Roles of GARCH and ARCH effects on the stability in stock market crash

2021 ◽  
Author(s):  
Hai-Feng Li ◽  
Dun-Zhong Xing ◽  
Qian Huang ◽  
Jiangcheng Li
Keyword(s):  
Stock Market ◽  
Market Price ◽  
Nonequilibrium Dynamics ◽  
Escape Time ◽  
Theoretical Simulation ◽  
Market Stability ◽  
Share Data ◽  
Escape Process ◽  
The Stability ◽  
The Impact

Abstract We theoretically stochastic simulate and empirically analyze the escape process of stock market price nonequilibrium dynamics under the influence of GARCH and ARCH effects, and explore the impact of ARCH and GARCH effects on stock market stability. Based on the nonlinear GARCH model of econophysics, and combined with GARCH and ARCH effects of volatility, we propose a delay stochastic monostable potential model. We use the mean escape time, or mean hitting time, as an indicator for measuring price stability, as first introduced in Ref. [1]. Based on the comparative analysis of actual Chinese A-share data, the theoretical and empirical findings of this paper are as follows} (1) The theoretical simulation results and actual data are consistent. (2) There exist optimal GARCH and ARCH effects maximally enhancing stock market stability.

scholarly journals Factors affecting stock market index volatility: Empirical study

2021 ◽  
Vol 10 (3) ◽  
pp. 169-176
Author(s):  
Mohammed Ali Al-Rimawi ◽  
Thair Adnan Kaddumi
Keyword(s):  
Economic Growth ◽  
Growth Rate ◽  
Interest Rate ◽  
Stock Market ◽  
Foreign Investment ◽  
Inflation Rate ◽  
Market Price ◽  
Economic Growth Rate ◽  
Macroeconomic Variables ◽  
The Impact

How is stock market price volatility affected, and what is the nature of the impact that macroeconomic variables do on the stock market price direction? The main objective of this study is to investigate the impact of some selected macroeconomic variables (inflation rate (INR), interest rate (IR), economic growth rate (EGR), and foreign investment (FI)) on Amman Stock Exchange (ASE) fluctuation for the period 1999–2018. The information is based on the annual data published by industrial companies listed at ASE. The study adopted a descriptive-analytical approach, also simple and multiple linear regression analysis was employed for the mentioned purpose (Nurfadilah & Samidi, 2017). The results revealed that there is no statistically significant impact of INR, IR, EGR, and FI collectively on ASE performance (Niewińska, 2020). Individually, the results indicated that there is a statistically significant impact of all variables (INR, IR, EGR, and FI) on ASE performance. Additionally, the results concluded that foreign investment, portrayed the highest impact factor on ASE performance, followed by a change in average interest rate, then inflation rate, and the least impact attributes to the economic growth rate. Finally, the research recommends that Jordanian banks should reduce the lending interest rate to enhance investment in securities and improve economic growth rate, also Jordanian authorities should encourage foreign direct and indirect investment and make more efforts to attract more foreign investment, either in the form of tax incentives or by extending finance at low-interest rates.

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.

scholarly journals Stock Market Prediction Using Twitter Sentiment Analysis

2021 ◽  
pp. 265-270
Author(s):  
Padmanayana ◽  
Varsha ◽  
Bhavya K
Keyword(s):  
Stock Market ◽  
Sentiment Analysis ◽  
Stock Price ◽  
Market Price ◽  
Future Price ◽  
Stock Market Prediction ◽  
Stock Price Prediction ◽  
Price Prediction ◽  
Media Platform ◽  
The Impact

Stock market prediction is an important topic in ?nancial engineering especially since new techniques and approaches on this matter are gaining value constantly. In this project, we investigate the impact of sentiment expressed through Twitter tweets on stock price prediction. Twitter is the social media platform which provides a free platform for each individual to express their thoughts publicly. Specifically, we fetch the live twitter tweets of the particular company using the API. All the stop words, special characters are extracted from the dataset. The filtered data is used for sentiment analysis using Naïve bayes classifier. Thus, the tweets are classified into positive, negative and neutral tweets. To predict the stock price, the stock dataset is fetched from yahoo finance API. The stock data along with the tweets data are given as input to the machine learning model to obtain the result. XGBoost classifier is used as a model to predict the stock market price. The obtained prediction value is compared with the actual stock market value. The effectiveness of the proposed project on stock price prediction is demonstrated through experiments on several companies like Apple, Amazon, Microsoft using live twitter data and daily stock data. The goal of the project is to use historical stock data in conjunction with sentiment analysis of news headlines and Twitter posts, to predict the future price of a stock of interest. The headlines were obtained by scraping the website, FinViz, while tweets were taken using Tweepy. Both were analyzed using the Vader Sentiment Analyzer.

scholarly journals An Empirical Study of a Mathematical Model for Influence of Government Tax on the Price Behavior and the Stability of Market Price

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Fenglian Wang ◽  
Chia-Huei Wu ◽  
Sang-Bing Tsai ◽  
Yi-Zhang Jiang
Keyword(s):  
Price Competition ◽  
Market Price ◽  
Stable Region ◽  
Price Behavior ◽  
Tax Rate ◽  
System P ◽  
The Government ◽  
The Stability ◽  
Fierce Competition ◽  
The Impact

The fierce competition among enterprises and disordered market price competition have affected the development of the whole regional economy. Government tax subsidies have always been regarded as the advantages of enterprise development, but the mechanism of the influence of government tax on regional economic development, especially the impact on market price, has not been explored. Based on the Bertrand competition, applying chaos control theory, considering the government revenue rate, the influence of government tax on the price behavior and market price stability is analyzed, and then the numerical simulation is carried out. The research shows that the price adjustment of enterprises is a complicated process and government tax is helpful to the stability of market price. The government tax rate increasing can increase the stable region of price equilibrium and reduce the bifurcation and chaos of the price game system.

Impact of Stock Market Volatility on Gold prices during the Covid-19 pandemic

2021 ◽  
Vol 9 (3) ◽  
Author(s):  
Garishma Gulyani ◽  
Priyanka Gupta ◽  
Ramanpreet Singh
Keyword(s):  
Stock Market ◽  
Market Price ◽  
Unit Root Test ◽  
Selection Strategy ◽  
Stock Market Volatility ◽  
Stock Selection ◽  
Causality Test ◽  
Integration Test ◽  
The Impact ◽  
The Relationship

The present research study examines the impact of Stock marketson Gold prices using daily data for pre and during COVID-19 period (January-October 2020). This study uses Unit root test, Granger causality test, GARCH method and Johansen’s co-integration test to evaluate difference in the Volatility as well as the relationship between them. The findings show that no causal relationship exists between Gold Prices and Stock market prices in the short run. The result of the Johansen Co-integration test for the long-run relationship between theGold price and Nifty Indices showno co-integration at all, but low co-integration inshort-run cannot be ruled out. With this study, an attempt has been made to reveal the relationship that exists between Gold and stock markets with empirical findings using the time series analysis which reveals the original side of work during the pandemic. The ARCH and GARCH coefficient explain significantly the persistence of information on stock return volatility. The present study recommends that the integration between Gold and Stock market price entails the need for investors globally to follow a portfolio stock selection strategy to add value from the investments in India.These findings have important implication for the investors seeking portfolio diversification.

scholarly journals Impact of Accounting Ratios on Stock Market Price of Listed companies in Colombo Stock Exchange

2021 ◽  
Author(s):  
Chandrasegaran Larojan
Keyword(s):  
Regression Analysis ◽  
Stock Market ◽  
Stock Exchange ◽  
Pearson Correlation ◽  
Random Effect ◽  
Market Price ◽  
Fixed Effect ◽  
Effect Regression ◽  
The Impact ◽  
Accounting Ratios

This study investigates the impact of accounting ratios on stock market price of top twenty companies based on the highest market capitalization listed in the Colombo Stock Exchange (CSE). The objectives of this study were to examine the impact of Earnings per Share (EPS) on stock market price; to examine the impact of Dividend per Share (DPS) on stock market price, to examine the impact of Price Earnings ratio (PE) on stock market price and to examine the impact of Market to Book ratio (MB) on stock market price. The panel data was collected from the top twenty companies for the period of five years from 2015 to 2019. EPS, DPS, PE and MB ratios were used as the proxies for the independent variables and stock price was used as the proxy for the dependent variable for this study. In order to perform the inferential analysis Pearson correlation analysis, panel regression with fixed effect, random effect and pooled linear regression were used. Hausman test was adopted in order to choose either random effect regression or fixed effect regression. According to pooled regression analysis, EPS, DPS and PE ratios had positive significant impact on stock market price. MB ratio had a negative significant impact on stock market price. According to fixed effect regression analysis, EPS, PE and MB ratios had positive insignificant impact on stock market price whereas DPS had a positive significant impact on stock market price. This study offers an insight to the potential investors to make the rational investment decisions in the stock market.

scholarly journals Effect of Dividend on Stock Market Price: A Panel Data Approach

2020 ◽  
Vol 23 (1) ◽  
pp. 199-208
Author(s):  
Purna Man Shrestha
Keyword(s):  
Panel Data ◽  
Stock Market ◽  
Dividend Policy ◽  
Random Effect ◽  
Random Effect Model ◽  
Market Price ◽  
Lagrangian Multiplier ◽  
Return On Equity ◽  
Effect Model ◽  
The Impact

Dividend policy is major concern for investor, managers and policy makers. Proper dividend policy helps to achieve the wealth maximization goal of the firm. This study has examined the impact of dividend on stock market price of Nepalese enterprises. For this purpose 33 dividend paying companies listed on NEPSE has been selected as sample. Likewise, this study used unbalance panel data for the period of 2000/01 to 2018/19. Breusch and Pagan Lagrangian multiplier test concluded that Pooled regression model is not appropriate and Hausman test concluded that Random Effect model is not appropriate for the data used in this study. Thus, this study adopted Fixed Effect model to analyze the impact of dividend on stock market price. This study concluded that there is significant impact of dividend on stock market price of Nepalese enterprises after controlling return on equity, earnings per share and return on equity. Finally, this study concluded that cash dividend has significant negative and stock dividend has significant positive impact on stock market price of Nepalese enterprises.

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