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Purpose The aim of this study is to evaluate of the predictive ability of goodwill and other intangible assets on forecasting corporate profitability. Subsequently, this study compares the efficiency of deep learning model to that of other machine learning models such as random forest (RF) and support vector machine (SVM) as well as traditional statistical methods such as the linear regression model. Design/methodology/approach Studies confirm that goodwill and intangibles are valuable assets that give companies a competitive advantage to increase profitability and shareholders’ returns. Thus, by using as sample Greek-listed financial data, this study investigates whether or not the inclusion of goodwill and intangible assets as input variables in this modified deep learning models contribute to the corporate profitability prediction accuracy. Subsequently, this study compares the modified long-short-term model with other machine learning models such as SVMs and RF as well as the traditional panel regression model. Findings The findings of this paper confirm that goodwill and intangible assets clearly improve the performance of a deep learning corporate profitability prediction model. Furthermore, this study provides evidence that the modified long short-term memory model outperforms other machine learning models such as SVMs and RF , as well as traditional statistical panel regression model, in predicting corporate profitability. Research limitations/implications Limitation of this study includes the relatively small amount of data available. Furthermore, the aim is to challenge the authors’ modified long short-term memory by using listed corporate data of Greece, a code-law country that suffered severely during the recent fiscal crisis. However, this study proposes that future research may apply deep learning corporate profitability models on a bigger pool of data such as STOXX Europe 600 companies. Practical implications Subsequently, the authors believe that their paper is of interest to different professional groups, such as financial analysts and banks, which the authors’ paper can support in their corporate profitability evaluation procedure. Furthermore, as well as shareholders are concerned, this paper could be of benefit in forecasting management’s potential to create future returns. Finally, management may incorporate this model in the evaluation process of potential acquisitions of other companies. Originality/value The contributions of this work can be summarized in the following aspects. This study provides evidence that by including goodwill and other intangible assets in the authors’ input portfolio, prediction errors represented by root mean squared error are reduced. A modified long short-term memory model is proposed to predict the numerical value of the profitability (or the profitability ratio) in contrast to other studies which deal with trend predictions, i.e. the binomial output result of positive or negative earnings. Finally, posing an extra challenge to the authors’ deep learning model, the authors’ used financial statements according to International Financial Reporting Standard data of listed companies in Greece, a code-law country that suffered during the recent fiscal debt crisis, heavily influenced by tax legislation and characterized by its lower investors’ protection compared to common-law countries.

ÖZETMigreni olan kişiler migreni olmayan kişilere oranla farklı görsel ve işitsel bilgioluştururlar. Migren atakları arasında kognitif etkilenmeyi gösteren kortikal fonksiyonlardaelektrofizyolojik ve fonksiyonel değişiklikler saptanırken bazı çalışmalarda kortikaldeğişiklikler veya kognitif performansta azalma saptanmamıştır. Çalışmamızda migreninkognitif işlevler üzerine etkisinin olup olmadığı eğer varsa hangi işlevlerin etkilendiğiniaraştırmak amacıyla dikkat, bellek, dil, yürütücü işlevler, görsel ve mekansal işlevlerideğerlendiren nöropsikolojik testler ile görsel olaya ilişkin potansiyeller (OİEP) tetkikindekayıtlanan N2 ve P3 dalga latansları arasındaki ilişkiyi değerlendirmeyi amaçladık.Çalışmaya yaşları 16-45 arasında, migren tanısı alan 32 hasta (26 kadın, 6 erkek).alındı. Kontrol grubu olarak yaş ve eğitim düzeyi uyumlu 20 sağlıklı olgu seçildi. Beckdepresyon envanteri uygulanarak depresyonu olanlar çalışmaya alınmadı. OİEP tetkikindekontrol grubu ile karşılaştırıldığında migren grubunda Fz, Cz ve Pz `den kayıtla N2 (p=0.000)ve P3 (p=0.000) latansları kontrol grubuna oranla uzun bulunmuştur. En uzun N2 ve P3latansı Fz'den kayıtla elde edilmiş olup arkadan öne doğru gelindiğinde latansın uzadığısaptanmıştır. Hastalar migren tiplerine göre incelendiğinde auralı ve aurasız gruplara ait N2ve P3 latans ortalama değerleri açısından istatistiksel anlamlı fark saptanmamıştır (p0.05).Sonuç olarak migrende kognitif işlevler etkilenmektedir. OİEP tetkiki nörokognitiftestlerle kanıtlanan migrendeki kognitif etkilenmeyi destekler bulgular ortaya koymaktadır.OİEP migren için tek başına tanısal test olmamasına karşın özellikle kognitif süreci izlemekiçin önemli, uygulaması kolay, noninvaziv bir tekniktir .Anahtar Kelimeler: Migren, görsel olaya ilişkin potansiyeller, kognitif işlevler SUMMARYVISUAL EVENT RELATED POTENTIALS IN MIGRANEOUS PATIENTSIndividuals who experience migraine process visual and auditory informationdifferently from those without migraine. Functional and electrophysiologic alterations incortical functioning have been found during the migraine interval. However, not all studieshave found such cortical alterations or cognitive performance decrements. In our study, wehave aimed to examine whether migraine is associated with cognitive efficiency, if so, tocorrelate the neuropsychological tests of attention, memory, language, cognitiveefficiency,and visuospatial abilities with the latencies of N2 and P3 recorded on visualevent-related potentials (ERP).Thirty-two patients with the diagnosis of migraine ( 26 female, 6 male) age rangedbetween 16-45 and 20 controls with the similar age and educational state were included in thestudy. Patients with depression that was examined by Beck depression inventory wereexcluded. Migraine group had significantly longer latencies for N2 (p=0.000) and P3(p=0.000) waves recorded by Fz, Cz, and Pz electrodes when compared with the controlgroup. The longest latencies were recorded on Fz and the latencies were observed to be longerfrom back to the front. There was no statistically difference between the patients with andwithout aura (p>0.05)Neuropsychological battery was applied for both of the groups. The scores ofattention, memory, language, cognitive efficiency, and verbal paired associates in themigraine group were significantly lower compared with the control group and there was anegative correlation between the cognitive tests and the latencies of N2 and P3 (p=0.000).There was no statistically difference between the patients with and without aura (p>0.05).In conclusion, cognitive function is effected in migraine. ERP supports the cognitiveimpairment in the migraine that has been observed by the neuropsychological tests. ThoughERP is not a major test for the diagnosis of migraine, it is important for the follow-up of thecognitive abilities, and is a noninvasive technique that can be applied easily.Key words: Migraine, visual event-related potentials, cognitive functions 86