Stock Market Calendar Anomalies: Evidence from ASEAN-5 Stock Markets

To challenge the appropriateness of the theory of the weak-form market efficiency, this study examines the day-of-the-week effect and the twist-of-the-Monday effect for the ASEAN – 5 stock markets for the period June 10, 2002 through August 21, 2009. Our Kruskal-Wallis statistic test finds support for the day-of-the-week effect in Malaysia and Thailand stock markets. In addition, the Wilcoxon Rank Sum Test shows that Monday has significantly lower returns compared to Thursday and Friday returns in Malaysian stock market. On the other hand, Friday has the highest returns in a week and this is significantly different compared with other days in Thailand stock market. This study also found evidence on the twist-of-the-Monday effect, where returns on Mondays are influenced by the previous week's returns in Indonesia, Malaysia and the Philippines stock markets.Calendar Anomalies, Day-of-the-week, Twist-of-the-Monday, Non-parametric test

The Russian default and the contagion to Brazil.

This paper investigates the contagion from Russia to Brazil in late 1998 under two dimensions players involved and the timing of events. The data does not seem to reflect a compensatory liquidation of assets story by international institutional investors. It does contribute, however, to the suspicion that the contagion was triggered by foreign investors panicking from the Russian crisis, and joining local residents on their speculation against the Brazilian real. Adjusted correlations in the Brady market increase significantly during the crisis, which lends support to the view that if there was a contagion from Russia to Brazil, the most likely place of the transmission was the off-shore Brady market. Finally, the paper does not support the hypothesis that it was the liquidity crisis in mature markets, and not the Russian crisis, that timed the crisis in Brazil.

Private Equity Investment in the BRICs

This Article investigates the legal and economic environment for private equity investments in Brazil, Russia, India and China (“BRIC”). In contrast with disappointing returns in the 1990s, private equity investment has soared in developing countries over the past decade. To explain what has led to the recent success of private equity in the BRICs, this Article will first give an overview of the challenges faced generally when investing in portfolio companies in developing markets and then analyze the legal and economic framework for each of the four BRICs. This Article finds that Brazil and China offer the best opportunities for private equity because investors can rely on strong domestic capital markets for the exit. While India is not far behind, Russia still has room for improvement, particularly with regard to the reliability of its legal system and the attractiveness of its capital markets

Textual analysis in finance

Tese (doutorado)—Universidade de Brasília, Departamento de Economia, Brasília, 2019.Esta tese é composta por três estudos que têm como objetivo estudar o impacto da mídia escrita no mercado acionário. No primeiro estudo, fazemos uma pesquisa acerca dos trabalhos que utilizam análise textual para quantificar variáveis econômicas e resumimos os principais resultados dos estudos que investigam seu impacto no mercado acionário. Como o uso de textos como dados em pesquisas científicas é um campo que está em crescimento, este estudo tem como objetivo sintetizar os principais resultados para delinear onde está a fronteira do conhecimento na literatura de finanças. Os dois estudos restantes investigam a relação entre duas variáveis estimadas a partir de notícias e o mercado acionário brasileiro. Assim, no segundo estudo que compõe esta tese estudamos o impacto da incerteza econômica nos retornos acionários semanais. Neste estudo, propomos um novo método para estimar incerteza econômica a partir de notícias usando vetores de palavras para representar o vocabulário. Encontramos um efeito significativo da nossa medida de incerteza econômica na precificação das aç ões e mostramos que medidas de incerteza propostas na literatura mensuradas a partir de notícias geram um efeito similar. No terceiro estudo, estimamos corrupção a partir de notícias e analisamos sua relação com o desempenho de ações de duas empresas que estiveram envolvidas em escândalos de corrupção nos últimos anos. Este estudo tem como objetivo quantificar o custo da corrupção para essas empresas. O impacto da corrupção abordada nas notícias nos retornos acionários divergem entre as empresas. No caso em que a empresa possui controle privado, a corrupção nas notícias impactam negativamente os retornos acionários. Para o caso em que a empresa possui controle estatal, o efeito é insignificante. Encontramos, ainda, um efeito de longo prazo dos escândalos de corrupção nos preços das ações.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES).This thesis is composed of three studies that aim to investigate the impact of written media on stock performance. In the first study, we make a survey of the literature that uses textual analysis to quantify economic variables and review the main results of the studies that examine its effect on the stock market. Since the use of texts as data in scientific research is a growing field, this study aims to summarize the main findings to draw where the frontier knowledge in finance literature is. The remaining two studies investigate the relation between two variables estimated from news stories and the Brazilian stock market. Thereby, in the second study, we investigate the impact of economic uncertainty on weekly stock returns. We propose a new method to estimate economic uncertainty from news stories using word vectors for word representation. We find that there is a significant effect of our economic uncertainty measure on pricing individual stocks and provide similar evidence with uncertainty measures from news stories proposed in the literature. In the third study, we estimate corruption from news stories and investigate its relation to the stock performance of two firms that were involved in corruption scandals in the latest years with the primary goal of estimating the cost of corruption for the firms. The impact of the corruption reported in the news stories on the stock returns diverges between companies. In the case the company has private ownership, corruption in news negatively impacts stock returns. For the state-owned company, the effect is insignificant. We also find a long-term effect of the corruption scandals in the stock prices

Firm Performance and Stock Returns: The Moderating Role of Google Search Volume Index: Evidence from Companies Listed in Indonesian Sharia Stock Index

This study examines the effect of company performance on stock returns moderated by Google search volume on companies listed on the Indonesia Sharia Stock Index (ISSI). The research sample consists of companies registered with ISSI from January 1, 2020, to December 31, 2021. The results showed that the company's performance indicators, ROE and EPS, significantly positively affected stock returns. In addition, Google search volume directly impacts the increase in stock returns and positively moderates the relationship between EPS and stock returns. This research contributes to the accounting and capital market literature by looking at synergies between companies and investors' attention to Islamic stock returns, especially in times of crisis

Techniques for Stock Market Prediction: A Review

Stock market forecasting has long been viewed as a vital real-life topic in economics world. There are many challenges in stock market prediction systems such as the Efficient Market Hypothesis (EMH), Nonlinearity, complex, diverse datasets, and parameter optimization. A stock's value on the stock market fluctuates due to many factors like previous trends of the stock, the current news, twitter feeds, any online customer feedbacks etc. In this paper, the literature is critically analysed on approaches used for stock market prediction in terms of stock datasets, features used, evaluation metrics used, statistical, machine learning and deep learning techniques along with the directions for the future. The focus of this review is on trend and value prediction for stocks. Overall, 68 research papers have been considered for review from years 1998-2023. From the review, Indian stock market datasets are found to be most frequently used datasets. Evaluation metrics used commonly are accuracy and Mean Absolute Percentage Error. ARIMA is reported as the most used frequently statistical technique for stick market prediction. Long-Short Term Memory and Support Vector Machine are the commonly used algorithms in stock market prediction. The advantages and disadvantages of frequently used evaluation metrics, machine learning, deep learning and statistical approaches are also included in this survey