Corporate reputation and market value: Evidence with generalized regression neural networks

• Effects of Corporate Reputation (CR) on firms’ market value are still controversial.
• Generalized Regression Neural Network (GRNN) is proposed to analyze such relationship.
• Presence of firms in CR rankings has a positive influence on financial performance.
• A higher CR is positively related with shares’ market value.
• GRNN gets more robust results than conventional Multiple Lineal Regression.

SummaryCorporate Reputation (CR) is a critical intangible asset for a firm. As a representation of its past actions and results, CR encompasses a number of features which conform the status of a firm regarding its competitors. This helps corporations not only to gain competitive advantages, but also to survive in times of economic turbulences. Despite its apparent relevance, it remains inconclusive and controversial whether CR affects firms’ financial performance, a key point for current and potential investors. Our aim is to provide new evidence that could shed some light in determining the role of CR in stock market valuation. Since most of the previous research focus on this relationship using Multiple Regression (MR), it has been suggested that more conclusive results could be achieved using neural networks, but it has not been proven yet to the best of our knowledge. Using a sample of Spanish listed companies in the period 2008–2011, MR and a neural network technique, Generalized Regression Neural Network (GRNN), have been used. At an empirical level, results show that the mere presence of a firm in a reputation ranking has a positive impact on its market value, and that also a higher CR have a favorable influence on financial performance. At a methodological level, results of GRNN have proven to be more robust than those obtained using traditional MR.