IHS Markit is building out its analytics to more than double the number of companies covered by its dividend forecasting service.
The model uses machine learning to apply the methodologies of the dividend forecasting team to process a range of inputs and proxies, including company guidance, historical patterns, industry and peer group trends, consensus forecasts and other datasets from IHS Markit.
The model, enabling the expanded dividend coverage, was developed in partnership with the data science team at IHS Markit.
The expanded global service covers 28,000 stocks in more than 90 markets, providing up to five years of dividend forecast data for each stock covered.
Alessandro Ferretti, head of dividend products at IHS Markit, said: “Combining cutting edge analytics with our more than 15 years of dividend forecasting expertise offers index providers, derivatives desks, asset managers and hedge funds access to the broadest set of dividend forecasts available for large-, mid- and small-cap stocks globally, including frontier markets.”
Yaacov Mutnikas, chief data scientist and chief technology officer at IHS Markit, added: “Using machine learning, advanced statistical modelling and time series analysis techniques to uncover patterns in multiple datasets helps us dramatically expand coverage and also retain the analytical rigour our dividend forecasting team has developed over many years.”
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