Stock trend prediction is one of the most widely investigated and challenging problems for
investors and researchers. Since the convolutional neural network (CNN) was introduced to …

Many researchers attempt to accurately predict stock price trends using technologies such
as machine learning and deep learning to achieve high returns in the stock market …

Prediction with higher accuracy is vital for stock market prediction. Recently, considerable
amount of effort has been poured into employing machine learning (ML) techniques for …

With the price of Bitcoin, Ethereum, and many other cryptocurrencies climbing, the
cryptocurrency market has become the most popular investment area in recent years. Unlike …

How to construct a promising portfolio to reduce the risk of investment and to improve returns
has markedly attracted scholars' attention. Firstly, it is hard to choose prospective set of …

With T+ 0 and short selling mechanism, the stock index futures are attractive to short-term
traders in China, where stocks cannot be liquidated within the day and are difficult to short …

The prediction of stock price has always been a main challenge. The time series of stock
price tends to exhibit very strong nonlinear characteristics. In recent years, with the rapid …

This study proposes a novel approach for modeling financial time series, concentrating on
data pre-processing and selecting effective features in conventional and proposed modeling …

Accurate prediction of the stock market trend can assist efficient portfolio and risk
management. In recent years, with the rapid development of deep learning, it can make the …

In this design study, we present IRVINE, a Visual Analytics (VA) system, which facilitates the
analysis of acoustic data to detect and understand previously unknown errors in the …