Examinando por Materia "Abnormal returns"

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    ÍtemAcceso Abierto
    Determinantes de la rentabilidad no esperada de las empresas bancarias que cotizan en la Bolsa de Valores de Lima
    (Grupo Editorial Espacios GEES 2021 C.A., 2017) Lizarzaburu, Edmundo R.; Burneo Farfan, Kurt; Guevara Medina, José A.
    This research proposes a theoretical framework focused on explaining the unexpected or "abnormal" return of the most representative banks of the Peruvian financial system, which also have shares listed on the Lima Stock Exchange. Likewise, this paper propose a number of explanatory variables such as the ratio of allowance for loan losses (PPP), size of the bank (TAM), asset liquidity (LIQ), leverage ratio (APL), efficiency in the management (EG), fee income (ICM) and general cost ratio (RCG). Thus, an independent linear regression is performed for each bank. Finally, we found that the level of assets is the significant variable in this analysis because it serves as a barrier for new and existing competitors.
  • Miniatura
    ÍtemSolo Metadatos
    Modeling and forecasting abnormal stock returns using the nonlinear Grey Bernoulli model
    (Universidad ESAN. ESAN Ediciones, 2018-06-01) Doryab, Bahar; Salehi, Mahdi
    Purpose – This study aims to use gray models to predict abnormal stock returns. Design/methodology/approach – Data are collected from listed companies in the Tehran Stock Exchange during 2005-2015. The analyses portray three models, namely, the gray model, the nonlinear gray Bernoulli model and the Nash nonlinear gray Bernoulli model. Findings – Results show that the Nash nonlinear gray Bernoulli model can predict abnormal stock returns that are defined by conditions other than gray models which predict increases, and then after checking regression models, the Bernoulli regression model is defined, which gives higher accuracy and fewer errors than the other two models. Originality/value – The stock market is one of the most important markets, which is influenced by several factors. Thus, accurate and reliable techniques are necessary to help investors and consumers find detailed and exact ways to predict the stock market.