Download or read book Stock Market Forecasting Using Fuzzy Logic written by and published by . This book was released on 2016 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Stock Market Trend Prediction Using Neural Networks and Fuzzy Logic written by Maha Abdelrasoul and published by . This book was released on 2016-11-22 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book An Improved Intelligent Model for Stock Market Time Series Data Prediction Using Fuzzy Logic and Deep Neural Networks written by Parniyan Mousaie and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Neuro Fuzzy Based Stock Market Prediction System written by M. Gunasekaran and published by . This book was released on 2013 with total page 6 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Applying Fuzzy Logic to Stock Price Prediction written by Ali Ghodsi Boushehri and published by . This book was released on 2000 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Forecasting Ibovespa Index with Fuzzy Logic written by Cesar Duarte Souto-Maior and published by . This book was released on 2006 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Fuzzy Information Retrieval written by Donald H. Kraft and published by Morgan & Claypool Publishers. This book was released on 2017-01-23 with total page 83 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information retrieval used to mean looking through thousands of strings of texts to find words or symbols that matched a user's query. Today, there are many models that help index and search more effectively so retrieval takes a lot less time. Information retrieval (IR) is often seen as a subfield of computer science and shares some modeling, applications, storage applications and techniques, as do other disciplines like artificial intelligence, database management, and parallel computing. This book introduces the topic of IR and how it differs from other computer science disciplines. A discussion of the history of modern IR is briefly presented, and the notation of IR as used in this book is defined. The complex notation of relevance is discussed. Some applications of IR is noted as well since IR has many practical uses today. Using information retrieval with fuzzy logic to search for software terms can help find software components and ultimately help increase the reuse of software. This is just one practical application of IR that is covered in this book. Some of the classical models of IR is presented as a contrast to extending the Boolean model. This includes a brief mention of the source of weights for the various models. In a typical retrieval environment, answers are either yes or no, i.e., on or off. On the other hand, fuzzy logic can bring in a "degree of" match, vs. a crisp, i.e., strict match. This, too, is looked at and explored in much detail, showing how it can be applied to information retrieval. Fuzzy logic is often times considered a soft computing application and this book explores how IR with fuzzy logic and its membership functions as weights can help indexing, querying, and matching. Since fuzzy set theory and logic is explored in IR systems, the explanation of where the fuzz is ensues. The concept of relevance feedback, including pseudorelevance feedback is explored for the various models of IR. For the extended Boolean model, the use of genetic algorithms for relevance feedback is delved into. The concept of query expansion is explored using rough set theory. Various term relationships is modeled and presented, and the model extended for fuzzy retrieval. An example using the UMLS terms is also presented. The model is also extended for term relationships beyond synonyms. Finally, this book looks at clustering, both crisp and fuzzy, to see how that can improve retrieval performance. An example is presented to illustrate the concepts.

Download or read book Computational Science ICCS 2001 written by Vassil Alexandrov and published by Springer Science & Business Media. This book was released on 2001-05-24 with total page 1068 pages. Available in PDF, EPUB and Kindle. Book excerpt: LNCS volumes 2073 and 2074 contain the proceedings of the International Conference on Computational Science, ICCS 2001, held in San Francisco, California, May 27-31, 2001. The two volumes consist of more than 230 contributed and invited papers that reflect the aims of the conference to bring together researchers and scientists from mathematics and computer science as basic computing disciplines, researchers from various application areas who are pioneering advanced application of computational methods to sciences such as physics, chemistry, life sciences, and engineering, arts and humanitarian fields, along with software developers and vendors, to discuss problems and solutions in the area, to identify new issues, and to shape future directions for research, as well as to help industrial users apply various advanced computational techniques.

Download or read book A Neuro fuzzy Logic Forecasting System in Stock Investment Decision Making Processes written by Xu Wang and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "The sophisticated financial investment world is characterized by highly random variations in stock prices, financial indexes and trading volumes so that it is quite difficult to get fundamental understanding of the financial investment process and to predict the stock market. This research attempts to develop a new and innovative approach to predict the stock time series with artificial intelligence techniques. Specifically, a fuzzy logic analysis has been made to predict the stock time series with different characteristic variables and different investments horizons, respectively. A neural network is designed to fine-tune the parameters involved and thus a neuron-fuzzy logic time series forecasting model has been developed" - abstract.

Download or read book Fuzzy Logic for Business Finance and Management written by George Bojadziev and published by World Scientific. This book was released on 1997 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is an interdisciplinary book for knowledge workers in business, finance, management, and socio-economic sciences. It provides a guide to and techniques for forecasting, decision making, conclusions, and evaluations in an environment involving uncertainty, vagueness, and impression. Traditional modeling techniques do not capture the nature of complex systems especially when humans are involved. Fuzzy logic provides effective tools for dealing with such systems. Emphasis is on applications presented in case studies including Time Forecasting for Project Management, New Product Pricing, Client Financial Risk Tolerance Policy, Deviation and Potential Problem Analysis, Inventory Control Model, Stock Market Strategy.

Download or read book Stock price Prediction a referential approach on how to predict the stock price using simple time series written by Dr.N.Srinivasan and published by Clever Fox Publishing. This book was released on with total page 56 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Fuzzy Sets Fuzzy Logic and Their Applications written by Michael Gr. Voskoglou and published by MDPI. This book was released on 2020-03-25 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: The present book contains 20 articles collected from amongst the 53 total submitted manuscripts for the Special Issue “Fuzzy Sets, Fuzzy Loigic and Their Applications” of the MDPI journal Mathematics. The articles, which appear in the book in the series in which they were accepted, published in Volumes 7 (2019) and 8 (2020) of the journal, cover a wide range of topics connected to the theory and applications of fuzzy systems and their extensions and generalizations. This range includes, among others, management of the uncertainty in a fuzzy environment; fuzzy assessment methods of human-machine performance; fuzzy graphs; fuzzy topological and convergence spaces; bipolar fuzzy relations; type-2 fuzzy; and intuitionistic, interval-valued, complex, picture, and Pythagorean fuzzy sets, soft sets and algebras, etc. The applications presented are oriented to finance, fuzzy analytic hierarchy, green supply chain industries, smart health practice, and hotel selection. This wide range of topics makes the book interesting for all those working in the wider area of Fuzzy sets and systems and of fuzzy logic and for those who have the proper mathematical background who wish to become familiar with recent advances in fuzzy mathematics, which has entered to almost all sectors of human life and activity.

Download or read book Ordinary Shares Exotic Methods written by Francis E. H. Tay and published by World Scientific. This book was released on 2003 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exotic methods refer to specific functions within general soft computing methods such as genetic algorithms, neural networks and rough sets theory. They are applied to ordinary shares for a variety of financial purposes, such as portfolio selection and optimization, classification of market states, forecasting of market states and data mining. This is in contrast to the wide spectrum of work done on exotic financial instruments, wherein advanced mathematics is used to construct financial instruments for hedging risks and for investment.In this book, particular aspects of the general method are used to create interesting applications. For instance, genetic niching produces a family of portfolios for the trader to choose from. Support vector machines, a special form of neural networks, forecast the financial markets; such a forecast is on market states, of which there are three OCo uptrending, mean reverting and downtrending. A self-organizing map displays in a vivid manner the states of the market. Rough sets with a new discretization method extract information from stock prices."

Download or read book Investing in Mutual Funds Using Fuzzy Logic written by Kurt Peray and published by CRC Press. This book was released on 1999-06-25 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fuzzy Logic is an analytical tool used in the modeling of those phenomena that fall outside the scope of exact sciences. It is used in the analysis of complex and highly nonlinear processes, where mathematical models or standard classic logic cannot define conditions inherent to such processes, e.g. human thinking. Kurt Peray's detailed analysis of the new approaches and techniques for Risk Control and Portfolio Asset Allocation - which uses the principles of Fuzzy Logic - helps you to make decisions as to when to buy, hold or sell. While making independent and educated decisions, you will be able to hedge your portfolio from the volatile forces in the market, and will offset the erosive impact of inflation and taxation. In this electronic age, investors have quick access to important information relevant to the decision process. The guidelines and formulas that serve as foundations to the Fuzzy Logic approach gives you the ability to build customized programs. Investing in Mutual Funds Using Fuzzy Logic is for the individual who wants to invest in financial instruments that will provide a return for growth. With the investment approach he devised, Peray guides the you towards achieving your investment goals.

Download or read book Applying Fuzzy Logic to Stock Price Prediction written by and published by . This book was released on 2000 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Integrated Computational Intelligence and Japanese Candlestick Method for Short term Financial Forecasting written by Takenori Kamo and published by . This book was released on 2011 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This research presents a study of intelligent stock price forecasting systems using interval type-2 fuzzy logic for analyzing Japanese candlestick techniques. Many intelligent financial forecasting models have been developed to predict stock prices, but many of them do not perform well under unstable market conditions. One reason for poor performance is that stock price forecasting is very complex, and many factors are involved in stock price movement. In this environment, two kinds of information exist, including quantitative data, such as actual stock prices, and qualitative data, such as stock traders' opinions and expertise. Japanese candlestick techniques have been proven to be effective methods for describing the market psychology. This study is motivated by the challenges of implementing Japanese candlestick techniques to computational intelligent systems to forecast stock prices. The quantitative information, Japanese candlestick definitions, is managed by type-2 fuzzy logic systems. The qualitative data sets for the stock market are handled by a hybrid type of dynamic committee machine architecture. Inside this committee machine, generalized regression neural network-based experts handle actual stock prices for monitoring price movements. Neural network architecture is an effective tool for function approximation problems such as forecasting. Few studies have explored integrating intelligent systems and Japanese candlestick methods for stock price forecasting. The proposed model shows promising results. This research, derived from the interval type-2 fuzzy logic system, contributes to the understanding of Japanese candlestick techniques and becomes a potential resource for future financial market forecasting studies"--Abstract, leaf iii.

Download or read book Fuzzy Logic and NeuroFuzzy Applications in Business and Finance written by Constantin Von Altrock and published by Prentice Hall. This book was released on 1997 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this hands-on, practical guide, you'll walk through powerful fuzzy logic business applications for business, including risk assessment, forecasting, supplier evaluation, customer targeting, and scheduling. You'll watch fuzzy logic at work analyzing credit risk, evaluating leases, making stock market decisions, and uncovering fraud.