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The purpose of this study is to examine empirically the conditional correlation between the major US indices (S&P500 index and Dow Jones Industrial index) and three selected meat commodities as: Feeder Cattle, Leen Hogs and Live Cattle during the period from July 22, 2010 to June 30, 2017.

In this study, the authors use for the first time the GARCH-DECO (1,1) to examine empirically the conditional nexus between the major US indices (S&P500 index and Dow Jones Industrial index) and three selected meat commodities as; Feeder Cattle, Leen Hogs and Live Cattle during the period from July 22, 2010 to June 30, 2017.

From the empirical findings, the authors conclude the existence of a highly significance of conditional heteroscedasticity parameters can demonstrate us to distinguish the nature of the volatility dependency between S&P500 index and Dow Jones Industrial index and three selected meat commodities indices.

This can find clear the significance of relationship in the process of financialization of the major US index and meat commodities indices in the case of this paper.

This study attempts to examine the time-varying volatility spillovers between environmentally sustainable assets and quantify the value-at-risk of the portfolios across various frequencies.

To accomplish these objectives, this paper utilizes a connectedness index-based TVP-VAR model and applies the wavelet-based VaR ratio to daily data spanning from January 2018 to September 2023.

The empirical findings reveal a notable increase in the connectedness index between green stocks and green bonds during the COVID-19 crisis, signifying evidence of a contagion effect. The portfolio’s risk ratio also exhibited a sharp rise amid the pandemic, particularly over medium and long-term horizons, driven by increased spillover among green assets. Notably, our analysis indicates that green bonds influence the connectedness system between green stocks and the value-at-risk ratio, reducing volatility spillover and portfolio risk ratios across various investment horizons. These results highlight the role of green bonds as an effective diversification asset against the risks associated with green equities.

This research investigates the dynamic connectedness and value-at-risk ratio between eight green sectoral renewable energy and non-energy equities and green bonds. We put forward some portfolio implications for green investors with an environmental consciousness who desire to decarbonize their portfolios and mitigate environmental issues.

This paper aims to examine the volatility connectedness between energy and agricultural commodities across different quantiles and time horizons.

This study uses the quantile frequency connectedness approach on daily data spanning from January 2019 to November 2023.

The results indicate a sharp increase in total connectedness during the COVID-19 crisis and the Russian−Ukrainian conflict, suggesting that both the crisis and the war contribute to volatility spillover among energy and soft commodities. In fact, the findings suggest that, in the short term, the effects of the pandemic have a greater impact on dynamic risk spillover than those of the war. However, over the long term, the consequences of geopolitical tensions related to the war exert a more significant influence compared to the effects of the pandemic.

This study confirms that energy market prices and oil uncertainty play a significant role in explaining fluctuations in agricultural commodities across diverse timeframes, frequencies and quantiles. Particularly, at extreme quantiles, the results indicate that large shocks have a more pronounced impact than small shocks. These findings hold important implications for policymakers and market participants.

This paper aims to examine whether International Financial Reporting Standards (IFRS) adoption and corporate governance attributes increase the management earnings forecasts’ accuracy disclosed in prospectuses for French Initial Public Offerings (IPOs).

The analysis is based on cross-sectional regression explaining the absolute forecast errors by using 45 French firms that made IPOs between 2005 and 2016 in two French financial markets: Euronext and Alternext.

In agreement with the agency theory and the signaling theory, the authors find that the IFRS adoption and the effective corporate governance, proxied by the board characteristics, increase the accuracy of management forecasts. As a result, this latter gives a credible signal in constructing and sustaining shareholders’ trust on the transparency and the reliability of such financial information.

It is plausible that the limited size of the sample represents a limitation of this study. Another limitation is that no other corporate governance attributes such as board meeting frequency, audit committee measures and ownership structure are used.

Shareholders can take benefit from management forecasts accuracy to structure their investment portfolios efficiently to allocate their funds more effectively and mitigate the costs of adverse selection that they have to face. Furthermore, the authors expect the findings to be interesting to IPO firms, as this study highlights the efficiency of larger and independent boards in decreasing managerial discretion, increasing disclosure quality and supervising management. The results could encourage GAAP-adopters countries to move toward IFRS, as this research reinforces the role of IFRS in enhancing the quality of financial disclosure by offering the required information for shareholders.

This study is important because the potential investors should assess management earnings forecasts accuracy before they consider it when evaluating IPO firms. Also, this paper has some implications for the financial market. It is recommended that future investors pay more attention, when assessing the accuracy of management earnings forecasts, to the accounting regulations of the financial reporting along with the corporate governance mechanisms. Moreover, this study could incite French regulators to revise the AFEP-MEDEF code. Under this code, it could insist that larger and independent boards are more effective in performing their governing roles than smaller boards.

This study aims to investigate the effect of overconfident chief executive officers (CEOs) on corporate tax avoidance and whether this relationship is affected by institutional and family ownership.

Using a sample of French-listed firms from 2009 to 2021, the authors find that firms managed by overconfident CEOs engage in more tax avoidance practice.

The authors further find that institutions and families are likely to discourage tax avoidance practices, paying close attention to their long-term horizons and reputational concerns. Overall, the authors' findings shed light on the monitoring role of institutional and family shareholders in restraining the effect of CEO behavioral bias on companies' tax avoidance.

To the authors' knowledge, no study has investigated the impact of managerial overconfidence on the tax behavior of French firms. The authors also extend the growing literature regarding managerial effects by providing new evidence that French firms held by concentrated institutional and family ownership curtail CEO overconfidence behavior toward corporate tax avoidance practices.