Applying Fuzzy Logic To Stock Price Prediction
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Applying Fuzzy Logic To Stock Price Prediction
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Author : Ali Ghodsi Boushehri
language : en
Publisher:
Release Date : 2000
Applying Fuzzy Logic To Stock Price Prediction written by Ali Ghodsi Boushehri and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Fuzzy logic categories.
The major concern of this study is to develop a system that can predict future prices in the stock markets by taking samples of past prices. Stock markets are complex. Their dramatic movements, and unexpected booms and crashes, dull all traditional tools. This study attempts to resolve such complexity using the subtractive clustering based fuzzy system identification method, the Sugeno type reasoning mechanism, and candlestick chart analysis. Candlestick chart analysis shows that if a certain pattern of prices occurs in the market, then the stock price will increase or decrease. Inspired by the key information that candlestick analysis uses, this study assumes that everything impacting a market, from economic factors to politics, is distilled into market price. The model presented in this study elicits, from historical data price, some of the rules which govern the market, and shows that rules which are drawn from a particular stock are to some extent independent of that stock, and can be generalized and applied to other stocks regardless of specific time or industrial field. The experimental results of this study in the duration of 3 months reveals that the model can correctly predict the direction of the market with an average hit ratio of 87%. In addition to daily prediction, this model is also capable of predicting the open, high, low, and close prices of desired stock, weekly and monthly.
Applying Fuzzy Logic To Stock Price Prediction
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Author :
language : en
Publisher:
Release Date : 2000
Applying Fuzzy Logic To Stock Price Prediction written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with categories.
Stock Market Forecasting Using Fuzzy Logic
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Author :
language : en
Publisher:
Release Date : 2016
Stock Market Forecasting Using Fuzzy Logic written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Electronic books categories.
Forecasting is a very tedious task and many factors should be taken into consideration for proper predictions. The chaotic nature and randomness of stock market index values, makes forecasting stock market values a very challenging task. Financial forecasting can be done in many areas such as currencies, commodities, bonds and stocks. This project is restricted to stocks; and in particular the SENSEX, National Stock Exchange of India. Prediction of the stock market can be of interest to investors, traders and researchers. To take appropriate buy and sell decision for a stock knowing the momentum of the stock market can be of great help. Forecasting becomes difficult considering highly unpredictable attributes such as historical prices, company orders, company earnings, company revenue, etc. The proposed fuzzy model identifies the momentum of the stock index for next 5 days by considering the 14-day historic data as the base. The fuzzy model is applied to the close and open values and a system is designed which takes input as 14-day data and outputs the future moment as Up(bearish), Neural and Down(Bullish). The results found closely match with the expected real-world values when compared with already known data.
Type 3 Fuzzy Logic In Time Series Prediction
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Author : Oscar Castillo
language : en
Publisher: Springer Nature
Release Date :
Type 3 Fuzzy Logic In Time Series Prediction written by Oscar Castillo and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Applying Fuzzy Logic For The Digital Economy And Society
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Author : Andreas Meier
language : en
Publisher: Springer
Release Date : 2019-02-28
Applying Fuzzy Logic For The Digital Economy And Society written by Andreas Meier and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-28 with Business & Economics categories.
This edited book presents the state-of-the-art of applying fuzzy logic to managerial decision-making processes in areas such as fuzzy-based portfolio management, recommender systems, performance assessment and risk analysis, among others. Presenting the latest research, with a strong focus on applications and case studies, it is a valuable resource for researchers, practitioners, project leaders and managers wanting to apply or improve their fuzzy-based skills.
Neuro Fuzzy Based Stock Market Prediction System
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Author : M. Gunasekaran
language : en
Publisher:
Release Date : 2013
Neuro Fuzzy Based Stock Market Prediction System written by M. Gunasekaran and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with categories.
Neural networks have been used for forecasting purposes for some years now. Often arises the problem of a black-box approach, i.e. after having trained neural networks to a particular problem, it is almost impossible to analyze them for how they work. Fuzzy Neuronal Networks allow adding rules to neural networks. This avoids the black-box-problem. Additionally they are supposed to have a higher prediction precision in unlike situations. Applying artificial neural network, genetic algorithm and fuzzy logic for the stock market prediction has attracted much attention recently, which has better correlated the non-quantitative factors with the stock market performance. However these approaches perform less satisfactorily due to the memoryless nature of the stock market performance. In this paper, we propose a data compression-based portfolio prediction model hybridized with the fuzzy logic and genetic algorithm. In the model, the quantifiable microeconomic stock data are first optimized through the genetic algorithms to generate the most effective microeconomic data in relation to the stock market performance.
Stock Market Trend Prediction Using Neural Networks And Fuzzy Logic
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Author : Maha Abdelrasoul
language : en
Publisher:
Release Date : 2016-11-22
Stock Market Trend Prediction Using Neural Networks And Fuzzy Logic written by Maha Abdelrasoul and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-22 with categories.
Fuzzy Logic For Business Finance And Management
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Author : George Bojadziev
language : en
Publisher: World Scientific
Release Date : 2007
Fuzzy Logic For Business Finance And Management written by George Bojadziev and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Business & Economics categories.
This is truly an interdisciplinary book for knowledge workers in business, finance, management and socio-economic sciences based on fuzzy logic. It serves as a guide to and techniques for forecasting, decision making and evaluations in an environment involving uncertainty, vagueness, impression and subjectivity. Traditional modeling techniques, contrary to fuzzy logic, do not capture the nature of complex systems especially when humans are involved. Fuzzy logic uses human experience and judgement to facilitate plausible reasoning in order to reach a conclusion. Emphasis is on applications presented in the 27 case studies including Time Forecasting for Project Management, New Product Pricing, and Control of a Parasit-Pest System.
Stock Price Prediction A Referential Approach On How To Predict The Stock Price Using Simple Time Series
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Author : Dr.N.Srinivasan
language : en
Publisher: Clever Fox Publishing
Release Date :
Stock Price Prediction A Referential Approach On How To Predict The Stock Price Using Simple Time Series written by Dr.N.Srinivasan and has been published by Clever Fox Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on with Business & Economics categories.
This book is about the various techniques involved in the stock price prediction. Even the people who are new to this book, after completion they can do stock trading individually with more profit.
An Improved Intelligent Model For Stock Market Time Series Data Prediction Using Fuzzy Logic And Deep Neural Networks
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Author : Parniyan Mousaie
language : en
Publisher:
Release Date : 2023
An Improved Intelligent Model For Stock Market Time Series Data Prediction Using Fuzzy Logic And Deep Neural Networks written by Parniyan Mousaie and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.
It is vitally crucial to establish a method that can accurately forecast prices on the stock exchange market because of the influence the stock market has on the country's ability to raise capital and advance its economic growth. On the stock market, a great number of sensitivity factors are connected to price movement, which is why the progressions associated with such a phenomenon are routinely evaluated. Several neural network models have recently been used to forecast stock prices. In this research, the data related to active companies in the stock market was used to evaluate research questions. Also, the neural network technique was used to look at all data from the market index, fuzzy neural network model, and long short-term memory (LSTM) model from 2020 to 2021. Accordingly, this study aims to forecast the stock price and give a dynamic model with fewer errors using integrated factors, the technical, cardinal, and economic assessment of the market index using the neural network technique. This will be accomplished by utilizing the neural network method. The findings demonstrated that if the combined data of basic analytical factors was used further, we would not only have better training and receive better results, but we would also be able to decrease the prediction error.