Science topic
Stock Markets - Science topic
All about the market economics of booms and busts, bubbles, crashes, investment and returns.
Publications related to Stock Markets (10,000)
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This study will examine the determinants of income among individuals with Cerebral Palsy (CP) in India, as well as the implications for income tax. People with cerebral palsy may have limitations in their economic and social opportunities, which can be impacted by factors such as age, gender, type of cerebral palsy, education level, social status,...
This study examines the directional return predictability between the technology sector of U.S. stock market and three major cryptocurrencies (Bitcoin, Ethereum, and Dogecoin). Using daily data from August 7, 2015, to February 8, 2024, and the cross-quantilogram approach in both static and dynamic settings, the results reveal significant positive p...
This paper presents a new forecasting approach using the Pelican Optimized Extreme Learning Machine (PO-ELM) model, designed to enhance the prediction of future trends based on historical data. The PO-ELM model refines the ELM by introducing the pelican optimizer, which systematically identifies the decision parameters of the ELM like input weights...
This study explores the intersection of modern financial systems and traditional cultural practices through cross-cultural time series analysis, focusing on the linkage between global stock market fluctuations and the economic behaviors of the Tharu people of Nepal. In recent years, global financial markets have exhibited increasing volatility, pro...
In this article, we study the stochastic structure of cryptocurrency rates of returns as compared to stock returns by focusing on the associated cross-sectional distributions. We build two datasets. The first comprises forty-six major cryptocurrencies, and the second includes all the companies listed in the S&P 500. We collect individual data from...
This paper provides a new analysis for optimal consumption and investment policies with stochastic income. Our analysis gives some kind of procedure for solving the Bellman equation with the dimension reduction scheme developed. In particular, we provide an interpretation of the reduced problem based on the probabilistic approach. The value functio...
Recent literature documents that the well-documented salience theory (ST) effect can be largely explained by the short-term return reversal in the stock market of U.S. and around the globe (Cakici and Zaremba (2022)). Our study extends the tests of ST into the commodity futures markets which contain no effect of short-term reversal. In contrast to...
The current study aims to examine the influence of overreaction on the decision-making processes of investors. Also, this study investigates how herding and overconfidence serially mediate the connection between overreaction and investors’ decision-making. This study used a survey method to collect data using a structured questionnaire from 426 ind...
This study presents a new method for predicting stock prices on the Indonesia Stock Exchange (IDX) using a hybrid deep learning model. The proposed model combines historical price data, consisting of open, high, low, and close values, with technical indicators such as Moving Average (MA), Simple Moving Average (SMA), and Exponential Moving Average...
An approximate computationally feasible algorithm for solving the multi – period financial portfolio optimisation problem with transaction costs (final - essentially). Financial markets run the global economy - not governments (ref. Open U, Understanding Business Behaviour: Business Economics (2002)). WHAT IS AT STAKE IS, ESSENTIALLY, THE OPTIMAL U...
The purpose of this study is to investigate the responses of sector economic activity of the Japanese stock market to Economic Policy Uncertainty (EPU). To investigate this relationship, we take monthly data covering ten sectors of Japan’s economy and the EPU index spanning from January 2000 to January 2024. For the empirical analysis, we used a re...
The purpose of this study is to investigate the responses of sector economic activity of the Japanese stock market to Economic Policy Uncertainty (EPU). To investigate this relationship, we take monthly data covering ten sectors of Japan's economy and the EPU index spanning from January 2000 to January 2024. For the empirical analysis , we used a r...
The study examines the effect of firm’s specific dimensions on market share price of listed financial service firms in Nigeria. The study adopts correlation quasi-experimental research design. The population of the study was made up of the entire listed financial service firms in Nigeria which stands at 56 as at 31st December 2022. This includes de...
In financial networks, information does not always follow the shortest path between two nodes but may also take alternate routes. Communicability, a network measure, resolves this complexity and, in diffusion-like processes, provides a reliable measure of the ease with which information flows between nodes. As a result, communicability appears to b...
This paper evaluates the applicability of the Fama-French three-factor model in optimizing portfolio construction and maximizing returns, using historical stock data from various industries over the period from 2002 to 2022. The analysis is divided into two distinct sub-periods, 2002-2012 and 2013-2022, to assess the model’s performance across diff...
A steady increase in the stock market price reflects the maximization of corporate value. The Price to Book Value ratio serves as a metric for assessing the growth in a company's value. Profitability and leverage policies are just two of the several aspects that influence the company's overall value. This study aims to evaluate the impact of financ...
Candlestick patterns are widely recognized as tools for predicting price movements, gaining popularity in the stock market. However, their applicability in the FOREX market, which operates continuously 24 hours daily, remains uncertain. This study assesses the accuracy of widely known candlestick patterns, particularly Doji patterns, in the FOREX m...
Against the backdrop of funds flowing from the real economy to the virtual economy, the trend of corporate financialization is becoming more and more obvious. Establishing how to guide enterprises to return to their main business is the key to guaranteeing the sustainable development of the economy. Considering the promulgation of new accounting st...
This article aims to provide a comparative analysis of the capital structure of large companies in the manufacturing sector of Colombia and Ecuador regarding company size, guarantees or tangibility, cost of debt, growth opportunities, reputation, and liquidity as determinant variables. Based on a sample of 509 manufacturing companies in Colombia an...
Investors base their decisions on a variety of factors, including the price-
earnings ratio, the consumer price index, and various news stories. A lot of research has gone
into automating the evaluation of such sources of information over the last many decades so that
they can help them make quick decisions. Most of the attempts centered on numeric...
The research aims to know the role that computerized accounting systems play in reducing financial risks according to the COSO framework. As this was achieved by analyzing spending on computerized accounting tools such as electronic devices and information networks, as well as conducting an analysis to measure financial risks according to the matri...
Plain language summary
Study of risk factors in global stock markets during the COVID-19 pandemic under different market conditions
Purpose: This study investigates how international risk factors affected stock markets during the COVID19 pandemic. It examines whether these effects varied depending on whether the market was performing well (bullish)...
Academics have recently prioritized studying the stock market due to its
fundamental nonlinearity. A stock market investment is based on speculation. In order to
predict the value of stocks, people seek out methods and tools that will allow them to make
the most money with the least amount of risk. Model training, feature selection, and pre-
proces...
Triggered by the COVID-19 crisis, one of the most severe stock market crashes in history arose in March 2020. In this study, to analyze the dynamic efficiency before and after the crash, the returns of NASDAQ insurance stock markets are utilized. The significant fluctuation clustering phenomenon is presented in the studied series during the March 2...
Purpose-The study aims to investigate the persistence of seasonal anomalies during religious holidays in emerging markets. Design/methodology/approach-The authors select the Bombay Stock Exchange and National Stock Exchange stock returns from January 1990 to December 2022. The GARCH family models were adopted to examine the mean-variance returns as...
With the volatile and complex nature of financial data influenced by external factors, forecasting the stock market is challenging. Traditional models such as ARIMA and GARCH perform well with linear data but struggle with non-linear dependencies. Machine learning and deep learning models, particularly Long Short-Term Memory (LSTM) networks, addres...
Stock market is pivotal to economical systems. It is a platform where listed stocks of companies can be bought/sold by market participants to gain profit. In 2020, the total capitalization of all markets reached $95 trillion. Within such profiting platforms, malicious attacks like stock price/market manipulation are conducted. Stock price manipulat...
This paper proposes an innovative Multi-Modal Transformer framework (MMF-Trans) designed to significantly improve the prediction accuracy of the Chinese stock market by integrating multi-source heterogeneous information including macroeconomy, micro-market, financial text, and event knowledge. The framework consists of four core modules: (1) A four...
This study examines volatility spillover across sectoral stock indices in India, an emerging market economy, during the COVID-19 pandemic. Our research makes three key contributions: (a) incorporating range volatility measures to capture the pandemic's impact on stock market volatility, (b) providing a comparative assessment of volatility spillover...
This paper presents a structured literature review of AI agents in financial applications, focusing on their implementation frameworks, model architectures, and future directions. The review categorizes AI agents into five key domains: financial risk management, investment strategies, fraud detection, stock market analysis, and customer support. By...
The aim of this paper was to investigated the effect of monetary policy uncertainty on stock market uncertainty in Iran. In this paper, the positive and negative shocks of monetary policy uncertainty were calculated using nonlinear autoregressive distributed lag (NARDL) approach. The annual data of Iran's economy over the period 2000-2022 were used...
A multitude of factors exert influence on stock prices. In this era of globalized capital markets, characterized by the absence of borders and the interpenetration of economies, development and globalization have emerged as pivotal elements in shaping stock prices and financial returns. Noteworthy is the decision made in 1980 in Turkey, wherein pol...
This study examines whether stock price sensitivity to illiquidity shocks changes over time in the Saudi stock market. Using structural break analysis, the research identifies shifts in the sensitivity of stock prices to illiquidity. A Markov switching model is then applied to understand these changes. The results indicate that small firms experien...
In this work we analyze the correlation structure of the Spanish stock market around COVID-19 using random matrix theory (RMT). The results reveal that the empirical spectral distribution of eigenvalues associated with correlation matrices of prices for major companies listed on IBEX35 and IBEXC differs across the analyzed periods. In all cases, it...
The objective of this paper is to examine the structure as well as the performance of different investment strategies using two asset classes (stocks and commodities) and different portfolio methods. More specifically, we construct different portfolios using three diversification strategies—the traditional minimum-variance portfolio strategy, the m...
This study investigates the multifractal properties of daily returns of the Standard and Poor’s 500 Index (SPX), the Dow Jones Industrial Average (DJI), and the Nasdaq Composite Index (IXIC), the three main indices representing the U.S. stock market, from 1 January 2005 to 1 November 2024. The multifractal detrended fluctuation analysis (MF-DFA) me...
Our proposal is basically a methodological one; the central objective is to propose a unique qualitative experimental protocol in the field of behavioral finance. More specifically, the aim is to understand the behavior of individual investors in stock markets. We believe that this approach offers real added value on two levels. Firstly, although b...
Low household risk market participation has been a problem for a long time in China, this study explores the issue of Chinese household asset allocation from the perspective of mobile payment. Based on China Household Finance Survey data in 2017, this research studies the impact of mobile payment on Chinese household stock market participation and...
Are green patents granted to family firms perceived more favorably by the market than those granted to non-family firms? Using a sample of 8918 green patents granted to family and non-family firms between 2014 and 2018, our study shows that it depends on the attributes of the green patent. Integrating the green innovation and family firm literature...
Purpose: This study explores the impact of market institutions on Ukraine's national security and competitiveness. Specifically, it presents the role of the stock market and banking sector in shaping economic stability and defense capabilities. Methodology/approach: Drawing on insights from institutional economics, this research employs a comparati...
Climate change has heightened the need to understand physical climate risks, such as the increasing frequency and severity of heat waves, for informed financial decision-making. This study investigates the financial implications of extreme heat waves on stock returns in Europe and the United States. Accordingly, the study combines meteorological an...
The use of deep learning, specifically time series neural networks, in predicting stock market trends has emerged as a significant use case in financial analysis. However, the complex interrelationships and instability of the stock market have made the timely and accurate prediction of its behaviour as a confronting endeavour. To address this diffi...
We examine how local media influences trading activity in local stocks by separating the effects of national news from local news and local printed press news from local web page news. Our results show that information provided by local web pages induces investors to become net buyers. The results are particularly strong in rural districts known as...
В данной статье приводятся результаты оценки стоимости публичных акционерных обществ сырьевого сектора на основе финансовой отчетности с января 2019 года по декабрь 2022 года. Актуальность работы обусловлена резким изменением экономической ситуации с момента начала специальной военной операции, вызванного беспрецедентным усилением санкционного давл...
This study aims to identify stock price jumps and examine stock returns dynamics in emerging Asian stock markets. Additionally, the study employs the Swap Variance estimation approach to measure integrated volatility and determine monthly jumps. Specifically, three diverse approaches are used to identify monthly integrated volatility: realized vola...
Accurately predicting stock price trends is of critical importance in the financial sector, enabling both individuals and enterprises to make informed and profitable decisions. In recent years, researchers have employed a variety’ of techniques to forecast stock market trends, yet the challenge of improving accuracy remains. This research introduce...
Citation: Akgüller, Ö.; Balcı, M. A.; Batrancea, L. M.; Gaban, L. Fractional Abstract: This study addresses the challenge of capturing both short-run volatility and long-run dependencies in global stock markets by introducing fractional transfer entropy (FTE), a new framework that embeds fractional calculus into transfer entropy. FTE allows analyst...
This study examines the relationship between Cultural Tightness-Looseness (CTL) and stock market integration, focusing on a sample of 36 markets from 2004 to 2022. The analysis demonstrates that “loose” cultures, characterized by greater social flexibility, exhibit higher levels of financial integration with the global market. This relationship rem...
While there is a large body of literature on oil uncertainty-equity prices and/or returns nexus, an associated important question of how oil market uncertainty affects stock market bubbles remains unanswered. In this paper, we first use the Multi-Scale Log-Periodic Power Law Singularity Confidence Indicator (MS-LPPLS-CI) approach to detect both pos...
Financial institutions, together with stock markets, actively promote financial development in economies worldwide, which has significantly boosted the economic growth of some countries. By applying cointegration techniques, this study analyzes the long-term relevance between economic growth, financial development, human capital, globalization and...
The technology sector, which makes significant contributions to the economy of countries, has the ability to provide high added value. When we look at the distinction between developed and developing countries in the world, we see that the technology sector is at the forefront. Especially when we look at the distinction between developed and develo...
European stock markets are a complex and dynamic terrain, requiring sophisticated methods of analysis to understand their degree of interconnectedness and integration. The paper investigates the financial integration of European Union (EU) financial markets using a dynamic Principal Component Analysis (PCA) approach. By calculating the Financial In...
This article categorizes climate risk into transition risk and physical risk. We developed the climate transition risk index and climate physical risk index through manual collection of textual data, and employed high-frequency data and the TVP-VAR-DY model to assess risk spillover in the Chinese stock market. Subsequently, the causal forest method...
This pragmatic study aims to comprehensively examine the underlying impact of economic policy uncertainty (EPU) on both inflation and stock market performance across fifteen major global economies, employing the robust panel Autoregressive Distributed Lag (ARDL) model. The outcome reveals that there is a long-run nexus between the EPU, inflation, a...
This study assessed the connectedness between oil shocks and industry stock indexes in the United States (US). We consider the normal and extreme conditions across different frequency horizons, and the quantile time–frequency connectedness method is used to determine the tail risk contagion under different frequency horizons. Our results reveal tha...
"Artificial Neural Network" is known as one of the most advanced "Bankruptcy Prediction Models". Based on this research paper، the main structure of three - and four - layer Perceptron models for bankruptcy prediction had led to same models; however، three-layer network has benefited from more predictive power than four - layer network. In comparis...
Environmental, social, and governance (ESG) indicators and reports are becoming one of the crucial reports of businesses, particularly for listed companies. In the world, ESG is a new concept concerned with how to achieve sustainable development in enterprises in terms of environment, society, and corporate governance (Jin & Lei, 2023). In Vietnam,...
This paper explores the impact of Environmental, Social, and Governance (ESG) related news sentiment and investors' sentiment (IS) on forecasting stock prices by applying machine learning (ML). X (formerly Twitter) data is used to analyze IS using Natural Language Processing (NLP). While ESG sentiment is sourced from the Amenity Analytics dataset,...
The stock market can significantly reflect the cascading propagation relationships between enterprises related to financial events. To explore this cascading propagation relationship, this paper adopts complex network dynamics and network topology analysis to examine the propagation of stock price pre-increase event and the influencing mechanisms o...
Social inclusion is essential to inclusive development but is less explored in relation to financial behavior, especially stock market participation. This study aims to develop and validate a social inclusion scale specific to stock market participation. The study used literature review, expert insights, and focus groups to identify social inclusio...
The evidence of financial globalization and the rapid and uniform contagion that it entails among the different international financial markets, have been exposed after the 2008 crisis outbreak, as well as the different chapters of financial stress that have been experienced since then, such as the sovereign debt crisis, the Brexit event, the COVID...
Security market valuations and their fundamentals, such as company earnings, are of the interest of not only investors, but also company finance managers, as well as central banks due to their focus on financial stability. Identification of the key financial ratios, which can predict stock market valuation levels is of crucial importance. In this s...
This study aims to develop a dynamic portfolio model based on asset class, precious metals, world oil, and dollar index. This study performs a comparative test between the Dynamics Conditional Correlation (DCC) and Asymmetric Dynamics Conditional Correlation (ADCC) to determine the best method in forming a dynamic portfolio. Four big cap companies...