Showing 1 - 10 of 363
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 …
Persistent link: https://www.econbiz.de/10011488820
Persistent link: https://www.econbiz.de/10014581568
Persistent link: https://www.econbiz.de/10014544073
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 …
Persistent link: https://www.econbiz.de/10012175006
Persistent link: https://www.econbiz.de/10011968724
Persistent link: https://www.econbiz.de/10011417732
Persistent link: https://www.econbiz.de/10010462052
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...
Persistent link: https://www.econbiz.de/10012800743
Persistent link: https://www.econbiz.de/10012694117
This paper presents different deep neural network architectures designed to forecast the distribution of returns on a portfolio of U.S. Treasury securities. A long short-term memory model and a convolutional neural network are tested as the main building blocks of each architecture. The models...
Persistent link: https://www.econbiz.de/10012008287