Forecasting Ibovespa Index With Fuzzy Logic

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Forecasting Ibovespa Index With Fuzzy Logic

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Author : Cesar Duarte Souto-Maior
language : en
Publisher:
Release Date : 2006

Forecasting Ibovespa Index With Fuzzy Logic written by Cesar Duarte Souto-Maior and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with categories.

Much research has been done aiming the forecasting of stock market index values. However, very few researches focus on the predictability of the direction of stock market movements. This paper fills this gap through the estimation of a model, using fuzzy logic to forecast the direction of the movements of the São Paulo Stock Exchange index (IBOVESPA). To establish the rules of the model it was used an estimation period based on 1,000 daily data sets, corresponding to the period of January 8, 1997 to January 22, 2001. The test period was from January 23, 2001 to February 2, 2005. A software called FuzzyTECH® was used. Despite the estimated model produces an inexact answer, with a probabilistic output, it was possible to implement an investment strategy, using the IBOVESPA index as a proxy for an investment fund, which outperformed a buy-and-hold strategy.

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.

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.

Soft Computing And Signal Processing

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Author : V. Sivakumar Reddy
language : en
Publisher: Springer Nature
Release Date : 2020-03-13

Soft Computing And Signal Processing written by V. Sivakumar Reddy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-13 with Technology & Engineering categories.

This book presents selected research papers on current developments in the fields of soft computing and signal processing from the Second International Conference on Soft Computing and Signal Processing (ICSCSP 2019). The respective contributions address topics such as soft sets, rough sets, fuzzy logic, neural networks, genetic algorithms and machine learning, and discuss various aspects of these topics, e.g. technological considerations, product implementation, and application issues.

Proceedings Of Third International Conference On Intelligent Computing Information And Control Systems

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Author : A. Pasumpon Pandian
language : en
Publisher: Springer Nature
Release Date : 2022-03-14

Proceedings Of Third International Conference On Intelligent Computing Information And Control Systems written by A. Pasumpon Pandian and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-14 with Technology & Engineering categories.

This book is a collection of papers presented at the International Conference on Intelligent Computing, Information and Control Systems (ICICCS 2021). It encompasses various research works that help to develop and advance the next-generation intelligent computing and control systems. The book integrates the computational intelligence and intelligent control systems to provide a powerful methodology for a wide range of data analytics issues in industries and societal applications. The book also presents the new algorithms and methodologies for promoting advances in common intelligent computing and control methodologies including evolutionary computation, artificial life, virtual infrastructures, fuzzy logic, artificial immune systems, neural networks and various neuro-hybrid methodologies. This book is pragmatic for researchers, academicians and students dealing with mathematically intransigent problems.

Lecture Notes In Management Science

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Author : Kaveh Sheibani
language : en
Publisher: Tadbir Institute for Operational Research, Systems Design, and Financial Services
Release Date : 2008-09-15

Lecture Notes In Management Science written by Kaveh Sheibani and has been published by Tadbir Institute for Operational Research, Systems Design, and Financial Services this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-09-15 with Business & Economics categories.

These proceedings gather contributions presented at the 1st International Conference on Applied Operational Research (ICAOR 2008) in Yerevan, Armenia, September 15-17, 2008, published in the series Lecture Notes in Management Science (LNMS). The conference covers all aspects of Operational Research and Management Science (OR/MS) with a particular emphasis on applications.

Fuzzy Information Processing

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Author : Guilherme A. Barreto
language : en
Publisher: Springer
Release Date : 2018-07-03

Fuzzy Information Processing written by Guilherme A. Barreto and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-03 with Computers categories.

This book constitutes the thoroughly refereed proceedings of the 37th IFSA Conference, NAFIPS 2018, held in Fortaleza, Brazil, in July 2018. The 55 full papers presented were carefully reviewed and selected from 73 submissions. The papers deal with a large spectrum of topics, including theory and applications of fuzzy numbers and sets, fuzzy logic, fuzzy inference systems, fuzzy clustering, fuzzy pattern classification, neuro-fuzzy systems, fuzzy control systems, fuzzy modeling, fuzzy mathematical morphology, fuzzy dynamical systems, time series forecasting, and making decision under uncertainty.

Evolving Intelligent Systems

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Author : Plamen Angelov
language : en
Publisher: John Wiley & Sons
Release Date : 2010-03-25

Evolving Intelligent Systems written by Plamen Angelov and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-03-25 with Computers categories.

From theory to techniques, the first all-in-one resource for EIS There is a clear demand in advanced process industries, defense, and Internet and communication (VoIP) applications for intelligent yet adaptive/evolving systems. Evolving Intelligent Systems is the first self- contained volume that covers this newly established concept in its entirety, from a systematic methodology to case studies to industrial applications. Featuring chapters written by leading world experts, it addresses the progress, trends, and major achievements in this emerging research field, with a strong emphasis on the balance between novel theoretical results and solutions and practical real-life applications. Explains the following fundamental approaches for developing evolving intelligent systems (EIS): the Hierarchical Prioritized Structure the Participatory Learning Paradigm the Evolving Takagi-Sugeno fuzzy systems (eTS+) the evolving clustering algorithm that stems from the well-known Gustafson-Kessel offline clustering algorithm Emphasizes the importance and increased interest in online processing of data streams Outlines the general strategy of using the fuzzy dynamic clustering as a foundation for evolvable information granulation Presents a methodology for developing robust and interpretable evolving fuzzy rule-based systems Introduces an integrated approach to incremental (real-time) feature extraction and classification Proposes a study on the stability of evolving neuro-fuzzy recurrent networks Details methodologies for evolving clustering and classification Reveals different applications of EIS to address real problems in areas of: evolving inferential sensors in chemical and petrochemical industry learning and recognition in robotics Features downloadable software resources Evolving Intelligent Systems is the one-stop reference guide for both theoretical and practical issues for computer scientists, engineers, researchers, applied mathematicians, machine learning and data mining experts, graduate students, and professionals.

Pattern Recognition With Fuzzy Objective Function Algorithms

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Author : James C. Bezdek
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-13

Pattern Recognition With Fuzzy Objective Function Algorithms written by James C. Bezdek and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-13 with Mathematics categories.

The fuzzy set was conceived as a result of an attempt to come to grips with the problem of pattern recognition in the context of imprecisely defined categories. In such cases, the belonging of an object to a class is a matter of degree, as is the question of whether or not a group of objects form a cluster. A pioneering application of the theory of fuzzy sets to cluster analysis was made in 1969 by Ruspini. It was not until 1973, however, when the appearance of the work by Dunn and Bezdek on the Fuzzy ISODATA (or fuzzy c-means) algorithms became a landmark in the theory of cluster analysis, that the relevance of the theory of fuzzy sets to cluster analysis and pattern recognition became clearly established. Since then, the theory of fuzzy clustering has developed rapidly and fruitfully, with the author of the present monograph contributing a major share of what we know today. In their seminal work, Bezdek and Dunn have introduced the basic idea of determining the fuzzy clusters by minimizing an appropriately defined functional, and have derived iterative algorithms for computing the membership functions for the clusters in question. The important issue of convergence of such algorithms has become much better understood as a result of recent work which is described in the monograph.

Forecasting Principles And Applications

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Author : Stephen A. DeLurgio
language : en
Publisher:
Release Date : 1998

Forecasting Principles And Applications written by Stephen A. DeLurgio and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Forecasting categories.