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Can the Representativeness Heuristic Explain the Asset Growth Anomaly?

He, Miao; Kapadia, Nishad; Tice, Sheri - 2021

We find that the low average returns to firms with high asset growth are consistent with two key implications of models of diagnostic investor expectations (e.g., Bordalo, Gennaioli, La Porta, and Shleifer, 2019) that formalize the representativeness heuristic of Kahneman and Tversky (1972)....

Persistent link: https://www.econbiz.de/10013249516

The locomotive assignment problem : a survey on optimization models

Piu, F.; Speranza, Maria Grazia - In: International transactions in operational research : … 21 (2014) 3, pp. 327-352

Persistent link: https://www.econbiz.de/10010373867

Sectoral digital intensity and GDP growth after a large employment shock : a simple extrapolation exercise

Gallipoli, Giovanni; Makridis, Christos A. - In: The Canadian journal of economics : the journal of the … 55 (2022), pp. 446-479

Persistent link: https://www.econbiz.de/10013193612

Nowcasting Chinese GDP in a data-rich environment : lessons from machine learning algorithms

Zhang, Qin; Ni, He; Xu, Hao - In: Economic modelling 122 (2023), pp. 1-15

Persistent link: https://www.econbiz.de/10014388697

Blockchain technology-based FinTech banking sector involvement using adaptive neuro-fuzzy-based K-nearest neighbors algorithm

Rjoub, Husam; Adebayo, Tomiwa Sunday; Kirikkaleli, Dervis - In: Financial innovation : FIN 9 (2023) 1, pp. 1-23

an adaptive neuro-fuzzy-based K-nearest neighbors' algorithm. The chaotic improved foraging optimization algorithm is … proposed algorithm is compared with existing approaches to demonstrate its efficiency. The findings showed that it achieved 91 …

Persistent link: https://www.econbiz.de/10014289064