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We take Cumulative Prospect Theory (CPT) seriously by rigorously estimating structural models using the full set of CPT parameters. Much of the literature only estimates a subset of CPT parameters, or more simply assumes CPT parameter values from prior studies. Our data are from laboratory experiments with undergraduate students and MBA students facing substantial real incentives and losses. We also estimate structural models from Expected Utility Theory (EUT), Dual Theory (DT), Rank-Dependent Utility (RDU), and Disappointment Aversion (DA) for comparison. Our major finding is that a majority of individuals in our sample locally asset integrate. That is, they see a loss frame for what it is, a frame, and behave as if they evaluate the net payment rather than the gross loss when one is presented to them. This finding is devastating to the direct application of CPT to these data for those subjects. Support for CPT is greater when losses are covered out of an earned endowment rather than house money, but RDU is still the best single characterization of individual and pooled choices. Defenders of the CPT model claim, correctly, that the CPT model exists “because the data says it should.” In other words, the CPT model was borne from a wide range of stylized facts culled from parts of the cognitive psychology literature. If one is to take the CPT model seriously and rigorously then it needs to do a much better job of explaining the data than we see here.

Despite the widespread prevalence of share pledging by Indian promoters, this area remains out of the researchers’ purview. This study aims to bridge this research gap by delineating the impact of promoter share pledging on future stock price crash risk and financial performance in India.

A sample of 257 companies listed on the Standard and Poor’s Bombay Stock Exchange 500 (S&P BSE 500) Index has been analysed using panel (fixed-effects) data regression methodology over 2011–2020. Further, alternative proxies for crash risk and financial performance are adopted to ensure that the study’s initial findings are robust. Finally, the instrumental variable with the two-stage least squares (IV-2SLS) method has also been employed to alleviate endogeneity concerns.

The results suggest a significantly positive relationship between promoter share pledging and future stock price crash risk in India. Conversely, this association is significantly negative for future financial performance. Moreover, the results hold, even after including alternative proxies of stock price crash risk and financial performance and addressing endogeneity concerns.

Owing to the sizeable equity shareholdings of the promoters, share pledging has remained a lucrative source of finance in India. Despite the popularity, the findings of this study question the relevance of share pledging by Indian promoters considering its impact on aggravating future stock price crash risk and deteriorating future financial performance.

This paper aims to introduce a heteroskedastic hidden truncation normal (HTN) model that allows for conditional volatilities, skewness and kurtosis, which evolve over time and are linked to economic dynamics and have economic interpretations.

The model consists of the HTN distribution introduced by Arnold et al. (1993) coupled with the NGARCH type (Engle and Ng, 1993). The HTN distribution nests two well-known distributions: the skew-normal family (Azzalini, 1985) and the normal distributions. The HTN family of distributions depends on a hidden truncation and has four parameters having economic interpretations in terms of conditional volatilities, kurtosis and correlations between the observed variable and the hidden truncated variable.

The model parameters are estimated using the maximum likelihood estimator. An empirical application to market data indicates the HTN-NGARCH model captures stylized facts manifested in financial market data, specifically volatility clustering, leverage effect, conditional skewness and kurtosis. The authors also compare the performance of the HTN-NGARCH model to the mixed normal (MN) heteroskedastic MN-NGARCH model.

The paper presents a structure dynamic, allowing us to explore the volatility spillover between the observed and the hidden truncated variable. The conditional volatilities and skewness have the ability at modeling persistence in volatilities and the leverage effects as well as conditional kurtosis of the S&P 500 index.

This study aims to examine the multiscale predictability power of COVID-19 deaths and confirmed cases on the S&P 500 index (USA), CAC30 index (France), BSE index (India), two strategic commodity futures (West Texas intermediate [WTI] crude oil and Gold) and five main uncertainty indices Equity Market Volatility Ticker (EMV), CBOE Volatility Index (VIX), US Economic Policy Uncertainty (EPU), CBOE Crude Oil Volatility Index (OVX) and CBOE ETF Gold Volatility Index (GVZ). Furthermore, the authors analyze the impact of uncertainty indices and COVID-19 deaths and confirmed cases on the price returns of stocks (S&P500, CAC300 and BSE), crude oil and gold.

The authors used the wavelet coherency method and quantile regression approach to achieve the objectives.

The results show strong multiscale comovements between the variables under investigation. Lead-lag relationships vary across frequencies. Finally, COVID-19 news is a powerful predictor of the uncertainty indices at intermediate (4–16 days) and low (32–64 days) frequencies for EPU and at low frequency for EMV, VIX, OVX and GVZ indices from January to April 2020. The S&P500, CAC30 and BSE indexes and gold prices comove with COVID-19 news at low frequencies during the sample period. By contrast, COVID-19 news and WTI oil moderately correlated at low frequencies. Finally, the returns on equity and commodity assets are influenced by uncertainty indices and are sensitive to market conditions.

This study contributes to the literature by exploring the time and frequency dependence between COVID-19 news (confirmed and death cases) on the returns of financial and commodity markets and uncertainty indexes. The findings can assist market participants and policymakers in considering the predictability of future prices and uncertainty over time and across frequencies when setting up regulations that aim to enhance market efficiency.

The authors extend the recent research using the risk component of human resource’s (HR’s) compensation plans to examine the effects of risk components on two strategic outcomes: within-firm temporal change, or strategic variation, and firm strategic divergence from the industry, or strategic deviation. In addition, the authors examine the role of previous financial performance as a boundary moderator condition of the effects of risk components in the compensation plan and firm strategic outcomes.

To examine the effects of low- and high-risk components of executive compensation on strategic variation and deviation over time, the authors collected data from 2,510 companies listed in the Standard and Poor’s 500 index in a panel data format of a 12-year period. The authors gathered financial and other firm-level data from COMPUSTAT, and executive compensation and executive-level data from ExecuComp.

The findings support the main effects of risk components on strategic change, while both high- and low-risk components act on strategic deviation contingent on the moderating role of total shareholder return (TSR). In the theoretical framework, the authors test the moderating role of total shareholder return (TSR) as a boundary condition of the effects of risk components in the compensation plan. In doing so, the authors provide a fine-grained understanding of the influence of compensation plan risk components on outcomes proximal to executives, such as the maintenance of the status quo and the search for financial gains.

New studies can explore a three-way moderating effect on performance indicators, such as TSR, Tobin’s Q and return on asset. The authors addressed this limitation and did a comparative analysis, but the authors did not include additional moderating mechanisms in these interactive effects.

By disaggregating the executive’s compensation based on the risk components, boards of directors can mitigate any possible unwanted biases in the relationship between principal and agent.

By considering the influence of both low- and high-risk components of compensation plans on strategic outcomes –instead of firm performance – this study expands strategy literature supporting the influence of compensation schema on a firm’s outcomes. This path is new because it offers a moderating perspective to understand the strategic deviations and changes that chief executive officers imprint in their firms.

Los autores amplían la investigación reciente usando el componente de riesgo de los planes de compensación de RH para examinar los efectos de los componentes de riesgo en dos resultados estratégicos: cambio temporal dentro de la empresa, o variación estratégica, y divergencia estratégica de la empresa de la industria, o desviación estratégica. Además, examinamos el papel del desempeño financiero anterior como una condición moderadora límite de los efectos de los componentes de riesgo en el plan de compensación y los resultados estratégicos de la empresa.

Para examinar los efectos de los componentes de alto y bajo riesgo de la compensación ejecutiva en la variación y desviación estratégica a lo largo del tiempo, recopilamos datos de 2510 empresas que figuran en el índice Standard & Poor's 500 en un formato de datos de panel de un período de 12 años. Los autores recopilaron datos financieros y de otro tipo a nivel de empresa de COMPUSTAT, y compensación de ejecutivos, y datos a nivel ejecutivo de EXECUCOMP.

Nuestros hallazgos respaldan los efectos principales de los componentes de riesgo en el cambio estratégico, mientras que los componentes de alto y bajo riesgo actúan sobre la desviación estratégica dependiendo del papel moderador del rendimiento total del accionista. En el marco teórico, los autores prueban el papel moderador del Retorno Total del Accionista como condición límite de los efectos de los componentes de riesgo en el plan de compensación. Al hacerlo, brindamos una comprensión detallada de la influencia de los componentes de riesgo del plan de compensación en los resultados próximos a los ejecutivos, como el mantenimiento del statu quo y la búsqueda de ganancias financieras.

al considerar la influencia de los componentes de bajo y alto riesgo de los planes de compensación en los resultados estratégicos, en lugar del desempeño de la empresa, este estudio amplía la literatura de estrategia que respalda la influencia del esquema de compensación en los resultados de una empresa. Este camino es nuevo porque ofrece una perspectiva moderadora para entender las desviaciones y cambios estratégicos que los CEOs imprimen en sus firmas.

los nuevos estudios pueden explorar un efecto moderador de tres vías en los indicadores de rendimiento, como TSR, Tobin's Q y ROA. Abordamos esta limitación e hicimos un análisis comparativo, pero no incluimos mecanismos moderadores adicionales en estos efectos interactivos.

al desagregar la compensación del ejecutivo en función de los componentes de riesgo, las juntas directivas pueden mitigar cualquier posible sesgo no deseado en la relación entre el principal y el agente.

Os autores estendem a pesquisa recente usando o componente de risco dos planos de remuneração de RH para examinar os efeitos dos componentes de risco em dois resultados estratégicos: mudança temporal dentro da empresa, ou variação estratégica, e divergência estratégica da empresa do setor, ou desvio estratégico. Além disso, examinamos o papel do desempenho financeiro anterior como uma condição moderadora dos efeitos dos componentes de risco no plano de remuneração e nos resultados estratégicos da empresa.

Para examinar os efeitos dos componentes de baixo e alto risco da remuneração executiva na variação e desvio estratégico ao longo do tempo, coletamos dados de 2.510 empresas listadas no índice Standard & Poor's 500 em um formato de dados de painel de um período de 12 anos. Os autores coletaram dados financeiros e de outros níveis da empresa da COMPUSTAT, remuneração executiva e dados de nível executivo da EXECUCOMP.

Nossos resultados suportam os principais efeitos dos componentes de risco na mudança estratégica, enquanto os componentes de alto e baixo risco atuam no desvio estratégico contingente ao papel moderador do Retorno Total ao Acionista. No referencial teórico, os autores testam o papel moderador do Total Shareholder Return como condição limite dos efeitos dos componentes de risco no plano de remuneração. Ao fazer isso, fornecemos uma compreensão refinada da influência dos componentes de risco do plano de remuneração nos resultados próximos aos executivos, como a manutenção do status quo e a busca por ganhos financeiros.

ao considerar a influência dos componentes de baixo e alto risco dos planos de remuneração nos resultados estratégicos -em vez do desempenho da empresa- este estudo expande a literatura de estratégia que apoia a influência do esquema de remuneração nos resultados de uma empresa. Esse caminho é novo porque oferece uma perspectiva moderadora para entender os desvios e mudanças estratégicas que os CEOs imprimem em suas empresas.

Novos estudos podem explorar um efeito moderador de três vias em indicadores de desempenho, como TSR, Q de Tobin e ROA. Abordamos essa limitação e fizemos uma análise comparativa, mas não incluímos mecanismos moderadores adicionais nesses efeitos interativos.

Ao desagregar a remuneração do executivo com base nos componentes de risco, os conselhos de administração podem mitigar possíveis vieses indesejados na relação entre principal e agente.

The purpose of this study is to analyse and compile the literature on various option pricing models (OPM) or methodologies. The report highlights the gaps in the existing literature review and builds recommendations for potential scholars interested in the subject area.

In this study, the researchers used a systematic literature review procedure to collect data from Scopus. Bibliometric and structured network analyses were used to examine the bibliometric properties of 864 research documents.

As per the findings of the study, publication in the field has been increasing at a rate of 6% on average. This study also includes a list of the most influential and productive researchers, frequently used keywords and primary publications in this subject area. In particular, Thematic map and Sankey’s diagram for conceptual structure and for intellectual structure co-citation analysis and bibliographic coupling were used.

Based on the conclusion presented in this paper, there are several potential implications for research, practice and society.

This study provides useful insights for future research in the area of OPM in financial derivatives. Researchers can focus on impactful authors, significant work and productive countries and identify potential collaborators. The study also highlights the commonly used OPMs and emerging themes like machine learning and deep neural network models, which can inform practitioners about new developments in the field and guide the development of new models to address existing limitations.

The accurate pricing of financial derivatives has significant implications for society, as it can impact the stability of financial markets and the wider economy. The findings of this study, which identify the most commonly used OPMs and emerging themes, can help improve the accuracy of pricing and risk management in the financial derivatives sector, which can ultimately benefit society as a whole.

It is possibly the initial effort to consolidate the literature on calibration on option price by evaluating and analysing alternative OPM applied by researchers to guide future research in the right direction.

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 explore the impact of board gender diversity on firms’ forward-looking risk, as perceived by both the firm’s management and its investors. The authors seek to understand whether the presence of female directors and the consequent enhancement of board dynamics can influence a firm’s risk profile.

The authors use firms’ cash holdings and option implied volatility as proxies for future risk. The approach involves a rigorous analysis that accounts for potential concerns related to selection bias, endogeneity, heteroskedasticity and serial correlation. The authors further substantiate the findings through robustness checks, including a dynamic panel system general method of moment test and a Heckman correction model.

The results reveal an inverse relationship between board gender diversity and firms’ expected risk. The findings suggest that the primary driver of this risk reduction is the improvement in the group dynamics of the board that comes with increased gender diversity. This implies that gender diverse boards can significantly influence a firm’s risk management and financial performance.

The results indicate that gender diverse firms have economically and statistically significantly less expected risk and have better financial performance than firms with less board gender diversity. This has important implications for the organization of corporate boards.

If the addition of female directors alters the risk aversion of the board, then management may be compelled to alter their investment and production decisions that, ultimately, affects firms’ profitability. In addition, the authors investigate whether changes to firm risk is due to gender differences in risk preferences or to an improvement in the group dynamics of the board.

The empirical results suggest that the effect of board gender diversity on firms’ expected risk and financial performance may be due to an improvement in the collective intelligence of the board, as a result of more gender diversity, and not due to gender differences in risk preferences.

To the best of the authors’ knowledge, this work is the first to study the effect of board gender diversity on firms’ future risk.