An LSTM and GRU based trading strategy adapted to the Moroccan market. [PDF]
J Big Data, 2021 Forecasting stock prices is an extremely challenging job considering the high volatility and the number of variables that influence it (political, economical, social, etc.).
Touzani Y, Douzi K.
europepmc +2 more sources
Structural break-aware pairs trading strategy using deep reinforcement learning. [PDF]
J Supercomput, 2022 Pairs trading is an effective statistical arbitrage strategy considering the spread of paired stocks in a stable cointegration relationship. Nevertheless, rapid market changes may break the relationship (namely structural break), which further leads to ...
Lu JY +8 more
europepmc +2 more sources
Intelligent Algorithmic Trading Strategy Using Reinforcement Learning and Directional Change
IEEE Access, 2021 Designing a profitable trading strategy plays a critical role in algorithmic trading, where the algorithm can manage and execute automated trading decisions.
Monira Essa Aloud, Nora Alkhamees
doaj +2 more sources
IEEE Access, 2019 To determine an appropriate trading time for buying or selling stocks is always a difficult task. The common way to deal with it is using trading strategies formed by technical or fundamental indicators.
Chun-Hao Chen +3 more
doaj +2 more sources
Intelligent Dynamic Backlash Agent: A Trading Strategy Based on the Directional Change Framework
Algorithms, 2018 The Directional Changes (DC) framework is an approach to summarize price movement in financial time series. Some studies have tried to develop trading strategies based on the DC framework.
Amer Bakhach +3 more
doaj +2 more sources
Multi-Timescale Trading Strategy for Renewable Power to Ammonia Virtual Power Plant in the Electricity, Hydrogen, and Ammonia Markets [PDF]
IEEE Transactions on Energy Markets, Policy and Regulation, 2023 Renewablepower to ammonia (RePtA) is a prominent zero-carbon pathway for decarbonization. Due to the imbalance between renewables and production energy demand, the RePtA system relies on electricity exchange with the power grid.
Sirui Wu +7 more
semanticscholar +1 more source
Using a Graph-based Method for Detecting the Optimal Turning Points of Financial Time Series [PDF]
تحقیقات مالی, 2022 Objective: One of the concerns of financial market investors is adopting a profitable trading strategy, which is based on profitable turning points (TPs). To achieve this target, it is necessary to predict TPs.
Fateme Yazdani +2 more
doaj +1 more source
Trade Ease With Machine Learning and AWS
IEEE Access, 2023 Global trading is undergoing significant changes, necessitating modifications to the trading strategies. This study presents a newly developed cloud-based trading strategy that uses Amazon Web Services (AWS), machine learning (ML), and data science to ...
Kamurthi Ravi Teja, Chuan-Ming Liu
doaj +1 more source
Energy trading strategy of community shared energy storage
Electrical Engineering, 2023 One of the challenges of renewable energy is its uncertain nature. Community shared energy storage (CSES) is a solution to alleviate the uncertainty of renewable resources by aggregating excess energy during appropriate periods and discharging it when ...
M. Khojasteh +3 more
semanticscholar +1 more source
Optimal Price-maker Trading Strategy of Wind Power Producer Using Virtual Bidding
Journal of Modern Power Systems and Clean Energy, 2021 This paper proposes a stochastic optimization model for generating the optimal price-maker trading strategy for awind power producer using virtual bidding, which is a kind of financial tool available in most electricity markets of the United States.
Dongliang Xiao +2 more
semanticscholar +1 more source