In this literature review, we investigate machine learning techniques that are applied for
stock market prediction. A focus area in this literature review is the stock markets …

The search for models to predict the prices of financial markets is still a highly researched
topic, despite major related challenges. The prices of financial assets are non-linear …

Stock price prediction is an important issue in the financial world, as it contributes to the
development of effective strategies for stock exchange transactions. In this paper, we …

Financial time series prediction has many applications in economics, but producing
profitable strategies certainly has a special place among them, a daunting challenge …

Temperature forecasting has been a consistent research topic owing to its significant effect
on daily lives and various industries. However, it is an ever-challenging task because …

Prediction of oil prices is an implausible task due to the multifaceted nature of oil markets.
This study presents two novel hybrid models to forecast WTI and Brent crude oil prices using …

This paper aims to investigate how Machine Learning (ML) techniques perform in the
prediction of cryptocurrency prices. We answer if Support Vector Machines (SVM) and …

Several models have been presented to solve the financial time series forecasting problem.
However, even with sophisticated techniques, a dilemma arises from all these models …

Predicting intraday stock jumps is a significant but challenging problem in finance. Due to
the instantaneity and imperceptibility characteristics of intraday stock jumps, relevant studies …

Credit default swap which reflects the credit risk of a firm is one of the most frequently traded
credit derivatives. In this paper, we conduct a comprehensive study to verify the predictive …