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Big Data Analytics And Management Forecasting Behavior, Beng Wee Goh, Na Li, Tharindra Ranasinghe
Big Data Analytics And Management Forecasting Behavior, Beng Wee Goh, Na Li, Tharindra Ranasinghe
Research Collection School Of Accountancy
This paper investigates whether the use of Big Data analytics by firms has a spillover effect on management forecasting behavior. Insights provided by Big Data could potentially improve firms’ ability to forecast earnings (supply channel) and investor demand for earnings information is likely higher for firms engaging in data analytics (demand channel). Using a text-based measure of firms’ commitments to and usage of Big Data analytics, we find that Big Data analytics usage is positively associated with the propensity to issue management earnings forecasts. Consistent with the “supply channel” explanation, we find that Big Data analytics usage is positively associated …
The Implications Of Firms' Derivative Usage On The Frequency And Usefulness Of Management Earnings Forecasts, John L. Campbell, Sean Shun Cao, Hye Sun Chang, Raluca Chiorean
The Implications Of Firms' Derivative Usage On The Frequency And Usefulness Of Management Earnings Forecasts, John L. Campbell, Sean Shun Cao, Hye Sun Chang, Raluca Chiorean
Research Collection School Of Accountancy
We investigate how firms' use of derivatives impacts voluntary disclosure and offer four main findings. First, we find that when firms begin using derivative instruments, they increase the frequency of management earnings forecasts. Second, using path analysis, we find a direct link between derivative usage and forecast frequency, as well as an indirect link through reduced earnings volatility. Third, we find that CEOs with more pronounced career concerns increase forecast frequency only when derivatives make earnings easier to forecast and find no evidence that investor demand drives the decision to provide a forecast. These results suggest that the primary mechanism …