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The study reports empirical evidence that artificial neural network based models are applicable to forecasting of stock … the artificial neural network based models outperformed the ARIMA based model in forecasting future developments of the … can be used as predictors for forecasting future values of the stock market returns given that the returns has memory of …
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Forecasting the stock returns in the emerging markets is challenging due to their peculiar characteristics. These … markets exhibit linear as well as nonlinear features and Conventional forecasting methods partially succeed in dealing with … which caters both the linear and nonlinear markets. This paper investigates the forecasting ability of ANN by using Fama and …
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We use machine learning methods to predict stock return volatility. Our out-of-sample prediction of realised volatility for a large cross-section of US stocks over the sample period from 1992 to 2016 is on average 44.1% against the actual realised volatility of 43.8% with an R2 being as high as...
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