Forecasting stock prices using hidden Markov models and support vector regression with firefly algorithm

Forecasting stock prices using hidden Markov models and support vector regression with firefly algorithm

Many models have been proposed for forecasting stock prices. One is the Autoregressive Integrated Moving Average (ARIMA) model which is extensively used in the fields of economics and finance (Ariyo et al., 2014). In the Philippines, the Philippine Stock Exchange (PSE) forecasts future stock price m...

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Bibliographic Details
Main Authors: Cantuba, Joshua Reno S., Nicolas, Patrick Emilio U.
Format: text
Language:English
Published: Animo Repository 2016
Subjects:
Stocks > Prices > Philippines
Markov processes
Hidden Markov models
Box-Jenkins forecasting
MAD (Computer program language)
Regression analysis
Algorithms
Mathematics
Online Access:https://animorepository.dlsu.edu.ph/etd_bachelors/18393
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Institution: De La Salle University
Language: English

Internet

https://animorepository.dlsu.edu.ph/etd_bachelors/18393

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