ENDOGENOUS PARTICIPATION, RISK, AND LEARNING IN THE STOCK MARKET

2020 ◽  
pp. 1-33 ◽  
Author(s):  
Michael Shin
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Price Volatility ◽  
Participation Rate ◽  
Participation Rates ◽  
Asset Pricing Model ◽  
Excess Volatility ◽  
Subjective Risk ◽  
Cross Country

A simple asset pricing model with both endogenous stock market participation and subjective risk can explain the negative cross-country correlation between participation rates and the volatility of excess returns, along with the time-varying participation rates in the data. Belief-driven learning dynamics can explain the interplay between participation rates, subjective risk, and stock price volatility. When agents adaptively learn about the risk and return, my model generates 25% of the excess volatility observed in US stock prices, while also matching key moments. With learning about risk, excess volatility of stock prices is driven by fluctuations in the participation rate that arise because agents’ risk estimates vary with prices. I find that learning about risk is quantitatively more important than learning about returns.

scholarly journals The Impact of Economic Agents Perceptions on Stock Price Volatility

2015 ◽  
Vol 63 (4) ◽  
pp. 1229-1234
Author(s):  
Jaroslav Bukovina
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Negative Impact ◽  
Positive Impact ◽  
Price Volatility ◽  
Investment Strategy ◽  
Economic Agents ◽  
Market Indexes ◽  
The Impact

This paper studies perceptions of economic subjects and its impact on stock prices. Perceptions are represented by stock market indexes and Facebook activity. The contribution of this paper is twofold. In the first place, this paper analyzes the unique data of Facebook activity and proposes the methodology for employment of social networks as a proxy variable which represents the perceptions of information in society related to the specific company. The second contribution is the proposal of potential link between social network principles and theories of behavioral economics. Overall, the author finds the negative impact of Facebook activity on stock prices and the positive impact of stock market indices. The author points the implications of findings to protection of company reputation and to investment strategy based on the existence of undervalued stocks.

scholarly journals Stock Price Volatility Modelling with Regimes in Conditional Mean and Variance

2021 ◽  
pp. 113-121
Author(s):  
Abdulganiyu Salami ◽  
Timilehin Olasehinde
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Investment Decision ◽  
Price Volatility ◽  
Macroeconomic Policies ◽  
Volatility Clustering ◽  
Conditional Mean ◽  
High Volatility ◽  
Mean And Variance

This study examined the presence and nature of volatility in the Nigerian Stock market. Through a graphical presentation of the Nigerian stock prices, it was observed that there exist two regimes of volatility clustering between the periods of 1985M6 to 1999M12 and 2000M1 to 2018M6. Employing a regime covariate autoregressive (AR-X) with an exponential GARCH model, that allows for a shift in intercept, it was found that the second regime, 2000 M1 to 2018 M6, is more volatile, and that modelling of Nigerian stock market requires a technique that considers more than one regime of volatility clustering. Consequently, the study recommends that local and foreign investors take into consideration the high volatility of the recent Nigerian stock prices in making their investment decision and that policymakers take cognizance of the volatility in designing macroeconomic policies.

scholarly journals LITHUANIAN STOCK MARKET ANALYSIS USING A SET OF GARCH MODELS

2009 ◽  
Vol 10 (4) ◽  
pp. 349-360 ◽  
Author(s):  
Deimantė Teresienė
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Main Idea ◽  
Price Volatility ◽  
Market Analysis ◽  
Garch Models ◽  
Stock Price Volatility ◽  
Stage System ◽  
Main Factor

This article analyses the main factors that influence stock price volatility. The author offers a three‐stage system for explaning a set of stock price volatility factors. The main point is to pay attention to investor's psychology as the main factor of price volatility. For practical analysis the returns of the OMXV index and stock prices of the Lithuanian stock market are taken and applied to a set of GARCH models. The main idea is to choose the best of the general autoregressive conditional heteroskedasticity models (GARCH) for OMXV index and all sectors. All models are ranged according to their ability to model stock price return. The main tendencies of the Lithuanian stock market are also analysed in this article by highlighting the leverage effect.

Macroeconomic Factors and Pakistani Equity Market”

2004 ◽  
Vol 43 (4II) ◽  
pp. 619-637 ◽  
Author(s):  
Muhammad Nishat ◽  
Rozina Shaheen
Keyword(s):  
Stock Market ◽  
Industrial Production ◽  
Stock Prices ◽  
Stock Price ◽  
Consumer Price Index ◽  
Reverse Causality ◽  
Macroeconomic Factors ◽  
Macroeconomic Variables ◽  
Equilibrium Relationships

This paper analyzes long-term equilibrium relationships between a group of macroeconomic variables and the Karachi Stock Exchange Index. The macroeconomic variables are represented by the industrial production index, the consumer price index, M1, and the value of an investment earning the money market rate. We employ a vector error correction model to explore such relationships during 1973:1 to 2004:4. We found that these five variables are cointegrated and two long-term equilibrium relationships exist among these variables. Our results indicated a "causal" relationship between the stock market and the economy. Analysis of our results indicates that industrial production is the largest positive determinant of Pakistani stock prices, while inflation is the largest negative determinant of stock prices in Pakistan. We found that while macroeconomic variables Granger-caused stock price movements, the reverse causality was observed in case of industrial production and stock prices. Furthermore, we found that statistically significant lag lengths between fluctuations in the stock market and changes in the real economy are relatively short.

Znaczenie czynników behawioralnych w podejmowaniu decyzji inwestycyjnych na rynku kapitałowym

2016 ◽  
pp. 173-183
Author(s):  
Mirosław Wasilewski ◽  
Marta Juszczyk
Keyword(s):  
Capital Market ◽  
Stock Prices ◽  
Stock Price ◽  
Investment Decisions ◽  
Price Volatility ◽  
Decision Making Process ◽  
Emotional States ◽  
Psychological Conditions ◽  
History Of ◽  
Research Show

The aim of the study was to investigate the investors’ opinions concerning the usefulness of behavioral factors for investment decisions. The research was carried out in the group of 100 investors, using the services of five brokerages with a long history of operation. The results of the research show that people’s psychological conditions and sentiment in the stock market play an important role in the decision-making process of investors in the capital market. The importance of this factor increased with the length of the investment period. The emotional states of people and their psychological conditions affect the stock price volatility. However, the complexity of the determinants of stock prices makes the market value of stocks can be affected by many factors at the same time and investors seem aware of this.

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.

EVOLUTION OF SHANGHAI STOCK MARKET BASED ON MAXIMAL SPANNING TREES

2012 ◽  
Vol 27 (03) ◽  
pp. 1350022 ◽  
Author(s):  
CHUNXIA YANG ◽  
YING SHEN ◽  
BINGYING XIA
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Spanning Tree ◽  
Stock Price ◽  
Spanning Trees ◽  
Turning Points ◽  
Single Step ◽  
P Value ◽  
Power Law Distribution ◽  
Structure Variation

In this paper, using a moving window to scan through every stock price time series over a period from 2 January 2001 to 11 March 2011 and mutual information to measure the statistical interdependence between stock prices, we construct a corresponding weighted network for 501 Shanghai stocks in every given window. Next, we extract its maximal spanning tree and understand the structure variation of Shanghai stock market by analyzing the average path length, the influence of the center node and the p-value for every maximal spanning tree. A further analysis of the structure properties of maximal spanning trees over different periods of Shanghai stock market is carried out. All the obtained results indicate that the periods around 8 August 2005, 17 October 2007 and 25 December 2008 are turning points of Shanghai stock market, at turning points, the topology structure of the maximal spanning tree changes obviously: the degree of separation between nodes increases; the structure becomes looser; the influence of the center node gets smaller, and the degree distribution of the maximal spanning tree is no longer a power-law distribution. Lastly, we give an analysis of the variations of the single-step and multi-step survival ratios for all maximal spanning trees and find that two stocks are closely bonded and hard to be broken in a short term, on the contrary, no pair of stocks remains closely bonded for a long time.

scholarly journals Disposition Effect and Return Predictability in the Tunisian Stock Market

2017 ◽  
Vol 4 (1) ◽  
pp. 1
Author(s):  
Cheïma Hmida ◽  
Ramzi Boussaidi
Keyword(s):  
Stock Market ◽  
Behavioral Finance ◽  
Stock Prices ◽  
Stock Price ◽  
Return Predictability ◽  
Capital Gains ◽  
Disposition Effect ◽  
Individual Investors ◽  
Long Run ◽  
Return Reversal

The behavioral finance literature has documented that individual investors tend to sell winning stocks more quickly than losing stocks, a phenomenon known as the disposition effect, and that such a behavior has an impact on stock prices. We examined this effect in the Tunisian stock market using the unrealized capital gains/losses of Grinblatt & Han (2005) to measure the disposition effect. We find that the Tunisian investors exhibit a disposition effect in the long-run horizon but not in the short and the intermediate horizons. Moreover, the disposition effect predicts a stock price continuation (momentum) for the whole sample. However this impact varies from an industry to another. It predicts a momentum for “manufacturing” but a return reversal for “financial” and “services”.

scholarly journals Is Abnormally Large Volume a Clue?

2016 ◽  
Vol 8 (9) ◽  
pp. 226
Author(s):  
Tsung-Hsun Lu ◽  
Jun-De Lee
Keyword(s):  
Stock Market ◽  
Large Volume ◽  
Stock Prices ◽  
Stock Price ◽  
Trading Volume ◽  
Sensitive Analysis ◽  
Support Level ◽  
Out Of Sample ◽  
Sample Test ◽  
Abnormal Trading Volume

This paper investigates whether abnormal trading volume provides information about future movements in stock prices. Utilizing data from the Taiwan 50 Index from October 29, 2002 to December 31, 2013, the researchers employ trading volume rather than stock price to test the principles of resistance and support level employed by technical analysis. The empirical results suggest that abnormal trading volume provides profitable information for investors in the Taiwan stock market. An out-of-sample test and a sensitive analysis are conducted for the robustness of the results.

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