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Based on stakeholder, agency and institutional theory, this study aims to examine the role of institutional ownership in the relationship between environmental, social and governance practices and CEO compensation.

Utilizing a fixed-effect panel regression analysis, this research utilized a panel data approach, analyzing data spanning from 2014 to 2021, focusing on US companies listed on the S&P500 stock market index. The dataset encompassed 219 companies, leading to a total of 1,533 observations.

The analysis identified that environmental scores significantly impact CEO equity-linked compensation, unlike social and governance scores. Additionally, it was found that institutional ownership acts as a moderating factor in the relationship between the environmental score and CEO equity-linked compensation, as well as the association between the social score and CEO equity-linked compensation. Interestingly, the direction of these moderating effects varied between the two relationships, suggesting a nuanced role of institutional ownership.

This research makes a unique contribution to the field of corporate governance by exploring the relatively understudied area of institutional ownership's influence on the ESG practices–CEO compensation nexus.

We propose an alternative rationale for why some firms employ veterans, driven not solely by benevolence but also by the prospect of enhanced outcomes. Financially, hiring veterans could correlate with improved stock market performance for the hiring company while aligning with corporate social responsibility (CSR) initiatives. Our study centers on the stock market performance of companies hiring veterans. It aims to underscore a lesser-known facet of the veteran employment discourse and its connection to the hiring firm's financial performance.

This paper evaluates the stock market performance of three VETS portfolios (made of companies that hire veterans) compared to the benchmark SPDR S&P 500 ETF. Using a modular approach, we create three VETS passive indices: VETSEW (equal-weighted index), VETSPW (price-weighted index) and VETSVW (value-weighted index). The study analyzes the annual returns, portfolio allocations, risk-adjusted performance metrics and style analysis of the portfolios from January 1, 2020, to December 31, 2022.

The findings indicate that all three VETS portfolios outperformed the benchmark, with higher ending balances and superior risk-adjusted ratios such as the Sharpe and Sortino ratios. Notably, the portfolios demonstrated resilience during challenging periods, including the COVID-19 pandemic, subsequent recovery and an inflationary period.

Limitations include the paper's focus solely on stock returns, suggesting a need for broader financial and management ratios. Moreover, a deeper exploration into how veterans contribute during turbulent times is suggested for further investigation. Although the study touches upon the financial performance of veteran-focused companies during challenging economic times, it does not extensively delve into the specific ways in which veterans add value under such circumstances, presenting an opportunity for further exploration.

Firms that employ veterans amid the COVID-19 pandemic demonstrate favorable risk-adjusted returns, underscoring the potential of veterans as valuable crisis-time assets. Our research further underscores the correlation between veteran hiring and enhanced financial prowess. These insights carry significant policy implications, including CSR initiatives for hiring veterans, skill translation and training and collaboration with veteran organizations.

The paper's findings suggest significant implications: (1) Policymakers could incentivize firms to hire veterans through tax benefits or grants, leveraging their skills for organizational resilience. (2) Collaborative efforts between policymakers and firms can promote responsible hiring, boosting a company's reputation through diversity and inclusion, positively impacting society. (3) Support for skill translation from military to civilian jobs is crucial. Programs certifying skills and tailored education aid veterans' successful transition into the workforce. (4) Collaborations between policymakers, veteran organizations and private sector entities can create networks, job placements and support systems for veterans' employment.

Numerous prior studies within the domain of corporate social responsibility have predominantly neglected the contributions veterans offer to businesses and the underlying reasons behind firms' decisions to employ them. Our research uniquely concentrates on the stock market performance of companies that choose to hire veterans.

The primary objective of this research is to explore the potential of utilizing Global Consciousness Project (GCP) data as a tool for understanding and predicting market sentiment. Specifically, the study aims to assess whether incorporating GCP data into econometric models can enhance the comprehension of daily market movements, providing valuable insights for traders.

This study employs econometric models to investigate the correlation between the Standard & Poor's 500 Volatility Index (VIX), a common measure of market sentiment and data from the GCP. The focus is particularly on the largest daily composite GCP data value (Max[Z]) and its significant covariation with changes in VIX. The research employs interaction terms with VIX and daily returns from global markets, including Europe and Asia, to explore the relationship further.

The results reveal a significant relationship with the GCP data, particularly Max[Z] and VIX. Interaction terms with both VIX and daily returns from global markets are highly significant, explaining about one percent of the variance in the econometric model. This finding suggests that variations in GCP data can contribute to a better understanding of market dynamics and improve forecasting accuracy.

One limitation of this study is the potential for overfitting and P-hacking. To address this concern, the models undergo rigorous testing in an out-of-sample simulation study lasting for a predefined one-year period. This limitation underscores the need for cautious interpretation and application of the findings, recognizing the complexities and uncertainties inherent in market dynamics.

The study explores the practical implications of incorporating GCP data into trading strategies. Econometric models, both with and without GCP data, are subjected to an out-of-sample simulation where an artificial trader employs S&P 500 tracking instruments based on the model's one-day-ahead forecasts. The results suggest that GCP data can enhance daily forecasts, offering practical value for traders seeking improved decision-making tools.

Utilizing data from the GCP is found to be advantageous for traders as noteworthy correlations with market sentiment are found. This unanticipated finding challenges established paradigms in both economics and consciousness research, seamlessly integrating these domains of research. Traders can leverage this innovative tool, as it can be used to refine forecasting precision.

This study aims to investigate the effect of seasonality caused by fasting as a religious practice on trading activity.

The authors use an unbiased sample of daily trading by individuals and institutions on the Boursa Kuwait. The authors use panel data on trading activities and Tobit regression models to examine the effect of Muslims’ religious practice of fasting during the holy month of Ramadan on trading behavior.

The authors find that during the holy month of Ramadan, Muslims’ religious practice of fasting leads to a decline in the frequency of both overall stock market trading and the ratio of individual trading volume to total trading volume. The authors find a significant decrease in individual buy-side trading as a proportion of total trading volume and simultaneously a significant increase in institutional buy-side trading.

This study’s findings have important implications for the main players in stock markets of countries with a Muslim majority. Market-makers should be aware of the significant increase in the proportion of institutional buy-side trading volume to total trading volume to minimize the cost of trading with better-informed traders (adverse selection).

To the best of the authors’ knowledge, this is the first study that investigates individuals’ trading activity during Ramadan.

This study aims to provide empirical evidence on the return and volatility spillover structures between Bitcoin, Fintech stocks and Asian-Pacific equity markets over time and during different market conditions, and their implications for portfolio management.

We use Time-varying parameter vector autoregressive and quantile frequency connectedness approach models for the connectedness framework, in conjunction with Diebold and Yilmaz’s connectivity approach. Additionally, we use the minimum connectedness portfolio model to highlight implications for portfolio management.

Regarding the uncertainty of the whole system, we show a small contribution from Bitcoin and Fintech, with a higher contribution from the four Asian Tigers (Taiwan, Singapore, Hong Kong and Thailand). The quantile and frequency analyses also demonstrate that the link among assets is symmetric, with short-term spillovers having the largest influence. Finally, Bitcoins and Fintech stocks are excellent diversification and hedging instruments for Asian equity investors.

There is an instantaneous, symmetric and dynamic return and volatility spillover between Asian stock markets, Fintech and Bitcoin. This conclusion should be considered by investors and portfolio managers when creating risk diversification strategies, as well as by policymakers when implementing their financial stability policies.

The study’s major contribution is to analyze the volatility spillover between Bitcoin, Fintech and Asian stock markets, which is dynamic, symmetric and immediate.

Candlestick charts are a key tool for the technical analysis of cryptocurrency price fluctuations. It is essential to examine trends in the time series of a financial asset when completing an analysis. To accurately examine its potential future performance, it must also consider how it has changed and been active during the period. The researchers created cryptocurrency trading algorithms in this study based on the traditional candlestick pattern.

The data includes information on Bitcoin prices from early 2012 until 2021. Only the engulfing Candlestick model was able to anticipate changes in the price movements of Bitcoin. The traditional Harami model does not work with Bitcoin trading platforms because it has yet to generate profitable business results. An inverted Harami is a successful cryptocurrency trading method.

The inverted Harami approach accounts for 6.98 profit factor (PrF) and 74–50% of profitable (Pr) transactions, which favors a particularly long position. Additionally, the study discovered that almost all analyzed candlestick patterns forecast longer trends greater than shorter trends.

To statistically study its future potential return, examining how it has changed and been active over the years is necessary. Such valuations are the basis for trading strategies that could help traders and investors in the cryptocurrency market. Without sacrificing clarity or ease of application, the proposed approach has increased performance by up to 32.5% of mean absolute error (MAE).

This study is novel in that it used multilayer autoregressive neural network (MARN) models with crypto-net (CNM) in machine learning to analyze a time series of financial cryptocurrencies. Here, the primary study deals with time trends extracted through a neural network model. Then, the developed model was tested using Bitcoin and Ethereum. Finally, CNM validity was tested through linear regression.

Art return indices are usually estimated based only on a few means of artistic expression (mainly paintings and drawings). Other forms of expression (e.g. sculptures and installations) are generally ignored, in part because they are three-dimensional and, hence, more difficult to measure. We analyze the price determinants as well as the return and risk of three artistic expressions (paintings, drawings and sculptures) executed by Fernando Botero, the most expensive living Latin American artist, to analyze the degree to which their risk and return attributes differ throughout a 20-year period.

We analyzed all paintings, drawings and sculptures executed by Botero and sold at Sotheby’s and Christie’s between 2000 and 2020 (a total of 707 artworks). The data and the images of each artwork were obtained from the web pages of these two auction houses. A hedonic regression was run to explain the price of each artwork and use explanatory variables that are standard in the literature. Art price indices for paintings, drawings and sculptures were constructed using the year-dummy variables estimated in the regressions. We performed a similar analysis for another artist, Carlos Cruz-Diez, as a robustness to our results.

The performance of Botero’s sculptures through time differs markedly from that of his paintings and drawings. Our results suggest that it is possible that returns estimated in the literature could suffer from a bias, as they have usually ignored the performance of sculptures and other artistic expressions. Botero’s paintings provided a return that was comparable to those of his sculptures (3.36% and 3.20%, respectively), they were two times as high as those of his drawings (1.68%). On the other hand, whereas paintings and drawings had similar annual standard deviations (26% and 25.22%, respectively), sculptures had a much smaller standard deviation (16.96%).

A limitation of the hedonic regression method lies in the need to have a significant and diverse sample to identify the true effect of each variable on the price of a good. Another limitation is that we were only able to use art prices from auctions, as this is the only comprehensive source of art price data that is publicly available. These two limitations are shared by all the studies that use the hedonic pricing model.

Our results have practical applications for art collectors and investors, as well as for artists, galleries and, in general, for the whole art market ecosystem. The risk and return attributes of the various artistic expressions of an artist can be different, and thus it makes sense to analyze each one of them individually, as well as their correlations with the other artistic expressions and with traditional and other alternative investments.

The art market is part of what is known as the “orange economy” (also known as the Creative Economy). According to the World Bank, the economic value of the creative sector is not well known or appreciated, even though cultural, creative and artistic activities are vital for our sense of well-being.

To the best of our knowledge, this is the first paper that compares the financial performance of paintings, drawings and sculptures for the case of a specific artist. We chose Botero for three reasons. First, he is a Latin American living artist who has achieved the highest levels of international sales. Second, Botero has worked extensively on various artistic expressions (oil paintings, drawings on different materials and sculptures) throughout his life, a characteristic that is essential to be able to carry out our study. Third, there is a long record of auction sales for each of Botero’s artistic expressions.

Los índices de rentabilidad del arte generalmente se estiman basándose únicamente en unos pocos medios de expresión artística (principalmente pinturas y dibujos). Otras formas de expresión artística (por ejemplo, esculturas e instalaciones) generalmente se ignoran, en parte porque son tridimensionales y, por tanto, más difíciles de medir. Analizamos los determinantes del precio, así como el retorno y el riesgo de tres expresiones artísticas (pinturas, dibujos y esculturas) ejecutadas por Fernando Botero, el artista latinoamericano vivo más caro, para analizar en qué medida sus atributos de riesgo y retorno difieren a lo largo del tiempo, en un período de 20 años.

Analizamos todas las pinturas, dibujos y esculturas ejecutadas por Botero y vendidas en Sotheby’s y Christie’s entre 2000 y 2020 (un total de 707 obras de arte). Los datos y las imágenes de cada obra se obtuvieron de las páginas web de estas dos casas de subastas. Se realizó una regresión hedonante para explicar el precio de cada obra de arte y se utilizaron variables explicativas estándar en la literatura. Los índices de precios de arte para pinturas, dibujos y esculturas se construyeron utilizando variables ficticias anuales estimadas en las regresiones. Realizamos un análisis similar para otro artista, Carlos Cruz-Diez, como análisis de robustez de nuestros resultados.

El desempeño de las esculturas de Botero a través del tiempo difiere marcadamente del de sus pinturas y dibujos. Nuestros resultados sugieren que es posible que los retornos estimados en la literatura sufran un sesgo, ya que generalmente han ignorado el desempeño de esculturas y otras expresiones artísticas. Las pinturas de Botero proporcionaron un retorno comparable al de sus esculturas (3.36% y 3.20%, respectivamente), pero fueron dos veces superiores a los de sus dibujos (1.68%). Por otro lado, mientras que las pinturas y los dibujos tuvieron desviaciones estándar anuales similares (26% y 25.22%, respectivamente), las esculturas tuvieron una desviación estándar mucho menor (16.96%).

Una limitación del método de regresión hedónica radica en la necesidad de contar con una muestra significativa y diversa para identificar el verdadero efecto de cada variable sobre el precio de un bien. Otra limitación consiste en que solo pudimos utilizar precios de arte de subastas, ya que esta es la única fuente completa de datos sobre precios de arte que está disponible públicamente. Estas dos limitaciones son compartidas por todos los estudios que utilizan el modelo de precios hedónico.

Nuestros resultados tienen aplicaciones prácticas para coleccionistas e inversores de arte, así como también para artistas, galerías y, en general, para todo el ecosistema del mercado del arte. Los atributos de riesgo y retorno de las diversas expresiones de un artista pueden ser diferentes, por lo que tiene sentido analizar cada una de ellas individualmente, así como sus correlaciones con las otras expresiones artísticas y con las inversiones tradicionales y otras alternativas.

El mercado del arte forma parte de lo que se conoce como “economía naranja” (también conocida como Economía Creativa). Según el Banco Mundial, el valor económico del sector creativo no es bien conocido ni apreciado, a pesar de que las actividades culturales, creativas y artísticas son vitales para nuestra sensación de bienestar.

Hasta donde hemos podido comprobar, este es el primer artículo que compara el desempeño financiero de pinturas, dibujos y esculturas para el caso de un artista específico. Elegimos a Botero por tres razones. En primer lugar, es el artista vivo latinoamericano que ha alcanzado los mayores niveles de ventas internacionales. En segundo lugar, Botero ha trabajado extensamente en diversas expresiones artísticas (óleos, dibujos sobre distintos materiales y esculturas) a lo largo de su vida, característica que resulta fundamental para poder realizar nuestro estudio. En tercer lugar, existe un largo historial de ventas en subasta de cada una de las expresiones artísticas de Botero.

Although the effects of both news sentiment and expectations on price in financial markets have now been extensively demonstrated, the jointness that these predictors can have in their effects on price has not been well-defined. Investigating causal ordering in their effects on price can further our understanding of both direct and indirect effects in their relationship to market price.

We use autoregressive distributed lag (ARDL) methodology to examine the relationship between agent expectations and news sentiment in predicting price in a financial market. The ARDL estimation is supplemented by Grainger causality testing.

In the ARDL models we implement, measures of expectations and news sentiment and their lags were confirmed to be significantly related to market price in separate estimates. Our results further indicate that in models of relationships between these predictors, news sentiment is a significant predictor of agent expectations, but agent expectations are not significant predictors of news sentiment. Granger-causality estimates confirmed the causal inferences from ARDL results.

Taken together, the results extend our understanding of the dynamics of expectations and sentiment as exogenous information sources that relate to price in financial markets. They suggest that the extensively cited predictor of news sentiment can have both a direct effect on market price and an indirect effect on price through agent expectations.

Even traditional financial management firms now commonly track behavioral measures of expectations and market sentiment. More complete understanding of the relationship between these predictors of market price can further their representation in predictive models.

This article extends the frequently reported bivariate relationship of expectations and sentiment to market price to examine jointness in the relationship between these variables in predicting price. Inference from ARDL estimates is supported by Grainger-causality estimates.

This paper aims to examine the influence of sustainability reporting on bank performance. Furthermore, this study investigates the impact of the country’s economic development, financial system and crisis in moderating sustainability reporting and bank performance relationship.

The sample consists of 400 listed banks from 19 countries over the 2009–2022 period. Panel fixed-effect regression is applied, and System Generalized Method of Moments is used as robustness to address endogeneity concerns. The results are robust and survive several sensitivity tests.

The results, aligning with legitimacy and agency theories, suggest a negative relationship between sustainability reporting and bank performance. Based on further classifications, results suggest the negative (positive) impact of country’s financial system (economic development) in moderating the sustainability reporting and bank performance nexus. Finally, this study documents the positive influence of sustainability reporting on bank performance during the crisis period. Overall, the findings fail to support the reduced information asymmetry accruing from higher sustainability disclosures in developing and bank-based economies.

This study has important implications for regulators, policymakers and other stakeholders, especially in light of recent banking scandals that have deteriorated stakeholders' faith in financial institutions' reporting quality.

This study extends the scant literature on sustainability reporting in banking from a cost-benefit vantage point. Furthermore, to the best of the author’s knowledge, no previous research has examined the moderating role of the country’s financial structure and crisis in sustainability reporting and bank performance relationship.

Although intellectual capital (IC) and human dynamic capabilities (HDCs) play a significant role in decarbonization processes, their measurement and reporting is under-researched. Hence, this study aims to identify the link between HDCs, carbon accounting and integrated reporting (IR) in the transition processes, investigating IC and HDCs in decarbonization processes to achieve net-zero business models (n-ZBMs).

A systematic literature review with a concise bibliometric analysis is conducted on 229 articles, published from 1990 to 2023 in Scopus database and Google Scholar. Reviewing data on publications, journals, authors and citations and analysing the article content, this study identifies the main search trends, providing a new conceptual model and future research propositions.

The results reveal that the literature has rarely focussed on carbon accounting in terms of IC and HDCs. Additionally, firms face pressure from institutions and stakeholders regarding legitimacy and transparency, necessitating a response considering IR and requiring n-ZBMs to be developed through IC and HDCs to meet social and environmental requirements.

Not only does this study link IC with HDCs to address carbon emissions through decarbonization practices, which has never been addressed in the literature to date, but also provides novel recommendations and propositions through which firms can sustainably transition to being net-zero emission firms, thereby gaining competitive advantage and contributing to the nation’s sustainability goals.