Search results

Although the value effect is comprehensively investigated in developed markets, the number of studies examining the Vietnamese stock market is limited. Hence, the first aim of this research is to provide empirical evidence regarding returns on value and growth stocks in Vietnam. The second aim is to explain abnormal returns on Vietnamese growth and value stocks using both risk-based and behavioral points of view.

From the risk-based explanation, the Capital Asset Pricing Model (CAPM), Fama–French three- and five-factor models are estimated. From the behavioral explanation, to construct the mispricing factor, this paper relies on the method of Rhodes-Kropf et al. (2005), one of the most popular mispricing estimations in the financial literature with numerous citations (Jaffe et al., 2020).

While the CAPM and Fama–French multifactor models cannot capture returns on growth and value stocks, a three-factor model with the mispricing factor has done an excellent job in explaining their returns. Three out of four Fama–French mimic factors do not contain additional information on expected returns. Their risk premiums are also statistically insignificant according to the Fama–MacBeth second-stage regression. By contrast, both robustness tests prove the explanatory power of a three-factor model with mispricing. Taken together, mispricing plays an essential role in explaining returns on Vietnamese growth and value stocks, consistent with the behavioral point of view.

There are several value-enhancing aspects in the field of market finance. First, this paper contributes to the literature of value effect in emerging markets. While the evidence of value effect is obvious in numerous developed as well as international markets, both growth and value effects are discovered in Vietnam. Second, the explanatory power of Fama–French multifactor models is evaluated in the Vietnamese context. Finally, to the best of the author's knowledge, this is the first paper that incorporates the mispricing estimation of Rhodes-Kropf et al. (2005) into the asset pricing model in Vietnam.

Prior studies generally focus on income smoothing through discretionary accruals and document that managers have incentives to smooth earnings due to various reasons. This paper aims to focus on income smoothing through research and development (R&D) management and examine whether and how income smoothing through R&D management affects credit rating agencies’ perception of firm risk.

The authors use financial statement data from the CRSP/Compustat Merged data set universe for the period from 1992 to 2019 after excluding financial and utility industries. The authors follow the model for credit ratings used in previous literature to test the hypothesis. Specifically, the authors use an ordered probit model to express credit ratings as a function of income smoothing attributes.

The authors find that R&D-based income smoothing improves a firm’s credit rating. However, the positive effect of R&D-based income smoothing on credit ratings is less than that of accruals-based income smoothing. This study also shows that the positive effect of R&D-based income smoothing is more pronounced for firms less subject to opportunistic incentives, further strengthening the notion that managers smooth earnings through R&D management to provide more informative earnings.

This study contributes to the income smoothing literature in several ways. First, the authors contribute to the research by showing that managers’ income smoothing activity through R&D management positively affects firms’ credit rating. Second, the authors also document the relative benefits of the two different income smoothing techniques in terms of improving credit agencies’ perception of firms’ creditworthiness.

The challenge of predicting changes in aggregate income and stock prices is one that has occupied the research agendas of economists. This paper aims to use the consumption–income ratio and the dividend–price ratio to predict future income and stock prices.

To examine the stability of the consumption–income ratio and the dividend–price ratio, the authors run a two-variable, two-lag reduced-form VAR in the vein of Cochrane (1994), using a lag of each respective ratio as exogenous to the VAR. Additionally, the authors estimate an AR(4) model for income and prices.

The consumption–income ratio and the dividend–price ratio remain key to understanding future movements in income and stock prices. The consumption–income ratio significantly predicts future income in the USA, and aggregate income is easier to predict than consumption in the VAR model. The dividend–price ratio does not significantly predict future price growth. Consumption and dividend shocks have lasting impacts on income and prices.

The consumption–income ratio and the dividend–price ratio are still key to understanding future movements in income and stock prices. The consumption–income ratio significantly predicts future income in the USA, and aggregate income is easier to predict than consumption in the VAR model. However, the dividend–price ratio does not significantly predict future price growth, a change from previous research from the 1990s, despite the increasing complexity of stock markets. Consumption and dividend shocks have lasting impacts on income and prices and appear to be significant drivers in both the short- and long-run variance in income and prices.

I seek to identify whether cash flow management can affect the performance and risk of the Greek listed companies.

This study examines the relationship of cash flow management with performance and risk, using a sample of 80 non-financial companies listed in the Athens Exchange. The study covers the period 2018–2022, and panel data analysis is applied. Both financial performance and stock return are taken into consideration, while risk concerns the volatility of the companies’ share prices. The various explanatory variables used include the net cash flow, free cash flow, cash conversion cycle days, cash flow from operating activities, cash flow from investing activities, cash flow from financing activities, inventory days, customer days and supplier days.

The empirical results provide evidence of a positive relationship between financial performance and net cash flow and free cash flow. In addition, operating cash flow is positively related to financial performance. The opposite is the case for investing and financing cash flow. Finally, some evidence of a negative relationship between financial performance and inventory and customer days is provided too. On the other hand, stock return and risk are not related to the cash flow management variables at all.

To the best of my knowledge, this is one of the few studies to examine the relationship of cash flow management with performance and risk, using data from the Greek stock market. The results can form an effective selection tool for investors seeking Greek companies with the highest financial performance potential, which may reward them with higher dividends.

This study aims to test the market anomaly of herding behavior driven by the response to supply chain disruptions in extreme market conditions such as those observed during COVID-19. The authors empirically test the response of the capital market participants for B2B firms, resulting in herding behavior.

Using the event study approach based on the market model, the authors test the impact of supply chain disruptions and resultant herding behavior across six sectors and among different B2B firms. The authors used cumulative average abnormal returns (CAAR) and cross-sectional absolute deviation (CSAD) to examine the significance of herding behavior across sectors.

The event study results show a significant effect of COVID-19 due to supply chain disruptions across specific sectors. Herding was detected across the automotive and pharmaceutical sectors. The authors also provide evidence of sector-specific disruption impact and herding behavior based on the black swan event and social learning theory.

The authors examine the impact of COVID-19 on herding in the stock market of an emerging economy due to extreme market conditions. This is one of the first studies analyzing lockdown-driven supply chain disruptions and subsequent sector-specific herding behavior. Investors and regulators should take sector-specific responses that are sophisticated during extreme market conditions, such as a pandemic, and update their responses as the situation unfolds.

Over the last few years, the European Central Bank (ECB) has adopted unconventional monetary policies. These measures aim to boost economic growth and increase inflation through the bond market. The purpose of this paper is to study the impact of the ECB’s quantitative easing (QE) on the investor’s behavior in the stock market.

First, the authors theoretically identify the transmission channels of the QE shocks to the stock market. Then, the authors empirically assess the financial market’s responses to QE shocks in a data-rich environment using a factor augmented VAR (FAVAR).

The results show that the ECB’s unconventional monetary policy positively affects the stock market. A QE shock leads to an increase in stock prices and a drop in the realized volatility and the implied risk premium. The authors also suggest that the ECB’s QE is transmitted to the stock market through five main channels: the liquidity, the expectation, the portfolio reallocation, the interest rates and the risk premium channels.

The findings help to better understand the behavior of stock market assets in a data-rich economic context and guide investors and policymakers in the presence of unconventional monetary tools. For instance, decision-makers and investors should consider the short-term effect of the QE interventions and the changing behavior of the financial actors over time. In addition, high stock market returns can increase risk appetite. This can lead investors to underestimate the market risk. Decision-makers and market participants should take into consideration the impact of the large injection of money through the QE, which may raise the risk of a speculative bubble in the financial market.

To the best of the authors’ knowledge, this is the first study that incorporates a theoretical and empirical analysis to explore QE transmission to the stock market in the European context. Unlike previous studies, the authors use the shadow rate proposed by Wu and Xia (2017) to quantify the effect of the ECB’s QE in a data-rich environment. The authors also include two key risk indicators – the stock market risk premium and the realized volatility – to capture investors’ behavior in the stock market following QE shocks.

This paper aims to examine the impact of chief executive officer (CEO) attributes on foreign shareholdings from the perspective of an emerging economy.

This study examined Bombay Stock Exchange listed firms from the Indian stock market and applied a balanced panel data approach with fixed effect estimation technique during the period 2010–2019.

The study shows that CEOs’ financial education and a higher level of education positively affect foreign shareholdings. The age and experience of CEO have a positive and significant impact on foreign shareholdings. Firms with male CEOs are preferred more by foreign investors. The effect of CEO busyness and CEO duality is negative on foreign shareholdings. Foreign investors prefer to invest in firms with foreign nationality CEOs. Furthermore, the robustness test reveals that the influence of CEO attributes on foreign shareholdings is stronger for new, small and stand-alone firms than for old, large and group-affiliated firms.

The study will be beneficial for a diverse audience ranging from firms’ board of directors, regulators and policymakers who are entrusted with the CEO recruitment process. Additionally, firms seeking external financing should disclose CEO information adequately and improve the reporting quality to attract foreign investors, as they consider CEO characteristics as a valuable signal before making investment decisions.

In light of the current legislative reforms, this study can be recognized as one of the early studies that explore the relationship between CEO attributes and foreign shareholdings in the context of an emerging economy.

This study aims to determine experimentally factors affecting the satisfaction of retail stock investors with various investor protection regulatory measures implemented by the Government of India and Securities and Exchange Board of India (SEBI). Also, an effort has been made to gauge the level of satisfaction of retail equities investors with the laws and guidelines developed by the Indian Government and SEBI for their invested funds.

To accomplish the study’s goals, a well-structured questionnaire was created with the help of a literature review, and copies of it were filled by Punjabi retail equities investors with the aid of stockbrokers, i.e. intermediaries. Amritsar, Jalandhar, Ludhiana and Mohali-area intermediaries were chosen using a random selection procedure. Xerox copies of the questionnaire were given to the intermediaries, who were then asked to collect responses from their clients. Some intermediaries requested the researcher to sit in their offices to collect responses from their clients. Only 373 questionnaires out of 1,000 questionnaires that were provided had been received back. Only 328 copies were correctly filled by the equity investors. To conduct the analysis, 328 copies, which were fully completed, were used as data. The appropriate approaches, such as descriptives, factor analysis and ordinal regression analysis, were used to study the data.

With the aid of factor analysis, four factors have been identified that influence investors’ satisfaction with various investor protection regulatory measures implemented by government and SEBI regulations, including regulations addressing primary and secondary market dealings, rules for investor awareness and protection, rules to prevent company malpractices and laws for corporate governance and investor protection. The impact of these four components on investor satisfaction has been investigated using ordinal regression analysis. The pseudo-R-square statistics for the ordinal regression model demonstrated the model’s capacity for the explanation. The findings suggested that a significant amount of the overall satisfaction score about the various investor protection measures implemented by the government/SEBI has been explained by the regression model.

A study could be conducted to analyse the perspective of various stakeholders towards the disclosures made and norms followed by corporate houses. The current study may be expanded to cover the entire nation because it is only at the state level currently. It might be conceivable to examine how investments made in the retail capital market affect investors in rural areas. The influence of reforms on the functioning of stock markets could potentially be examined through another study. It could be possible to undertake a study on female investors’ knowledge about retail investment trends. The effect of digital stock trading could be examined in India. The effect of technological innovations on capital markets can be studied.

This research would be extremely useful to regulators in developing policies to protect retail equities investors. Investors are required to be safeguarded and protected to deal freely in the securities market, so they should be given more freedom in terms of investor protection measures. Stock exchanges should have the potential to bring about technological advancements in trading to protect investors from any kind of financial loss. Since the government has the power to create rules and regulations to strengthen investor protection. So, this research will be extremely useful to the government.

This work has societal ramifications. Because when adequate rules and regulations are in place to safeguard investors, they will be able to invest freely. Companies will use capital wisely and profitably. Companies should undertake tasks towards corporate social responsibility out of profits because corporate houses are part and parcel of society only.

Many investors may lack the necessary expertise to make sound financial judgments. They might not be aware of the entire risk-reward profile of various investment options. However, they must know various investor protection measures taken by the Government of India & Securities and Exchange Board of India (SEBI) to safeguard their interests. Investors must be well-informed on the precautions to take while dealing with market intermediaries, as well as in the stock market.

This study aims to endeavour to decode artificial intelligence (AI)-based tokens' complex dynamics and predictability using a comprehensive multivariate framework that integrates technical and macroeconomic indicators.

In this study we used advance machine learning techniques, such as gradient boosting regression (GBR), random forest (RF) and notably long short-term memory (LSTM) networks, this research provides a nuanced understanding of the factors driving the performance of AI tokens. The study’s comparative analysis highlights the superior predictive capabilities of LSTM models, as evidenced by their performance across various AI digital tokens such as AGIX-singularity-NET, Cortex and numeraire NMR.

This study finding shows that through an intricate exploration of feature importance and the impact of speculative behaviour, the research elucidates the long-term patterns and resilience of AI-based tokens against economic shifts. The SHapley Additive exPlanations (SHAP) analysis results show that technical and some macroeconomic factors play a dominant role in price production. It also examines the potential of these models for strategic investment and hedging, underscoring their relevance in an increasingly digital economy.

According to our knowledge, the absence of AI research frameworks for forecasting and modelling current aria-leading AI tokens is apparent. Due to a lack of study on understanding the relationship between the AI token market and other factors, forecasting is outstandingly demanding. This study provides a robust predictive framework to accurately identify the changing trends of AI tokens within a multivariate context and fill the gaps in existing research. We can investigate detailed predictive analytics with the help of modern AI algorithms and correct model interpretation to elaborate on the behaviour patterns of developing decentralised digital AI-based token prices.

This paper contributes to the literature as follows. First, it examines if option and stock compensations raise creditor's risk, and which one is more important than the other. Second, it explores if CEO's compensation interacts with CEO overconfidence to raise creditor's risk. Third, it investigates how banks use different loan terms to alleviate their credit risk.

This study used advanced regression analysis and use of generalized methods of moment methodology.

The results show that option compensation is more important than stock compensation in raising credit risk; option compensation interacts with CEO overconfidence, giving rise to a much higher credit risk; and covenant usage is more important than other loan contract terms in mitigating credit risk given that covenant use could not be substituted away by using other loan contract terms such as increasing interest rate, reducing principal or shortening loan duration. This paper has practical implications for credit markets.

The main implication is that hand-collect data are available up to 2010.

It informs creditors the potential sources of loan risk emanating from option rather than stock incentives; it informs creditors that option incentive interacts with CEO overconfidence rendering the credit risk bigger than expected, and it informs creditors the importance of using covenants vis-à-vis other loan contract terms for mitigating compensation and overconfidence risk.

Banks are alerted to the risk due to the interaction between overconfidence and compensations, implying that overconfident managers remunerated with options compensations are more risky than overconfident managers who are not remunerated as such.

This paper is original: (1) The authors show that option compensation is more risky than stock compensation from viewpoint of creditors. This has not been assessed. (2) Interaction between managerial compensation and managerial overconfidence has not been assessed before. (3) Use of different loan contract terms to alleviate risk from overconfident managers (who are prone to over investment but who are innovative according to the literature) has not been evaluated.