Investment using technical analysis and fuzzy logic citeseerx. Applying investment strategies with technical analysis requires making use of indicators which are mathematical and statistical models, calculated from histori. 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. A fuzzy logic based trading system semantic scholar. Fuzzy capital budgeting techniques can capture this vagueness and model the imprecise estimations of parameter values. 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. Optimization of fuzzy metagraph based stock market dss. Tianshy liouy department of business administration cheng shiu university. Fuzzy logic was chosen as basis of technical analysis for the following reasons. In this article, we discuss the application of a combination of neural networks and fuzzy logic techniques to fundamentalist analysis of stock investment.
Portfolio investment decision support system based on a. Logic application in evaluating financial performance there are a few studies related to financial performance using fuzzy logic approach. The management of greenhouse climate parameters has been achieved by using the fuzzy logic method in the control system for the greenhouse. The use of fuzzy logic in trading rules has been successfully explored in some works. Using fuzzy logic to more accurately test technical. The analysis in section 3 is based on the concept fuzzy probability. The convolution which provides them, is based on the operation of intersection. Introduction in this paper, stock price prediction is discovering out the best time to buy or to sell. Investment using technical analysis and fuzzy logic sciencedirect. Department of information management national kaohsiung first university of science and technology 2, juoyue rd. Therefore by using this artificial intelligence ai application which is fuzzy logic fl can make it simpler as well as giving benefits to investors.
Technical analyses for currency trading vincent m kleinbrod1 and xiaoming li2, school of economics and finance, massey university, nz this version. The field of technical analysis dates back to the early twentieth century when. The technical analysis is the chart study of past behavior of the prices. Technical analysis presumes that there are trends and patterns in financial assets movements.
Traditional investment evaluation techniques based on discounted cash flows are not capable of capturing the uncertainty and vagueness in the data related to the wind energy investment parameters. 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. Citeseerx investment using technical analysis and fuzzy. The work employs fuzzy logic to perform the decision making process, based on inputs from. Portfolio investment decision support system based on a fuzzy. Fundamental and technical analysis are made automatically, and on the base of obtained partial results system produces evaluation of companies attractiveness as well as comments and. The authors state that the approach of fuzzy logic regarding language ambiguity is suitable for solving the given issue. A fuzzy logic based technical indicator for bist 30 index and. Investing in mutual funds using fuzzy logic crc press book fuzzy logic is an analytical tool used in the modeling of those phenomena that fall outside the scope of exact sciences. However, it is therefore as a matter of necessity to seek to foresee stock prices because traders need to know when to invest in order to get the maximum return of the investment. Additionally, a new technical market indicator that produces short and long entry signals is introduced. In this study, cognitive uncertainty was incorporated in technical analysis by using a fuzzy logicbased.
Index termshigh frequency trading, order execution, momentum analysis, fuzzy logic. In fuzzy logic, the same fact can belong to a number of sets with given membership values. That has changed as the advent of highspeed computing has made technical analysis easier and more widely available. Pdf stock technical analysis using multi agent and fuzzy. One of the tools for maintaining environmental sustainability is transformation from fossilbased energy sources to renewable energy sources in energy consumption. Jun 26, 2009 deciphering real estate investment decisions through fuzzy logic systems deciphering real estate investment decisions through fuzzy logic systems eddie chi man hui. Pdf portfolio investment decision support system based. In a given investment situation, it is necessary to consider several economic and technical parameters with respect to costs, profits, savings, the choice of time, tax and loyalty, project life, etc. A fuzzy decisionmaking approach for portfolio management with direct real estate investment eddie chi man hui 1, otto muk fai lau 2 and kak keung lo 3 1 department of building and real estate, the hong kong polytechnic university, hung hom, kowloon, hong kong email. The neural network identifies patterns and adapts to manage with the stock market movements using the human knowledge incorporated on the fuzzy inference logic. Fuzzy logic expert advisor topology for foreign exchange market.
Traditional investment evaluation techniques based on discounted cash flows are not. In this paper, we proposed a new forecasting method based on multiorder fuzzy time series, technical analysis, and a genetic algorithm. Fuzzy rules are expressed in englishlike sentences using vague propositions andor consequences that correspond more to the human way of thinking. 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. Fuzzy logic approach to swot analysis for economics tasks 321 somewhat more complicated is the case with pessimistic estimates. This paper proposes a sugenotype fuzzy inference system for stock price prediction. Because the developed fuzzy logic system was designed to consider the climate parameters required by the plant, it was more efficient in its operation than the conventional method. This work proposes a shortterm stock fuzzy decision system using a. The investors need to make a right decision to gain a high profit in stock trading. Few fuzzy systems have been created to forecast market activities using fundamental indicators 8,9,12,14,1820. Fuzzy rules are expressed in englishlike sentences using vague propositions and or consequences that correspond more to the human way of thinking.
Recently research work in stock market predictions are gaining momentum. Optimization of fuzzy metagraph based stock market dss using. Stock market prediction based on fundamentalist analysis. Dourra and siy 2002 analysed investment using technical analysis and fuzzy logic. A survey of fuzzy logic tools for fuzzybased system. Box 1738, 3000 dr, rotterdam, the netherlands email. Fuzzy logic expert advisor topology for foreign exchange. Finally, the possibilities of probabilities are obtained. Investment using technical analysis and fuzzy logic. Index terms fuzzy system, stock market, trading system, technical analysis. Pdf a predictive stock market technical analysis using fuzzy logic. Sugenotype fuzzy inference model for stock price prediction.
This paper proposes a multivariate fuzzy logic approach to boosting the profitability of technical analysis for currency trading. 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. An intelligent trading system with fuzzy rules and fuzzy capital. It is a challenge to develop the inherent rules using the traditional time series prediction technique. An investment analysis model using fuzzy set theory. This paper attempts to fill the gap between theorem and application.
The system generates a buy or sell signal, but it can also be combined with portfolio. The model uses bellman and zadehs decisionmaking criterion, determining the degree of convergence when the objective is to maximize the net present value of the project under the constraint of minimizing risk. Deploy fuzzy logic engineering tools in the finance arena, specifically in the technical analysis field. Stock selection into portfolio by fuzzy quantitative. The rules acquired make the system transparent and the output highly visualisable. The foundation of fuzzy logic for expressing imprecise, vague and uncertain information was. The performance of stock portfolios formed using fuzzy. A fuzzy logic stock trading system based on technical. Stock market prediction based on fundamentalist analysis with. Technical analysis involves predicting stock price using technical indicators like rsi, macd and william %r. A model for optimal investment project choice using fuzzy. Purpose the purpose of this paper is to explore the application of fuzzy logic in real estate investment in hong kong. To support investment decision based on technical analysis ta, this study aims to retrieve the knowledge or rules of various indicators by a hybrid soft computing model.
Shortterm stock market fuzzy trading system with fuzzy capital. The practicality of the approach was demonstrated by an application to a test set of data. 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. The control of greenhouses based on fuzzy logic using. Furthermore, this paper introduces a new proposal for performance evaluation of sudanese universities and academic staff using fuzzy logic. A comparison of wind energy investment alternatives using. Evaluation and analysis of investment alternatives with different economic lives using fuzzy logic chingwen chen. As reported by madhusudhan and moorthi 2018, sentiment expresses what the public thinks and shares its. A survey of fuzzy logic tools for fuzzybased system design. Our result shows that the fuzzy logic based expert advisor. Download citation investment using technical analysis and fuzzy logic deploy fuzzy logic engineering tools in the finance arena, specifically in the technical. Section 2 summarizes the stochastic investment analysis and this analysis is extended to the fuzzy case using fuzzy numbers. Investment using technical analysis and fuzzy logic core.
Deciphering real estate investment decisions through fuzzy. Stock technical analysis using multi agent and fuzzy logic. Pdf decision making using fuzzy logic for stock trading. The original aspect of this work consists in incorporating uncertainty into the model by. 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. None of the methodologies has explored a pure application of fuzzy logic inference to foreign exchange trading in open literature, to our knowledge. His modelmethod has since been developed and widely used in investment, operating design.
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. Probabilistic fuzzy logic based stock price prediction. This method relies on fuzzy logic to formulate a decision making when certain price movements or certain price formations occur. Fuzzy inferenceenhanced vcdrsa model for technical analysis.
Two types of analysis are used for the market movements forecasting fundamental and technical dataset. Although the validity of ta has been examined extensively by various statistical methods in literature, previous studies mainly explored the effectiveness of each technical indicator separately. Many large investment firms use black box trading, or computer modeling, to determine their entry and exit points. Fundamentals annual analysis involves global economic conditions such as bud, get, company information conditions as environments around the stock market, where technical analysis involves technical indicators like williamr%, macd, rsi, the stock status can be classified by fuzzy logic, neural network, and svm. If a reliable approach is not used to quantify the effects of these factors, it is very difficult to correctly assess each alternative and make. One of such techniques is fuzzy logic mitchell 1997. A fuzzy logic based trading system wee mien cheung uzay kaymak econometric institute, erasmus school of economics, erasmus university rotterdam p. An intelligent trading system with fuzzy rules and fuzzy. Application of fuzzy logic approach in financial performance. 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. In their paper, liu and zheng 2011 introduced the bollinger bands into the stochastic volatility model.
Using previous knowledge for stock market prediction based on fundamentalist analysis with fuzzyneural networks,2rd wseas icosmo, skiathos, greece, 2002. One of the most challenging areas in technical analysis is the. In fuzzy logic and its applications are now wellestablished and arguments for and against it have reached a steady state. In financial markets technical analysis is commonly used to provide trading decisions. Evaluation and analysis of investment alternatives with. Performance evaluation methods and techniques survey. It is known that the intersection can be determined as follows. This approach can be valuable for investors as a way to incorporate. In this paper we present a model for classifying exclusive investments. Using fuzzy logic to more accurately test technical analysis benjamin reinach technical analysis is a field of study in finance that attempts to predict future price movements of securities by analyzing past market statistics such as price and volume. A technical analysis indicator based on fuzzy logic cyberleninka. The suggested order placement algorithm also considers the markets intraday volatility to minimize trading costs.
A predictive stock market technical analysis using fuzzy logic article pdf available in computer and information science 73 july 2014 with 3,517 reads how we measure reads. There have been sufficient debates on the literature, providing the theoretical background on real estate investment decisions but there has been a lack of empirical support in this regard. 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 logic approach to swot analysis for economics tasks. The only required inputs to these indicators are past sequence of stock prices. A novel forecasting method based on multiorder fuzzy time. Classifiers like svm, fuzzy logic and neural networks are used to classify stock status. Investing in mutual funds using fuzzy logic crc press book. For decades, fundamental analysis was the only investment method that was given any credibility. Fuzzy inferenceenhanced vcdrsa model for technical. This is usually not the case of other methods like neural nets, stochastic modeling. A predictive stock market technical analysis using fuzzy logic. Using fuzzy logic to more accurately test technical analysis. The first one uses fuzzy logic to design the trading rules and to apply the stock market technical indicators.
Combination method between fuzzy logic and neural network. A fuzzy logic stock trading system based on technical analysis. The performance of stock portfolios formed using fuzzy logic expert systems, a type of artificial intelligence that replicate how experts think, can aide unskilled users in making decisions or apply an experts thought process to a sample much larger than could be examined by a human expert. But it is difficult because there are too many factors that may manipulate stock prices we focus on both fundamental analysis and technical analysis. Fuzzy logic approach to swot analysis for economics tasks and.
The second one enhances this fuzzy trading system adding a fuzzy strategy to manage the capital to trade. Membership function can have any shape, but triangular and trapezoid ones are very popular, they are simple and give satisfactory results fig. Neural networks in finance and investing, probus publishing company, chicago, illinois, usa, 1993. The author suggested fuzzy logic can be used as platform for comparison andor ranking difference portfolios and stated that fuzzy could be universal tool to combine several methods. Most of the proposed prediction models are based on technical analysis. High frequency trading using fuzzy momentum analysis. Can fuzzy logic make technical analysis 2020 financial. The complex behavior of the stock market requires development of forecasting systems. Stock market prediction based on investment analysis with. Investment analyses using fuzzy probability concept. Investment using technical analysis and fuzzy logic researchgate.