This paper proposes machine learning-based option pricing models that incorporate firm characteristics. We employ two semi-parametric models, one that uses machine learning to predict the implied volatility and the other to correct the pricing error of the Black-Scholes model and use 114 firm...

Managerial rhetoric portrayed as narrative disclosure of research and development (R&D) activities in 10-K filings is positively related to one-year ahead stock price crash risk. The positive relation between the narrative R&D disclosure and future crash risk is heightened for firms with...

This study takes Cyprus as a case country to examine the role of financial literacy for financial resilience in the pandemic period. Responses to the survey questions to assess the level of financial literacy show that in 2021 less than 4 out of 10 respondents had a good financial knowledge...

Using a textual measure of firms’ customer orientation (CUSTOR) constructed from 10-K filings, we document a positive and economically significant relation between CUSTOR and stock returns in crisis periods. High-CUSTOR firms outperform low-CUSTOR firms by 1.5% per month during the financial...

We employ extreme value theory to identify stock price crashes, featuring low-probability events that produce large, firm-specific negative outliers in the conditional distribution. Traditional methods employ approximations under Gaussian assumptions and central moments. This is inherently...

This study takes Cyprus as a case country to examine the role of financial literacy for financial resilience in the pandemic period. Responses to the survey questions to assess the level of financial literacy show that in 2021 less than 4 out of 10 respondents had a good financial knowledge...