Journal Article10.1007/S00500-016-2417-2
A novel technical analysis-based method for stock market forecasting
Yuh-Jen Chen,Yuh-Min Chen,Shiang Ting Tsao,Shu Fan Hsieh +3 more
- 01 Feb 2018
- Vol. 22, Iss: 4, pp 1295-1312
20
TL;DR: This study develops a novel technical analysis method for stock market forecasting to effectively promote forecasting accuracy, which can help investors to increase their decision support quality and profitability.
read more
Abstract: Owing to the dynamic changes of the stock market and numerous influences on stock prices, assessing stock prices has become increasingly difficult. Furthermore, when dealing with information on stocks, people tend to amplify the importance of available and self-correlative information, a habit that runs contrary to objective and reasonable investment decision-making. Therefore, how to use effective stock information to assist investors in making stock investment decisions is a major topic in stock investment. This study develops a novel technical analysis method for stock market forecasting to effectively promote forecasting accuracy, which can help investors to increase their decision support quality and profitability. Specifically, this study involves the following tasks: (1) design a technical analysis-based stock market forecasting process, (2) develop techniques related to technical analysis-based stock market forecasting, and (3) demonstrate and evaluate the developed technical analysis-based method for stock market forecasting. In developing techniques associated with the technical analysis-based stock market forecasting method, the techniques involve trend-based stock classification, adaptive stock market indicator selection, and stock market trading signal forecasting.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Behavioral finance factors and investment decisions: A mediating role of risk perception
Bashar Yaser Almansour,Sabri G. M. Elkrghli,Amar Yasser Almansour +2 more
- 15 Jun 2023
TL;DR: Behavioral finance factors and investment decisions in Saudi Arabia: Risk perception plays a significant role in mediating the impact of these factors on investment decision making.
47
Stock Prediction Based on Technical Indicators Using Deep Learning Model
01 Jan 2022
TL;DR: In this paper , an Evolutionary Deep Learning Model (EDLM) was proposed to identify stock trends' prices by using stock technical indicators (STIs) to study the stock market characteristics using STIs and make efficient trading decisions.
15
Application of online multitask learning based on least squares support vector regression in the financial market
TL;DR: In this article , a novel online multitask learning based on the least squares support vector regression (OMTL-LS-SVR) algorithm is proposed for multi-step-ahead financial time-series prediction.
14
Volatility Spillover Effects during Pre-and-Post COVID-19 Outbreak on Indian Market from the USA, China, Japan, Germany, and Australia
TL;DR: In this article , the authors examined volatility spillover effects from five prominent global stock markets to India's stock market during the pre-and-post COVID-19 outbreak using daily adjusted closing prices between January 2019 and September 2021 from six capital markets.
References
Optimization by Simulated Annealing
TL;DR: There is a deep and useful connection between statistical mechanics and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters), and a detailed analogy with annealing in solids provides a framework for optimization of very large and complex systems.
46.9K
Particle swarm optimization
James Kennedy,Russell C. Eberhart +1 more
- 06 Aug 2002
TL;DR: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced, and the evolution of several paradigms is outlined, and an implementation of one of the paradigm is discussed.
44.1K
Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces
Rainer Storn,Kenneth Price +1 more
TL;DR: In this article, a new heuristic approach for minimizing possibly nonlinear and non-differentiable continuous space functions is presented, which requires few control variables, is robust, easy to use, and lends itself very well to parallel computation.