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International audience; Exloring the role of different types of investors on stock market is crticial since different types of investors react and behave differently when making investment decision. The role of investor behavior is a very important issue in an immature stock market like Vietnam stock market because the market is characterized by a large number of individual investors and low reporting standard. Institutional and foreign investors however play an influential role due to their large exposure and strong investment expertise. Clearly, examining the role of investor behavior and its impact on the stock market in Vietnam is an important topic in finance. A significant body of empirical research has shown that investor behavior is an essential factor to explain stock price that the classical financial theory cannot explain. This research examines the role of investor behavior in stock market by examining the relationship between investor behavior and stock return using the Vietnamese stock exchange data. We create a sentiment index using the principal components analysis (PCA). Consistent with the sentiment and stock return literature, the research shows a negative contemporaneous relationship between investor sentiment and market return.

Optimal stock investment decisions rely on assessments of the distribution of expected returns. Using a representative sample, we find over half the US population cannot answer simple questions on expected stock returns. Respondents who are unable to make any return prediction, who cannot answer questions on the distribution of expected returns, or who reveal unlikely distributional beliefs participate less in the stock market and have smaller stock investments. However, overoptimistic investors are more likely to participate in the stock market and have larger stock investments. These results persist after controlling for financial literacy, intelligence, education, and demographics. People who are ignorant about stock return distribution are more likely to invest in equities if they have higher levels of trust. Therefore, trust can substitute for cognition as a factor positively associated with individuals’ propensity to invest.

Med bakgrund till det ökade intresset för aktier och dagens ekonomiska läge är det högst aktuellt att undersöka relationen mellan makroekonomiska svängningar och aktiepriserna på den svenska börsen. Det finns flera teorier som försöker förklara hur aktiepriser förändras, en allmän slutsats är att externa faktorer påverkar priset genom oförväntade händelser. Chen, Roll och Ross konstruerade en tidsseriemodell för att studera hur oförväntade makroekonomiska faktorer påverkar aktieavkastningen på New York-börsen. Deras slutsatser landade i att oförväntade förändringar i samtliga variabler har en signifikant relation till aktieprisavkastningen. Med detta i åtanke är syftet med uppsatsen att undersöka om avkastningen på olika branscher på den svenska börsen påverkas av oförväntade månatliga förändringar i inflation (KPI), konjunkturläget (BNP), avkastningskurvan, riskpremien samt växelkursen under tidsperioden 2000-2023. Det genomförs även en jämförande analys mellan de europeiska länderna Sverige, Tyskland, Danmark och Finland. De branschindex som studeras är finans, industri, teknologi, sjukvård och detaljhandel för respektive land. Genom en multipel regressionsmodell har få signifikanta samband påvisats, däremot finner vi ett mönster i negativa respektive positiva relationer mellan oförväntade makroekonomiska händelser och aktieavkastningen för samtliga länder. Sammanfattningsvis finner vi inga tydliga skillnader i vilka branscher som påverkas av respektive riskfaktor, däremot finns en skillnad i antal signifikanta värden mellan länderna. Nationella makroekonomiska händelser påvisar flest signifikanta samband till tyska branschindex, följt av danska och finska. Minst signifikanta samband påvisas för de svenska branschindexen. En förklaring bakom resultatet kan vara att ländernas aktiemarknader är mer eller mindre effektiva och investerare på respektive marknad är olika mottagliga till ny information. Avslutningsvis ser vi det vara rimligt att både branscher och länder påverkas av riskfaktorerna i olika stor utsträckning. Att bygga en aktieportfölj med tillgångar från både olika branscher och länder är därmed betydelsefullt för att sprida sina risker. Considering the increased interest in the stock market and the current economic situation, it is highly relevant to examine the relationship between macroeconomic fluctuations and share prices on the Swedish stock exchange. There are several theories that try to explain how stock prices change, a general conclusion is that external factors affect the price through unexpected events. Chen, Roll, and Ross constructed a time series model in order to study how unexpected macroeconomic factors affect stock returns on the New York Stock Exchange. Their conclusions resulted in that unexpected changes in all variables have a significant relationship to share price returns. With this in mind, the purpose of the essay is to investigate whether the return on various sector indexes on the Swedish stock exchange is affected by unexpected monthly changes in inflation (CPI), economic state (GNP), the term structure, the risk premium and the exchange rate during the time period 2000-2023. A comparative analysis is also carried out between the European countries Sweden, Germany, Denmark and Finland. The examined sector indexes are finance, industry, technology, healthcare and retail for each country. Through a multiple regression model, the result shows that few macroeconomic variables are significant in explaining stock returns. However, we find a pattern in negative as well as positive relationships between unexpected risk factors and stock returns for all countries. We find no significant differences in which sectors are affected by each risk factor but there is a difference in the number of significant values ​​between the countries. National macroeconomic events show the most significant relations to German sector indexes, followed by Danish and Finnish. Least significant relationships are found for the Swedish sector indexes. An explanation behind the result could be that the countries stock markets are more or less efficient and investors in each market are differently receptive to new information. Our conclusion is that we see it as reasonable that both sectors and countries are affected by the risk factors to varying degrees. Building a stock portfolio with assets from both different sectors and countries is therefore important for spreading your risks.

The purpose of this study is to determine the predictability of the Pakistani stock market's one-day forward returns by utilizing lagged daily returns for Pakistan, India, and Malaysia from 2006 to 2016. The findings indicate that lagged Pakistani market returns significantly predict Pakistani one-day ahead market returns. However, the other two growing stock markets, India and Malaysia, show no association with one-day ahead market returns. Mostly, stock market behavior in the pre-2008 and post-2008 eras was the same, although industry return behaviour was different due to the economic crisis of 2008. However, the Pakistani stock market one-day ahead returns predict the own Pakistani lag returns due to an inefficient market and prices do not follow a random walk. As a result, investors and financial analysts can foresee and generate anomalous returns by using previous data and information. Key words: Stock Market Returns Predictability, Stock Market crash, Market efficiency

Investor assessment of information on the effect of Ramadhan on stock return and trading volume company activities in the capital market is an important phenomenon that always occurs. The purpose of this study was to analyze average abnormal returns and average trading volume activities of stocks before and after the announcement the effect Ramadhan as National Non-Natural Disaster. The method used was an event study with a sample of companies listed in the LQ45, JII, SRI KEHATI, and PEFINDO Indexes. Observations of the 30-day Ramadan event were carried out from April 23 to March 24, 2021, in the month of Sha'ban - syawwal, using 15 samples obtained from IDX (Indonesian Stock Exchange) data. The analytical tool used was regression supported by the SPSS application. The results of the study showed that the Abnormal Returns (AR) was significantly different before (Sya'ban) and after the month of Ramadan (Syawal) for companies on the Indonesia Stock Exchange in 2021, indicating a consistent AR reaction to the Ramadhan Effect. Meanwhile, Trading Volume Activities (TVA) didn't differ significantly before (Sya'ban) and after the month Ramadan (Syawal) at companies on Indonesia Stock Exchanges in 2021. This study updates previous research by including the effect of Ramadan as a research test variable.

Whether a stock market should matter or not when monetary policy is concerned seems to be a controversial issue. The purpose of this study is to indicate whether the central bank should use monetary policy to help the stock market or not. Based on macroeconomic data such as interest rate and the stock market, we adopt a novel Bayesian time-varying regression model and determine that the impact of interest rate changes on stock returns varies over time in China, after controlling various macroeconomic factors. Although on average interest rates negatively impact stock price returns, they tend to have an abnormal positive effect at market high points, following a time-varying dynamic pattern. Surprisingly, during periods of overheated economic development, an increase in interest rates cannot suppress the rise in stock prices. Therefore, policymakers need to pay attention when accelerating the marketisation of interest rates and initiating the preventive role of timely and strategic adjustment of interest rates.

This research discusses and analyzes the company's profitability related to the company's stock return performance Profitability of the firm is related to the firm's performance of stock return. This study uses time-series data with a total sample of 1,010 firms from five countries in ASEAN (Indonesia, Thailand, Malaysia, Philippines, and Vietnam) from January 2010 to December 2019. Fama-French 3 factor model based on two different profitability showed that profitability positively affects the stock return in ASEAN markets. Fama-MacBeth's (1973) regression confirms that firm profitability scaled by operating profit-to-equity or operating profit-to-assets positively influences expected stock returns in the ASEAN market.DOI: 10.26905/jkdp.v25i3.5598

Deep learning methods have been developed, used in various fields, and they have shown outstanding performances in many cases. Many studies predicted a daily stock return, a classic example of time-series data, using deep learning methods. We also tried to apply deep learning methods to Korea’s stock market data. We used Korea’s stock market index (KOSPI) and several individual stocks to forecast daily returns and directions. We compared several deep learning models with other machine learning methods, including random forest and XGBoost. In regression, long short term memory (LSTM) and gated recurrent unit (GRU) models are better than other prediction models. For the classification applications, there is no clear winner. However, even the best deep learning models cannot predict significantly better than the simple base model. We believe that it is challenging to predict daily stock return data even if we use the latest deep learning methods.

The pandemic Covid-19 caused panic not only in health sectors but also weakened the world’s economy. The stock market, as one of the barometers of the economy, was hit by the pandemic Covid-19. The impact of Covid-19 on the stock market provides a signal for investors. Stock returns are what investors look for when investing in stocks. Returns on the stock exchange respond to several events, one of which is the news about health related to the Covid-19 pandemic. This study aims to seek whether the Covid-19 outbreak affects stock returns in Indonesia Stock Exchange. Using daily data of Covid-19 confirmed case, daily data of Covid-19 death cases, and stock returns data in Indonesia from January 2, 2020, to December 31, 2020. The panel-data regression model is used to estimate the result of the study. This study shows that stock returns in Indonesia Stock Exchange respond negatively significantly as the number of confirmed cases increases also stock returns in Indonesia respond negatively significantly to the daily growth of death cases. This study also finds that stock return in consumer goods and basic chemical industry were the impacted industries caused by pandemic Covid-19. Empirical findings could be used for the practitioner to consider investing in the stock market to avoid the significant impact of such outbreaks in the future.