This study proposes a multiple kernel learning (MKL)-based regression model for crude oil spot price forecasting and trading. We used a well-known trend-following technical analysis indicator, the moving average convergence and divergence (MACD) indicator, for extracting features from original spot prices. Additionally, we factored in the possibility that movements of target crude oil prices ma...

Gold and Bitcoin are two common investments in the market. Investors profit from capital market through specific trading strategies. Based on previous price data, this paper established a prediction-decision model, which provides investors with an optimal strategy effectively improves return investment. To begin with, we use past daily of gold bitcoin to calculate Bollinger band, DMA, MACD char...

Decision making process in stock trading is a complex one. There are numbers of technical indicators that are used by traders to study trends of the market and make buying and selling decisions based on their observations. This research seeks to deploy fuzzy inference to stock market, with four indicators used in technical analysis to aid in the decision making process in order to deal with pro...

The main motivation for this paper is to introduce a novel hybrid method for the prediction of the directional movement of financial assets with an application to the ASE20 Greek stock index. Specifically, we use an alternative computational methodology named Evolutionary Support Vector Machine (ESVM) Stock Predictor for modeling and trading the ASE20 Greek stock index extending the universe of...

The present paper aims in investigating the performance of state-of-the-art machine learning techniques in trading with the EUR/USD exchange rate at the ECB fixing. For this purpose, five supervised learning classification techniques (K-Nearest Neighbors algorithm, Naïve Bayesian Classifier, Artificial Neural Networks, Support Vector Machines and Random Forests) were applied in the problem of t...

In this research, we provided an answer to a very important trading question, what is the optimal number of technical tools in order achieve best results for both swing trade that uses daily bars and intraday minutes bars? We designed Machine Learning (ML) systems can four major cryptocurrencies: Bitcoin, Ethereum, BNB, Solana. found more indicators do not necessarily mean better performance. S...

The study investigated the effectiveness of technical analysis indicators in trading spot exchange rates emerging economies’ currencies under integration with artificial neural networks (ANN) and quantitative testing these indicators’ success this matter goal rationalizing decisions. period was from January 2012 to November 2022 for twenty-four against US dollar. Based on four indicators: simpl...

Working memory is a key executive function for flying an aircraft. This function is particularly critical when pilots have to recall series of air traffic control instructions. However, working memory limitations may jeopardize flight safety. Since the functional near-infrared spectroscopy (fNIRS) method seems promising for assessing working memory load, our objective is to implement an on-line...

In this work we are proposing a trading system where fuzzy logic is applied not only for defining the trading rules, but also for managing the capital to invest. In fact, two fuzzy decision support systems are developed. The first one uses fuzzy logic to design the trading rules and to apply the stock market technical indicators. The second one enhances this fuzzy trading system adding a fuzzy ...