PurposeThis paper examines the effects of managerial optimism on corporate cash holdings.Design/methodology/approachThe authors construct a novel measure of managerial optimism based on the linguistic tone of annual reports by applying a Naïve Bayesian Machine Learning algorithm to non-numeric parts of Vietnamese listed firms' reports from 2010 to 2016. The paper employs firm and year fixed effects model and also uses the generalized method of moments estimation as robustness checks.FindingsThe authors find that the cash holding of firms managed by optimistic managers is higher than the cash holdings of firms managed by non-optimistic managers. Managerial optimism also influences corporate cash holdings through internal cash flows and the current year’s capital expenditures. Although the authors find no evidence that optimistic managers hold more cash to finance future growth opportunities in general, optimistic managers hold more cash for near future investment opportunities than non-optimistic managers do.Research limitations/implicationsThe novel measure proposed in this study is expected to provide great potential for future finance studies investigating the relation between managerial traits and corporate policies since it is applicable for any levels of financial market development. In addition, the findings highlight the important role, both direct and indirect, of managerial optimism on cash holdings. Related future research should take this psychological trait into account to gain a better understanding of corporate cash holding.Originality/valueThis paper helps to extend the literature on managerial optimism measurement by introducing a new measure of managerial optimism based on the linguistic tone of annual reports. Furthermore, this is among the first studies directly linking annual report linguistic tone to cash holding. The paper also provides new evidence regarding how managerial optimism affects the relationship between the firm's growth opportunities and cash holding, given that mispricing corrections are naturally uncertain.

PurposeThis paper examines the role of the annual report’s linguistic tone in predicting future firm performance in an emerging market, Vietnam.Design/methodology/approachBoth manual coding approach and the naïve Bayesian algorithm are employed to determine the annual report tone, which is then used to investigate its impact on future firm performance.FindingsThe study finds that tone can predict firm performance one year ahead. The predictability of tone is strengthened for firms that have a high degree of information asymmetry. Besides, the government’s regulatory reforms on corporate disclosures enhance the predictive ability of tone.Research limitations/implicationsThe study suggests the naïve Bayesian algorithm as a cost-efficient alternative for human coding in textual analysis. Also, information asymmetry and regulation changes should be modeled in future research on narrative disclosures.Practical implicationsThe study sends messages to both investors and policymakers in emerging markets. Investors should pay more attention to the tone of annual reports for improving the accuracy of future firm performance prediction. Policymakers should regularly revise and update regulations on qualitative disclosure to reduce information asymmetry.Originality/valueThis study enhances understanding of the annual report’s role in a non-Western country that has been under-investigated. The research also provides original evidence of the link between annual report tone and future firm performance under different information asymmetry degrees. Furthermore, this study justifies the effectiveness of the governments’ regulatory reforms on corporate disclosure in developing countries. Finally, by applying both the human coding and machine learning approach, this research contributes to the literature on textual analysis methodology.

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