Investment using technical analysis and fuzzy logic software

Mar 05, 2018 data mining and technical analysis is a growing trend throughout many different fields. An approach to macd based on genetic algorithms and fuzzy logic abstract. Dual time frame relative strength stock selection using. A predictive stock market technical analysis using fuzzy logic. The first one uses fuzzy logic to design the trading rules and to apply the stock market technical. Simutis 30 develops a computer software for fuzzy logic based stock trading with evolutionary programming methods, where technical. Applying investment strategies with technical analysis requires making use of. Fuzzy logic approach to swot analysis for economics tasks and. In fact, two fuzzy decision support systems are developed. This study gave rise to important points regarding the suitability of applying fuzzy neural networks for longterm prediction about stock prices using indicators from fundamentalist analysis.

Fuzzy rules are expressed in englishlike sentences using vague propositions and or consequences that correspond more to the human way of thinking. But it is difficult because there are too many factors that may manipulate stock prices we focus on both fundamental analysis and technical analysis. There is a vast amount of literature on the topic making it a difficult task for a practicing engineer, beginner researcher, or an advanced student to grasp the topic and then apply the acquired knowledge with only a small investment of time and money. An investment analysis model using fuzzy set theory. Fuzzy logic is the basic concept behind the human decisionmaking process.

Thats the promise of technical analysis according to some apps, websites, and social media feeds. The field of technical analysis dates back to the early twentieth century when charles dow wrote a. It can now be connected to a related package, xquote, that collects security prices over the internet. Rapid rapid analysis program for investment decisions for linux and win32 a gpled technical analysis system. Predefinition of the system requirements the system requirements were defined in order to have control variables, parameters, and target based on the condition of controlled object. The neural network identifies patterns and adapts to manage with the stock market movements using the human knowledge incorporated on the fuzzy inference logic. Robust technical trading with fuzzy knowledgebased systems. Two types of analysis are used for the market movements forecasting fundamental and technical dataset. Impact of artificial intelligence and machine learning on. I have got knowledge that it has been applied in algorithmic trading and operational risk, but i want to know what. Software used for simulation was python and the stock prices. Traditional sorts of mathematical analysis generally yield hard yes or no answers. A fuzzy logic based trading system semantic scholar.

Several researchers have used neural networks models in a variety of ways to predict short and longterm stock forecasting, but most of these models use technical indicators as. The article discusses the widely used classic method of analysis, forecasting and decisionmaking in the various economic problems, called swot analysis. The valuation of rfid investment using fuzzy real option. There is a vast amount of literature on the topic making it a difficult task for a practicing engineer, beginner researcher, or an advanced student to grasp the topic and then apply the acquired knowledge with only a small investment. A technical analysis indicator based on fuzzy logic. Fuzzy inference system fis technical analysis ta investment decision knowledge retrieval rough set theory rst variable consistency dominancebased rough set approach vc. Investing in mutual funds using fuzzy logic crc press st. Valuation of real estate investments through fuzzy logic. It is also possible to create automatically the investor portfolio. In the 1980s, ai research focused primarily on expert systems and fuzzy logic. Financial fuzzy logic based systems 1 khurshid ahmad. Fuzzy logic expert advisor topology for foreign exchange.

The npv expanded adding option value option premium to existing npv will have a positive value. The author suggested fuzzy logic can be used as platform for comparison and or ranking difference portfolios and stated that fuzzy could be universal tool to combine several methods. A novel forecasting method based on multiorder fuzzy time. Since technical analysis theory consists of indicators used by experts to evaluate stock prices, the new proposed method maps these indicators into new inputs that can be fed into a fuzzy logic. Technical and investment analysis ralgo engineering big data. Next is the process of the calculation of fuzzy real options value using the blackscholes model and the expanded npv assuming the current value of expected cash flow and investment costs and the fuzzy number. With the investment approach he devised, peray guides the you towards achieving your investment goals.

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. The aim of the study is to create a new technical analysis indicator using fuzzy logic method which could be an alternative to popular indicators used by traders. This can result in a narrowed analysis for trading decisions. Fuzzy logic based systems have been recently developed for using candlestick data for acquiring and deploying knowledge of financial prediction lee, liu and chen 2006.

Fuzzy rules are expressed in englishlike sentences using. In this paper, momentum trading, a type of technical analysis. Investment using technical analysis and fuzzy logic. Dourra and siy 25 present a trading system using technical analysis and fuzzy logic, which.

In this paper an indicator for technical analysis based on fuzzy logic is proposed, which unlike traditional technical indicators, is not a totally objective mathematical model, but incorporates su. Stock selection into portfolio by fuzzy quantitative. Fuzzy logic approach to swot analysis for economics tasks. This paper discusses the use of fuzzy logic and modeling as a decision making support for longterm investment decisions on. In section 4 the system results has been discussed. The practicality of the approach was demonstrated by an application to a test set of data. Vol 1 215 fuzzy logic expert advisor topology for foreign exchange market 1david a. Xinvest this is a free package for tracking stock portfolio values. Fuzzy logic expert advisor topology for foreign exchange market. An introduction to technical analysis investors intelligence.

Deciphering real estate investment decisions through fuzzy logic systems deciphering real estate investment decisions through fuzzy logic systems eddie chi man hui. This page including description and links for a tool with the name tekviewexplorer. By visiting this website, there is very good chance that you already use technical analysis in your investment decision making process. Our result shows that the fuzzy logic based expert advisor. A mathematical logic that attempts to solve problems by assigning values to an imprecise spectrum of data in order to arrive at the most accurate conclusion possible. A fuzzy logic stock trading system based on technical analysis. Scribner softwares 2010 tekview explorer software uses fuzzy logic to create and backtest trading strategies.

The aim is to yield more accurate results in stock price prediction. Fuzzy logic is a branch of analytics theory that can be useful for complex systems and was first advanced by dr. Application of fuzzy logic approach in financial performance. Proceedings of the international conference on software engineering and intelligent systems 2010, july 5th9th, ota, nigeria seis 2010. Stock technical analysis using multi agent and fuzzy logic. A sign, usually based on technical indicators, that it is a good time to buy or sell a particular security. Matt may, the systems developer, said the companys objective was to provide an affordable, easyto use platform that would encourage people to test their investment. Trade signals come in a variety of forms, including bull or bear pennants. Fuzzy logic investment support on the financial market abstract.

Technical analysis software featuring fuzzy logic back. An intelligent trading system with fuzzy rules and fuzzy. The objective of this research was to demonstrate that a. Shortterm stock market fuzzy trading system with fuzzy capital. It could be explained with the decision tree method and rulebased programming. A survey of fuzzy logic tools for fuzzybased system. The work employs fuzzy logic to perform the decision making process, based on inputs from.

The use of fuzzy logic in trading rules has been successfully explored in some works. Investment using technical analysis and fuzzy logic core. This method relies on fuzzy logic to formulate a decision making when certain price movements or certain price formations occur. Fuzzy logic is often used when a trader seeks to make use of multiple factors for consideration.

Choose the right approach there are two different ways to approach technical analysis. Investment using technical analysis and fuzzy logic citeseerx. Introduction in this paper, stock price prediction is discovering out the best time to buy or to sell. If you believe that any material in vtechworks should be removed, please see our policy and procedure for requesting that material be amended or removed.

How does fuzzy logic helps is all about we are going to discuss here. Has fuzzy logic been commercially applied in finance fields and has it been successful. Fuzzyneural model with hybrid market indicators for stock forecasting 289 3 the proposed hybrid model in this paper, a hybrid predictive model based on technical, fundamental indicators and experts opinion using fuzzy neural architecture is proposed. This work proposes a shortterm stock fuzzy decision system using a novel trading strategy. The analysis of stock markets is high complex due to the amount of data analyzed and to the nature of those, in this chapter we propose the use of fuzzy data mining process to support the analysis processes in order to discover useful properties that can help to improve investment decisions. The fuzzy model is optimised by using a genetic algorithm and historical data. Index terms fuzzy system, stock market, trading system, technical analysis. Keywords fuzzy logic, software tools, embedded system. In general, stock selection by a human investor is subjective and fuzzy in nature, even when using technical analysis. The only required inputs to these indicators are past sequence of stock prices. Amibroker software has been used to compare the proposed fis with the other technical.

Frames can contribute to find the best allocation of investment. Fuzzy logic based stock value prediction using fundamental analysis. Application of fuzzy logic approach in financial performance evaluation. However, it is always worth reevaluating your tools, by taking a moment to consider the nature of technical analysis and how we might use it. A fuzzy logic stock trading system based on technical. Fuzzy logic is one of the crucial technique to resolve the most ambiguous decisionmaking process in trading activities. Impact of artificial intelligence and machine learning on technical analysis. A lighting control system in buildings based on fuzzy logic. Logic application in evaluating financial performance there are a few studies related to financial performance using fuzzy logic approach. Several researchers have used neural networks models in a variety of ways to predict short and longterm stock forecasting, but most of these models use technical. Using fuzzy logic to more accurately test technical. What is the role of fuzzy logic in algorithmic trading. If you are familiar with metatrader4 mt4 that is widely used by forex traders, then you can search and find agents who sell you realtime data for metatrader4.

Technical analysis software featuring fuzzy logic backtesting. Since technical analysis theory consists of indicators used by experts to evaluate stock prices, the new proposed method maps these indicators into new inputs that can be fed into a fuzzy logic system. The core of the proposed method is the use of fuzzy logic to assign goodness scores to all candidate stocks, so that they can be ranked. The study used rahavard novin software to provide the data. Fuzzy logic approach to swot analysis for economics tasks and example of its computer realization vladimir chernov1, oleksandr dorokhov2, liudmyla dorokhova3 abstract. The idea of using fuzzy quantitative analysis and fuzzy multicriteria decision making to imply final investment weights for the stock selection into portfolio is different from the previous works.

An intelligent trading system with fuzzy rules and fuzzy capital. Portfolio investment decision support system based on a fuzzy. With the investment approach he devised, peray guides the you towards achieving your investment. Since technical analysis theory consists of indicators used. Stock market prediction based on fundamentalist analysis with. There are a variety of techniques to predict whether a particular area of investment would be profitable in the future. Probabilistic fuzzy logic based stock price prediction.

The analysis of stock markets is high complex due to the amount of data analyzed and to the nature of those, in this chapter we propose the use of fuzzy data mining process to support the analysis processes in order to discover useful properties that can help to improve investment. This is usually not the case of other methods like neural nets, stochastic modeling. This paper aims to evaluate financial performance of companies from consumer product sector in malaysia using fuzzy logic approach. The rule base of the fuzzy system is kept relatively straightforward for enhancing the interpretability of the model. In fuzzy logic and its applications are now wellestablished and arguments for and against it have reached a steady state. Fuzzy logic based stock value prediction using fundamental.

This paper describes a hybrid intelligent system formed by a decision support system based on rules for the management of a stock portfolio and by a fuzzy inference system to select the stocks to be incorporated. With computational power becoming cheaper, using machines to solve largescale optimization problems became economically feasible. By using genetic algorithms, it is possible to establish an optimal value for the time window which could yield higher profits when compared to the time window used in literature. Investment using technical analysis and fuzzy logic researchgate.

Stock market prediction based on investment analysis with fuzzy. Stock market prediction based on fundamentalist analysis. Citeseerx investment using technical analysis and fuzzy. Lotfi zadeh of the university of california at berkeley in the 1960s. The rules acquired make the system transparent and the output highly visualisable.

Implementation of fuzzy rule based technical indicator in share. A case study of consumer product sector in malaysia. A new methodology for the parameterization of the technical analysis of the financial market indicator coined moving average convergencedivergence macd is presented in this paper. Investment using technical analysis and fuzzy logic semantic scholar. The use of numbers, statistics, and algorithms has led to much more than a simple new machine or computer program. Fuzzy rule based technical indicator frbti on investing in the stock. A survey of fuzzy logic tools for fuzzybased system design. The effectiveness of the automatic system of fuzzy logicbased. In this work we are proposing a trading system where fuzzy logic is applied not only for defining the trading rules, but also for managing the capital to invest.

Few fuzzy systems have been created to forecast market activities using fundamental indicators 8,9,12,14,1820. An essay or paper on fuzzy logic in stock market analysis. In 9, the authors presented the ex pert system based on the fuzzy logic representation of the technical analysis trading rules which are usually used by traders for decision making. Most investors use both technical and fundamental analysis to make decisions. Fuzzyneural model with hybrid market indicators for stock. There is another type of commonly asked question, however, which cannot readily be answered in this way. Advanced features use fuzzy logic and petri nets to create rulesbased trading models for generating buysell signals. Download citation investment using technical analysis and fuzzy logic. Using fuzzy logic to more accurately test technical analysis. Fuzzy logic was chosen as basis of technical analysis for the following reasons.