective

Changes in an index are a regular phenomenon and they take place due to the inclusion and exclusion of stocks from the index. The inclusion or exclusion of stocks creates great impact on the value of the firm. However, these changes are simply a short-lived event with no permanent valuation effect. The present research study analyzed the impact of the inclusion into and exclusion of certain stocks from National Stock Exchange (NSE) S&P CNX Nifty index with Indian perspective. The study provides evidence on whether the announcements of Nifty index maintenance committee have any information content. This will also demonstrate the efficiency of Indian stock market with particular reference to NSE. The study revealed that on an average, no permanent effects were observed on stock prices. It is also found from the study that the NSE reacted unfavourably to the inclusion and exclusion of stocks and it is impossible to earn any excess returns where the particular stocks are included or excluded from the index.

scholarly journals Using a Genetic Algorithm to Build a Volume Weighted Average Price Model in a Stock Market

2021 ◽  
Vol 13 (3) ◽  
pp. 1011
Author(s):  
Seung Hwan Jeong ◽  
Hee Soo Lee ◽  
Hyun Nam ◽  
Kyong Joo Oh
Keyword(s):  
Genetic Algorithm ◽  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Trading Volume ◽  
Weighted Average ◽  
Market Liquidity ◽  
Average Price ◽  
Volume Data ◽  
The Impact

Research on stock market prediction has been actively conducted over time. Pertaining to investment, stock prices and trading volume are important indicators. While extensive research on stocks has focused on predicting stock prices, not much focus has been applied to predicting trading volume. The extensive trading volume by large institutions, such as pension funds, has a great impact on the market liquidity. To reduce the impact on the stock market, it is essential for large institutions to correctly predict the intraday trading volume using the volume weighted average price (VWAP) method. In this study, we predict the intraday trading volume using various methods to properly conduct VWAP trading. With the trading volume data of the Korean stock price index 200 (KOSPI 200) futures index from December 2006 to September 2020, we predicted the trading volume using dynamic time warping (DTW) and a genetic algorithm (GA). The empirical results show that the model using the simple average of the trading volume during the optimal period constructed by GA achieved the best performance. As a result of this study, we expect that large institutions will perform more appropriate VWAP trading in a sustainable manner, leading the stock market to be revitalized by enhanced liquidity. In this sense, the model proposed in this paper would contribute to creating efficient stock markets and help to achieve sustainable economic growth.

scholarly journals A Stock Prices Prediction Approach Via Neural Network by Several Investor Indicators

2019 ◽  
pp. 477-484
Author(s):  
Yahui Chen ◽  
Zhan Wen ◽  
Qi Li ◽  
Yuwen Pan ◽  
Xia Zu ◽  
...  
Keyword(s):  
Neural Network ◽  
Stock Market ◽  
Bp Neural Network ◽  
Stock Prices ◽  
Stock Price ◽  
Quantitative Data ◽  
Prediction Models ◽  
Investor Behavior ◽  
Prediction Approach ◽  
The Impact

The prediction of stock indicators such as prices, trends and market indices is the focus of researchers. However, stock market has the characteristics of high noise and non-linearity. Generally, linear algorithms are not good for predicting stock market indicators. Therefore, BP neural network, a model suitable for nonlinear task, is widely used in stock market forecasting. However, many BP neural network prediction models are only based on historical stock quantitative data, and do not consider the impact of investor behavior on the stock market. Therefore, based on historical stock data and quantitative data of investor behavior of ten selected Chinese stocks, this paper trains a three-layer BP neural network to predict the stock prices such as the highest price ,the opening price ,the closing price, the lowest price in a short term. And then, the model that incorporates the investor behavior indicator is compared with the model that is not added. The results show that investor behavior indicators can improve the accuracy and generalization of the stock price forecasting model effectively, especially when the model based on stock quantitative data has a poor prediction accuracy on the test set.

scholarly journals Stock Price Prediction Using LSTM on Indian Share Market

10.29007/qgcz ◽  
2019 ◽  
Author(s):  
Achyut Ghosh ◽  
Soumik Bose ◽  
Giridhar Maji ◽  
Narayan Debnath ◽  
Soumya Sen
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Short Term Memory ◽  
Investor Sentiment ◽  
Spot Price ◽  
Physical Factors ◽  
Stock Price Prediction ◽  
The Impact ◽  
A Company

Predicting stock market is one of the most difficult tasks in the field of computation. There are many factors involved in the prediction – physical factors vs. physiological, rational and irrational behavior, investor sentiment, market rumors,etc. All these aspects combine to make stock prices volatile and very difficult to predict with a high degree of accuracy. We investigate data analysis as a game changer in this domain.As per efficient market theory when all information related to a company and stock market events are instantly available to all stakeholders/market investors, then the effects of those events already embed themselves in the stock price. So, it is said that only the historical spot price carries the impact of all other market events and can be employed to predict its future movement. Hence, considering the past stock price as the final manifestation of all impacting factors we employ Machine Learning (ML) techniques on historical stock price data to infer future trend. ML techniques have the potential to unearth patterns and insights we didn’t see before, and these can be used to make unerringly accurate predictions. We propose a framework using LSTM (Long Short- Term Memory) model and companies’ net growth calculation algorithm to analyze as well as prediction of future growth of a company.

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