AI in finance refers to the applications of AI techniques in financial businesses. This area has
attracted attention for decades, with both classic and modern AI techniques applied to …

Financial time series forecasting is undoubtedly the top choice of computational intelligence
for finance researchers in both academia and the finance industry due to its broad …

Predictions of stock and foreign exchange (Forex) have always been a hot and profitable
area of study. Deep learning applications have been proven to yield better accuracy and …

Though recurrent neural networks (RNN) outperform traditional machine learning algorithms
in the detection of long-term dependencies among the training instances, such as in term …

Stock-market prediction using machine-learning technique aims at developing effective and
efficient models that can provide a better and higher rate of prediction accuracy. Numerous …

Stocks that are fundamentally connected with each other tend to move together. Considering
such common trends is believed to benefit stock movement forecasting tasks. However, such …

Long-short term memory (LSTM) network is one of the state-of-the-art models to forecast the
movement of financial time series (FTS). However, existing LSTM networks do not perform …

An accurate exchange rate forecasting and its decision-making to buy or sell are critical
issues in the Forex market. Short-term currency rate forecasting is a challenging task due to …

Recent advances in machine learning are finding commercial applications across many
industries, not least the finance industry. This paper focuses on applications in one of the …

Numerous machine learning models have been developed to achieve the 'real-life'financial
objective of optimising the risk/return profile of investment strategies. In the current article:(a) …