An ARIMA time series model to forecast the revenue driver in equities in the stock market in Ecuador
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Abstract
This study investigates the feasibility of automating the process of buying and selling stocks on the Ecuadorian Stock Exchange, in order to democratize access to the market using, the CRISP-DM data mining methodology. The study analyzes the business model of local and foreign stockbrokers, which depends mainly on commissions, and suggests that automation could have a significant impact on the sector. Using the statistical software R, an ARIMA time series model is constructed to forecast transactions carried out in stockbrokers. The results show a decreasing trend in transactions and low liquidity levels in issuers.
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