Financial Stock Market Research Articles

Testing in GARCH‐X models: boundary, correlations and bootstrap theory

In this article, we consider the so‐called Fixed Shrinkage (FS) bootstrap for the class of GARCH models with explanatory variables (GARCH‐X). Under the assumption of stationary covariates, the proposed FS bootstrap does not require modeling the covariates, as these are kept fixed in the bootstrap generating process. Our main focus is on testing whether one or more of the covariates can be excluded in the GARCH‐X model. As is well‐known the limiting distribution of the likelihood‐ratio (LR) statistic in this setting is non‐standard and depends in particular on whether nuisance parameters are on the boundary or in the interior of the parameter space. In particular, and as detailed here, the non‐standard limiting distribution depends on correlations, or dependence, between the explanatory variables. The FS bootstrap takes the presence of nuisance parameters into account by implementing shrinking as proposed in Cavaliere et al. (2022) for pure ARCH models. We establish asymptotic validity of the FS bootstrap for GARCH‐X models, and demonstrate by simulations that the bootstrap‐based test performs extremely well even when nuisance parameters lie on the boundary of the parameter space. The empirical illustration amplifies that the presence of nuisance parameters (especially whether or not on the boundary) are vital for interpreting the dynamics of conditional volatility in financial stock market indices.

Determinants of environmental sustainability in the United States: analyzing the role of financial development and stock market capitalization using LCC framework

This research investigates how the USA's load capacity factor (LCF) has been impacted by trade openness, financial development, stock market capitalization, and industrialization over the period 1990–2022. This study also tests the “Load Capacity Curve (LCC)” hypothesis. Various unit root tests were conducted to determine the stationarity of the dataset, revealing that the variables are free from unit root problems and exhibit mixed orders of integration. The “Autoregressive Distributed Lag (ARDL)” bounds test confirmed co-integration among the variables. The results from the ARDL model validated the existence of the LCC hypothesis in the USA. The findings also demonstrated that industrialization is positively correlated with LCF, whereas financial development, stock market capitalization, and trade openness are negatively correlated with LCF. To ensure the robustness of the ARDL estimations, the study also employed several regressions, all of which confirmed the validity of the ARDL results. Additionally, pairwise Granger causality tests revealed unidirectional causal relationships between GDP and LCF, stock market capitalization and LCF, and industrialization and LCF, while no causal relationships were found between financial development and LCF and trade openness and LCF. The findings advocate that the USA should advance eco-friendly industrial practices to ensure environmental sustainability, alongside regulated financial markets and institutions that mandate the utilization of green investments.

The Mediating Effect Of Market Liquidity On The Relationship Between Financial Liberalization And Stock Market Returns Among East Africa Community Member Countries

The motivation for this study stems from the critical role of financial markets in economic development and the need to understand the factors influencing stock market performance in the East African Community (EAC) member countries. Financial liberalization, market liquidity, and macroeconomic stability are pivotal in shaping stock market returns. However, empirical studies examining these relationships within the EAC context are limited, prompting this comprehensive analysis. The general objective of this study was to investigate the effect of financial liberalization, market liquidity, and macroeconomic factors on stock market returns among EAC member countries. The study was anchored on the theory of financial liberalization, neoclassical theory, efficient market hypothesis, behavioral finance theory, and the general theory of employment, interest, and money. Data were collected from secondary sources, including financial reports, stock exchange databases, and relevant economic databases, covering the period from 2002 to 2021.The study employed fixed-effects regression models, chosen based on the Hausman specification test, to control for unobserved heterogeneity across countries. Baron and Kenny’s approach was used to test for mediation and moderation effects. The analysis involved examining the direct and, mediating relationships between the key variables. The findings revealed that financial liberalization significantly and positively affects stock market returns. Conversely, market liquidity was found to mediate this relationship, enhancing the positive effects of financial liberalization. The study concludes that financial liberalization is a crucial determinant of stock market performance in the EAC region. Market liquidity plays a significant role in amplifying the benefits of financial liberalization. For policymakers, the study recommends policymakers in EAC should focus on developing infrastructure that supports efficient trading systems. This recommendation is based on the finding that higher market liquidity significantly boosts the positive effects of foreign assets and liabilities on stock market returns

The spillover effects among financial stress, investor sentiment, and GCC stock markets: evidence under the bearish and bullish market states

ABSTRACT This study delves into an exploration of volatility spillover between financial stress, investor sentiment, and stock market index returns in the Gulf Cooperation Council (GCC) countries using the DCC-GARCH, wavelet coherence, and BEKK-GARCH models. A robustness check, applying Diebold and Yilmaz’s (2012, 2014) methodology, verifies network measures across markets. Significant patterns in financial stress index were observed during crises, with strong co-movement between financial stress, investor sentiment, and stock returns, especially during COVID-19 pandemic. Volatility transmission from stock returns to investor sentiment and the financial stress index was notable in some markets. Additionally, we found a significant volatility transmission from the financial stress index to market returns during periods of bearish stress in Bahrain and Kuwait and bullish stress across all countries. These findings offer insights for investors and fund managers optimizing portfolios and managing risk exposure.

From text to treasure: the predictive superiority of a FinTech index in stock market returns

This study employs a text analysis methodology to construct a Financial Technology (FinTech) Index, utilizing textual data from The New York Times. The primary aim is to investigate the correlation between financial technology and stock market performance. Our findings provide compelling evidence that the FinTech Index possesses substantial predictive capability for excess returns in the US stock market, a feature that becomes particularly pronounced during economic downturns. Notably, when compared with traditional macroeconomic indicators, the FinTech Index offers valuable incremental insights. Moreover, this study expands to include sector-level and international market analyses, demonstrating the broad applicability and robust performance of the FinTech Index. Importantly, through the use of out-of-sample testing, we substantiate that the FinTech Index demonstrates superior predictive accuracy, presenting opportunities for investors to achieve higher economic returns.

Financial Risk Tolerance as a Mediator Between Financial Literacy and Stock Market Participation: Evidence From Single Men and Women

Anchored upon the theory of planned behavior, the study examines a mediator, financial risk tolerance, in the relationship between financial literacy and stock market participation among single men and women. Using data from the 2019 Survey of Consumer Finances, the study uncovers an indirect effect of financial literacy on stock market participation through the mediating role of financial risk tolerance. This effect is observed in both genders, with a more pronounced mediation effect for men than for women. The study suggests that this gender disparity in the mediating mechanism is driven by the stronger correlation between financial risk tolerance and stock market participation among men, as the study finds that men exhibit a higher propensity to invest in the stock market when their financial risk tolerance increases compared with women. Consequently, the study asserts that addressing the gender gap in stock market participation may hinge on empowering women to transform their financial risk tolerance into concrete investment actions.

Systemic risk-sharing between natural gas, oil, and stock markets in top energy producer and consumer countries

This study investigates the dependence and risk spillovers in the short-, medium- and long-terms between natural gas (NG), crude oil and stock markets of top energy producer countries (Russia, Ukraine, and US) and consumer countries (China, India, and EU members). Using the wavelet coherence approach, the results show a long-term dependence between NG and all stock markets between 2006 and 2022. Low and intermediate frequency co-movements of oil with stock markets are more pronounced among top energy producers than top energy consumers (except the EU). Further, there is heterogeneous dependence between stock markets and both NG and oil. Moreover, the dependence is positive and high for oil, and negative for NG, irrespective of the time horizon. NG is a hedge asset in the short-, medium- and long-terms for investors in top energy producer and consumer countries. Oil is a diversifier asset in the long term and a weak hedge asset in both short- and long-terms. We find evidence of significant bidirectional and asymmetric spillovers of NG, oil, and stock markets. The upside and downside risk spillovers for both NG and oil are higher in the long term than in the short- and medium-terms. NG sends more risk to stock markets than oil does in the long term, particularly in Russia. Our findings have significant implications for financial risk assessments and stock market stability.

Relationship Between Financial Deepening Indicators and Stock Market Performance in Kenya

The purpose of this study was to find out the relationship between financial deepening indicators and the stock market performance in Kenya. The selected financial deepening indicators were; financial savings, private sector credit, broad money supply and intermediation ratio on the stock market performance. Johansen cointegration test was done indicating that the variables co-move towards a long-run equilibrium, a multivariate vector error correction model was run and the estimates obtained. The error correction term was also computed. Empirical results showed that all variables are adequately explained by their own lags and the lags of the other variables, the coefficients are also significant. The error correction model indicated that an increase in private sector credit by one unit in the previous quarter causes the stock market performance to increase by 48% in the current quarter. Variance decomposition tests and impulse response functions indicated how other variables respond to shocks in the other variables and the forecast errors for each of the predicted quarters. The implication of this study is that the policy makers who are; the Government, the Central bank of Kenya and the Capital Markets Authority ought to make policy decisions while considering the effect of the full market. This study concluded that private sector credit is the financial indicator variable that affects the stock market performance the most with a bidirectional relationship.

Stock Returns and Volatility Cross-Spillover Effect Between Sri Lanka And Asian Stock Markets

Sri Lanka holds a pivotal position in the Indian Ocean, fostering significant economic ties with South Asia, the Middle East, and Africa. This study examines the financial linkages and stock market behavior between Sri Lanka and key Asian economies (India, China, Pakistan, and Japan) from 2015 to 2021. Using daily stock prices from Bloomberg.com, the analysis employs the EGARCH (1,1) model to assess return and volatility spillovers. Results reveal negative return spillovers from India to Sri Lanka and cross-volatility spillovers from India, China, Pakistan, and Japan to Sri Lanka. Conversely, Sri Lanka exhibits negative return spillovers to India and Pakistan and cross-volatility spillovers to China and Japan. Sub-analysis identifies structural breaks in December 2019, indicating shifts in spillover dynamics pre- and post-Covid-19. These findings offer insights for investors, policymakers, fund managers, and governments to optimize investment strategies, formulate stable policies, and enhance portfolio diversification.

The mediating effect of trust on financial development and stock market comovement in BRICS economies

This study examines the effects of financial development on the stock market comovement of Brazil, Russia, India, China and South Africa (BRICS) on the one hand and the US Dow Jones on the other. Its main goal is to find out if trust has a mediating effect on financial development using data from the World Bank and the World Value Survey (WVS). Panel data analysis along with ARDL methods helped the authors obtain robust results. It was found that financial development plays a significant role in determining stock market comovement among the countries in question and that trust also has a moderating impact. The analysis was extended to the institutional and market factors of financial development. The paper introduces trust as a mediating variable that positively affects financial development, which in turn promotes stock market integration and comovement. Its results imply that investors should consider financial development and trust levels of a country when considering portfolio allocation for global diversification purposes, especially in emerging markets. Countries with insufficient trust levels, like Brazil, could benefit from improving their trust score through enhancing financial development and stability.

Modelling (A)symmetric Nexus Between Macroeconomic Information Sentiment Biases and Stock Market Returns in Case of India: A Bound Test Approach

This research attempts to scrutinise the asymmetric nexus of macroeconomic factors in determining the financial stock market performance using index returns of BSE-SENSEX and NSE-NIFTY as proxies for stock market performance in India. The auto-regressive distributed lag (ARDL) results demonstrate the long-term nexus of money supply, interest rates, gold prices, inflation, exchange rate, oil prices and foreign institutional investment (FII) in the capital market with stock returns. The non-linear ARDL (NARDL) results unequivocally support that the selected macroeconomic factors have an asymmetric nexus with the stock market performance. The study’s empirical findings have significant consequences for policy in designing the asset allocation decisions by the investor, portfolio managers and policymakers in the circumstances of a sudden positive or negative shock in the stock market. JEL Codes: E44, G10, C58

Does Volatility Spillover among Sectors Varies from Normal to Turbulent Periods? Evidence from Pakistan Stock Exchange

This study investigates how six financial market performances are affected by spillover volatility sectors in both during and following the 2007 financial crisis in Pakistan. By offering a wealth of material to fill in the gaps during the 2007 pre- and post-financial crisis timeframe, this study adds to the body of current knowledge. The pre-crisis era, which ran from January 1, 2003, to December 31, 2007, was used for the analysis on the Pakistani sectors. The period from January 1, 2008, to December 31, 2015, was known as the post-crisis era. The Pakistan Stock Exchange and other sources provided the data, which was routinely gathered. An ARCH, GARCH & EGARCH model is used to investigate the asymmetric volatility spillover among the six industries. The results provide compelling evidence for the existence of a spillover impact in Pakistani businesses in the years after the crisis. Furthermore, there is a significant transmission of volatility throughout Pakistan's many industries during the financial crisis. Overall, the results provide insight into the varying degrees of integration between sectors in Pakistan, ranging from stable to volatile eras. The results indicate that no significant vulnerability was detected. Additional elements can be included and the timing of data can be adjusted. In this study, data is currently gathered monthly. However, in the future, data might be collected on a daily, weekly, or yearly basis to enhance the reliability of the data and its corresponding conclusions. This study expands the existing body of research on volatility and spillover effects in several industries of Pakistan. This research is an innovative study being conducted in six market sectors. The primary impetus for conducting this inquiry is the financial catastrophe in the United States, which has had repercussions on global markets as a whole. Moreover, this time frame is also utilized to inspect the correlation in between financial crises and stock market returns in Asian emerging markets.

Does financial stability communication affect financial asset prices? Evidence from the Bank of England's communication experiment

AbstractThis paper examines the Bank of England's (BoE) communication on financial stability between 2013 and 2018. We apply an event study to determine the communication effect on financial institutions' stock market returns. We find that the BoE's announcements generate negative average abnormal returns for non‐banking and banking systems, including the Global Systemically Important Banks. The same effect emerges when we consider the communication's tone. Furthermore, we construct a macroprudential decision communication index and show that the negative impact of the BoE's tone is significant only when the decision communication index value is above average. Moreover, we find evidence that negative abnormal returns tend to appear after the Brexit referendum, while we find positive abnormal returns before that date. Besides, we do not identify a noticeable effect related to communication practices.

The Effect of Dividend Policy, Capital Structure, and Exchange Rate on Stock Returns in Industrial Sector Business Entities

The purpose of this study is to examine how Dividend Income, Capital Structure, and Exchange Rate affect Stock Market Performance. The sample consisted of 12 companies trading on the Indonesia Stock Exchange (IDX) selected using the Purposive Sampling method, resulting in 63 observations for each variable. Data from audited financial statements, tax reports, and stock market prices are published by Bursa Indonesia (IDX). Data analysis was performed using regression analysis techniques. The results of this study show that the Exchange Rate, Dividend Payout Ratio (DPR), and Debt to Equity ratio (DER) all have a significant impact on stock prices. Individually, the Exchange Rate and DER have significant effects, with the Exchange Rate having a negative effect and DER having a positive effect, but the DPR having no significant effect. The coefficient of determination shows that 10.8% of the stock price variation can be explained by the three variables studied, while 89.2% can be explained by other factors not included in the study.

Impacts of inflation on the Vietnamese stock market in economic turbulence

This study employs the GARCH model to examine how inflation affects the Vietnamese stock market. The analysis uses 2001-2022 data from the General Statistics Office and the Ho Chi Minh Stock Exchange (HoSE). This time frame encompasses various market cycles, including the recent financial crises, which alter the characteristics of stock variance. The findings reveal that inflation has a strong impact on the volatility of stock indexes because the psychological herd of the stock players has a huge impact on market volatility such that it weakens the market, leading to instability due to stock prices being blown up too high or depressed too low. Herd mentality facilitates price manipulation, stock price manipulation, and speculation. When the demand for capital flows into the secondary market, a surge has led to a large amount of money in circulation. This has caused a high level of inflation. The findings indicate that a one percent increase in inflation is associated with a 6.692 percent increase in the VN index, suggesting that Vietnam’s stock market returns can hedge against inflation. Yet, the popularity of speculative investments necessitates that the Vietnamese government not only address inflation but also improve financial regulations and stock market oversight.

Machine Learning based Financial Stock Market Trading Strategies with Moving Average, Stochastic Relative Strength Index and Price Volume Actions for Indian and Malaysian Stock Market

The study related to a new and very powerful stock, index and commodities trading strategy based on machine learning with Moving Average (MA), Stochastic Relative Strength Index (SRSI) and Price Volume (PV) analysis to generate three types of financial market or stock trading signals such as buy, sell and no trade. Moving averages and moving average crossover are widely used to smooth price data and identify trends, whereas Stochastic RSI is a powerful oscillator that measures the relative strength of recent stock prices. Combination of multiple indicators in machine learning can improve strategies and provide more accurate decision for investors and traders which generate financial worth. This model is very much useful for Indian and Islamic stock markets.

Complex Systems in Interdisciplinary Interaction

Complex systems consist of many components that interact with each other, and nonlinearity is fundamental in the dynamics that arise as a result of the interaction of these components and cannot be studied by observing only a small part of the system. A large number of them make fluctuations an integral part of their dynamics. Through interdisciplinary research, we integrate different disciplines and methodological approaches. We study complexity from different angles through topics that include neuroscience, artificial intelligence, and quantum physics. We have sought to explore these topics that have gained progressive interest in scientific circles as well as outside academic circles, influencing many areas outside academic research. Two goals connect our research. First, theoretical insights from neuroscience, artificial intelligence and quantum physics of the financial stock market. “Financial stock markets are sophisticated machines intertwined with scientific networks” (Ana Negovanović, 2024). They are the core of a system of different blocks that interact on the financial market in an interdisciplinary interaction of the most complex structures, neural networks with interconnected nodes. Second, new technologies- convergence of technologies, new industries, space industry through chaos theory. Investigating the attributes of complex systems is structure. Systems are structured in such a way that some parts of the system are specialized, and systems can naturally be divided into different levels of organization, which should be modeled at different levels of detail. An important component of systems understanding is the ability to break down a system model into its component parts and levels to see how the parts behave and how to connect the parts and levels to understand the overall dynamics and structure of the system. Perhaps one of the most transparent examples of the importance of structure in thinking about complex systems is the space program, where one must equally consider the behavior of individual components and the dynamics of how those components interact with each other.

Financial Crisis Prediction and Stock Market Analysis: A Systematic Review

Abstract: It is common known that attempting to foresee the movements of the stock market is a huge task that calls for a great lot of focus and concentration. Because of this, precisely predicting stock prices might potentially result in attractive rewards if the necessary decisions are made. This is the reason why this is the case. The non-stationary, noisy, and chaotic data that is accessible makes it difficult to generate correct forecasts about the stock market. This is because accurate predictions are difficult to produce. Because of this, it is difficult for investors to generate accurate forecasts in order to invest their money and earn a return from their investments. Various strategies are developed within the framework of the existing methodologies in order to forecast stock market movements. An overview of research articles arguing for different approaches is the goal of this study. In addition to being great academic publications, these research articles provide calculation methodologies, machine learning algorithms, performance factors, and other information. To address this recognized need, this study attempts to provide a comprehensive and current evaluation of the stock market forecasting approaches now in use. This research will include the categorization, analysis, and comparison of various approaches. In the end, the process of training and testing the model is evaluated using machine learning models. Based on the data, it is abundantly evident that logistic regression is better than any other approach that is presently being used.

The adaptive markets hypothesis: Insights into small stock market efficiency

ABSTRACT In this paper, we explore whether the adaptive markets hypothesis (AMH) describes the efficiency of the Finnish stock market better than the efficient markets hypothesis (EMH) does. Building on this, we also test how small market size and market liberalization impact the efficiency of the Finnish stock market and examine the relationship between market volatility and return in this market. We conduct this study by applying the subsample analysis and the rolling window analysis to the daily returns of the OMXH25 index and by measuring the efficiency through three linear and two nonlinear predictability tests. The results of our study strongly support the AMH. They also suggest that small market size alone does not make a market less efficient; opening a market to foreign investors improves its efficiency after a delay; and the correlation between market volatility and return varies over time in the Finnish stock market, being usually negative. These findings mostly contradict the traditional investment paradigm.

Determinants of Financial Literacy and its Effect on Stock Market Participation among University Students in Ghana

The study examined determinants of financial literacy and stock market participation in Ghana. The study also examined the relationship between financial literacy and stock market participation among university students in Ghana. The study involved surveying 400 University of Ghana students to assess their level of financial literacy, stock market participation, and explore potential influencing factors. The study analysed data using ANOVA and multiple regression analysis. The findings of the study revealed that students exhibited limited knowledge in various financial literacy areas, including interest compounding, time value of money, inflation, money illusion, stocks, bonds, mutual funds, and investment risk diversification. Moreover, the study identified male, older, postgraduate students, and those with more working experience as comparatively more financially literate and active participants in stock market activities. Additionally, a positive relationship between financial literacy and stock market participation in Ghana was established. Other determinants of stock market participation included age, gender, course of study, and income levels. Based on these findings, it is recommended that the Ministry of Education implement significant initiatives to enhance financial literacy education among tertiary students. Furthermore, financial institutions should increase advertising efforts to promote awareness about various financial products.