Background: Stock market prediction is one of the most challenging tasks since the financial
time series is highly volatile, noisy, non-linear and dynamic in nature. Long-Short-Term …

The study tries to estimate the returns using three known models, namely the single-index
model, capital asset pricing model (CAPM), and arbitrage pricing theory (APT) model. The …

This study uses artificial neural network (ANN) in forecasting the NIFTY. The paper trains
several ANN by using back propagation algorithm and they were assessed. The study uses …

The expansion of its use in numerous service industries is a result of technological
advancements and people'growing reliance on modern technology and artificial …

The development of the financial industry does not depend on speculation and high returns,
but on bringing convenience to people's lives. The development of Internet Finance in the …

Big data has become a trend in our world today. The rise in data production rate, which has
as consequence the increase in data quantity, comes with many important challenges, one …

Making stock market returns predictions are regarded as an efficient tool for financial risk
management and portfolio diversification. Various methods of forecasting for investment …

A model that combines econometric ARMA model with new machine learning techniques
will be developed to build an efficient portfolio, composed of Italian FTSE-MIB stocks. The …

Machine learning and artificial intelligence have become an integral part of people's culture,
influencing the lives of most people today. Machine learning is a subset of data science that …