Prediction of Peruvian Companies' Stock Prices Using Machine Learning

Jose Antonio Espíritu Pera, Alexis Oneil Ibañez Diaz, Yvan Jesus Garcia Lopez, José Antonio Taquía Gutiérrez

Producción científica: Capítulo del libro/informe/acta de congresoArticulo (Contribución a conferencia)revisión exhaustiva


Nowadays, the challenges that covid-19 has generated to the financial community that operates within the stock market
has generated a greater uncertainty in the profitability and consequently has made this practice more difficult. To
overcome that problem the present study aims to develop a model that facilitates this work; this model uses the SVR
regression algorithm and through technical indicators provide us with the possible trend that the stock may take in the
future and thus suggest that the investor in question buys, sells or holds the stock in view of that result. As a result of
the project, it was proposed to use 7 technical indicators RSI, MACD, ROC, WMA, OBV, the Williams indicator and
the stochastic oscillator that determine the current market condition. After validating the model, it was concluded that
there are different Peruvian companies that have been able to overcome the difficulties of the pandemic with enough
growth potential during this post-covid period.
Idioma originalInglés estadounidense
Título de la publicación alojadaPrediction of Peruvian Companies' Stock Prices Using Machine Learning
Lugar de publicaciónAUSTRALIA
EditorialIEOM Society International
Número de páginas11
ISBN (versión digital)979-8-3507-0542-3
EstadoPublicada - 15 mar. 2023

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