Financial markets play an important role on the economical and social organization of
modern society. In these kinds of markets, information is an invaluable asset. However, with …

Context: The amount and diversity of data have increased drastically in recent years.
However, in certain situations, the data to which a trained Machine Learning model is …

The process of continuously reallocating funds into financial assets, aiming to increase the
expected return of investment and minimizing the risk, is known as portfolio management. In …

Real-world data streams pose a unique challenge to the implementation of machine
learning (ML) models and data analysis. A notable problem that has been introduced by the …

Portfolio management aims at maximizing the return on investment while minimizing risk by
continuously reallocating the assets forming the portfolio. These assets are not independent …

Many daily applications are generating massive amount of data in the form of stream at an
ever higher speed, such as medical data, clicking stream, internet record and banking …

Inducing adaptive predictive models in real-time from high throughput data streams is one of
the most challenging areas of Big Data Analytics. The fact that data streams may contain …

A time series is a sequence of observations collected over fixed sampling intervals. Several
real-world dynamic processes can be modeled as a time series, such as stock price …

With the development of industry and technology, the development of the environment and
cities has drawn lots of attention. Time series prediction plays a vital role in protecting the …

A financial market is a platform to produce data streams continuously and around 1. 145
Trillion MB of data per day. Estimation and the analysis of unknown or dynamic behaviors of …