How to generate better returns? try our stock predictor
Predict stock price movements and volatilities can help traders and portfolio managers generate more returns and build efficient portfolios.
Using machine learning techniques, especially statistical classifiers, for day ahead forecasting of the movement of daily close prices of a broad range of several hundreds of liquid stocks is generally not very successful. We suspect that one of the reasons for failure is the relatively high volatility of prices in the last minutes before the market closes. There have been some attempts to use less volatile daily high prices instead, but the studies concentrated only on a specific non-statistical machine learning approach on a small number of specific securities.
Akkiba uses Long Short-Term Memory (LSTM) network to predict stock prices.
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