Dissertations / Theses on the topic 'Elliot’s waves'

This thesis deals with an analysis and prediction of foreign exchange markets. The thesis is based on the fractal market hypothesis and it uses tools based on fractal geometry for prediction of markets. The thesis also describes ways of using advanced methods of artificial intelligence for analyzing markets. The outcome is designed and implemented automatic trading system. The thesis also deals with testing of designed system on historical data and on the latest data as well.

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-Graduação em Engenharia de Produção.
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Esta pesquisa apresenta o método Elliott Waves de previsão dos próximos movimentos de preços no mercado financeiro sob o enfoque da teoria do caos e da complexidade, novas áreas da ciência que procuram entender o que a física newtoniana ainda não conseguiu explicar: o comportamento dos sistemas complexos. A possibilidade de conexão entre os mercados de capitais e as teorias do caos e da complexidade foi motivada pela descoberta do comportamento fractal das séries temporais de preços por Benoit Mandelbrot (1997) e pelos registros de repetições quase perfeitas de padrões fractais nos gráficos históricos de ações e mercadorias referentes à bolsa de valores Nova York e à bolsa de mercadorias de Chicago, feitos por Ralph Nelson Elliott e relatados por Robert Prechter (2000) e Glenn Neely (1990). Como alternativa à tradicional Hipótese dos Mercados Eficientes (HME), que está para a Economia assim como a mecânica de Newton está para a Física, a modelagem matemática através dos fractais produz resultados que acompanham as mudanças reais nos preços de uma maneira mais precisa e explicam o comportamento do mercado nos momentos de maior volatilidade. Enquanto os fractais Elliott baseiam-se em dados históricos para se prever acontecimentos futuros, a HME tem como uma de suas premissas a inexistência de memória nos mercados, ou seja, os preços variam aleatoriamente (distribuição de Gauss) e unicamente em função dos novos eventos econômicos, já que os eventos passados já foram totalmente assimilados pelo mercado e descontados nos preços atuais. A HME não corresponde à realidade dos mercados financeiros, o que foi comprovado por esta dissertação.

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The Elliott Wave analysis is a technique developed for the prediction of prices of financial assets (stocks, exchange rates etc.). This work introduces the basic concepts of the financial market, focusing mainly on the Elliott Wave principle, which differs from other techniques for providing direction and intensity of changes in shares / stocks prices in the financial market. The Elliott Wave detection usually employs manual methods, since automated systems present high costs and are apparently based on trial and error method associated with Statistics. Manual methods assess, following some rules, the waves prospected by trial and error, and requires specialized training and experience. To automatically detect the waves of Elliott, this work suggests, develops and tests a computational system based on Genetic Algorithms, an Artificial Intelligence technique inspired on Biology. Genetic Algorithms are used to evolve answers to problems by assessing candidates, which are coded as chromosomes. Tests of the system were performed based on BM&FBOVESPA stocks with high daily liquidity. Simulations have indicated that the detected waves are satisfactory, with error rate below 3% in each inflection point.
A análise das Ondas de Elliott é uma técnica desenvolvida para a previsão dos preços de ativos financeiros (ações, taxas de câmbios etc). O presente trabalho introduz conceitos básicos do mercado financeiro, focando principalmente nas Ondas de Elliott que diverge das outras técnicas por prever direção e intensidade da mudança do valor de ações/papéis no mercado financeiro. A detecção das Ondas de Elliott usa geralmente metodologia manual, visto que os sistemas automáticos possuem custos elevados e são aparentemente baseados em métodos de tentativa e erro associados à Estatística. O método manual avalia, seguindo algumas regras, as ondas prospectadas por tentativa e erro, exigindo treinamento especializado e experiência. Para detectar automaticamente as Ondas de Elliott no mercado financeiro, este trabalho propõe, desenvolve e testa um sistema computacional baseado em Algoritmos Genéticos, uma técnica de Inteligência Artificial baseada na seleção natural da Biologia. Algoritmos Genéticos são utilizados para evoluir respostas a problemas que permitem avaliar candidatos a soluções, codificados como cromossomos. Os testes do sistema foram realizados com base nos dados de ações pertencentes à Bolsa de Bolsa de Valores, Mercadorias e Futuros (BM&FBOVESPA) e possuidoras de alta liquidez diária. As simulações indicaram que as ondas detectadas pelo sistema foram satisfatórias, possuindo índice de erro abaixo de 3% por ponto de inflexão.

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This work deepens the discussion in the Technical Analysis field, aligning it premises to the theoretical framework of Behavioral Finance. In this purpose, this paper aimed to make, for the period between the years of 2007 and 2008, an empirical study of the brazilian stock market in the light of Technical Analysis and Behavioral Finance, as well as verifying the performance of technical index as auxiliary instrument for the decision taking. This way, the work is divided in two parts. In the first part, adopting the complementarity hypothesis of behavioral-technique approach in the process of analysis and taking of decision in the stock market, is aimed to establish a relation between Technical Analysis (Dow Theory and Elliott Waves Theory) and Behavioral Finance assumptions in the interpretation of the subprime crisis in the Brazilian stock market, through a documentary research with referring information of the years 2007 and 2008, crisis development period. The results had evidenced the utility of these theories, not only for the analysis of the subprime crisis consequences, as, also, for the examination of financial market agent s behavior in a historical perspective of larger reach. In the second part, adopting the hypothesis that the technical index are capable to assist the investors in the process of decision taking, had been refined the performances of the Exponential Moving Average, Moving Average Convergence/Divergence, Relative Force Index, Stochastic and Directional System, using as base, Brazilian s stock market data referring to the year of 2007. The research results demonstrated that the Assertiveness (A) of the purchase signals is superior to the Assertiveness (A) of the sales signals the results had demonstrated as well, the uselessness of Directional System (DS) as beeper of the market s predominant trend.
Este trabalho aprofunda a discussão no campo de estudos da Análise Técnica, alinhando suas premissas ao arcabouço teórico das Finanças Comportamentais. Neste intuito buscou-se realizar, para o período compreendido entre os anos de 2007 e 2008, um estudo empírico do mercado brasileiro de ações à luz da Análise Técnica e das Finanças Comportamentais, bem como verificar o desempenho de indicadores técnicos como instrumento auxiliar para a tomada de decisão. Desta forma, o trabalho encontra-se dividido em duas partes. Na primeira parte, adotando a hipótese de complementaridade das abordagens técnica-comportamental no processo de análise e tomada de decisão no mercado de ações, busca-se estabelecer uma relação entre os pressupostos da Análise Técnica (Teoria Dow e Teoria da Ondas de Elliott) e das Finanças Comportamentais na interpretação da crise subprime no mercado de ações brasileiro, através de uma pesquisa documental com informações referentes aos anos de 2007 e 2008, período de desenvolvimento da crise. Os resultados evidenciaram a utilidade destas teorias, não só para a análise dos reflexos da crise subprime, como, também, para o exame do comportamento dos agentes do mercado financeiro numa perspectiva histórica de maior alcance. Na segunda parte, adotando a hipótese de que os indicadores técnicos são capazes de auxiliar os investidores no processo de tomada de decisão, foram apurados os desempenhos dos indicadores Média Móvel Exponencial, Convergência/Divergência da Média Móvel, Índice de Força Relativa, Estocástico e Sistema Direcional, tomando como base dados do mercado de ações brasileiro referentes ao ano de 2007. Os resultados encontrados demonstraram que a Assertividade (A) dos sinais de compra é superior à Assertividade (A) dos sinais de venda, bem como apontaram a inutilidade do Sistema Direcional (SD) enquanto sinalizador da tendência predominante do mercado.

This thesis is concerned with future trend prediction on capital markets on the basis of neural networks. Usage of convolutional and recurrent neural networks, Elliott wave theory and scalograms for capital market's future trend prediction is discussed. The aim of this thesis is to propose a novel approach to future trend prediction based on Elliott's wave theory. The proposed approach will be based on the principle of classification of chosen patterns from Elliott's theory by the way of convolutional neural network. To this end scalograms of the chosen Elliott patterns will be created through application of continuous wavelet transform on parts of historical time series of price for chosen stocks.

This diploma thesis compares chaos theory with Elliott wave theory in order to find out whether there is an agreement in the area of prediction. Such formulation of main problem is considered original, new and pioneering issue. By solving an indirect problem of deterministic chaos, existence of the chaos was not proved in a respective time series. The possibility to predict future development of this time series in a short-term period was considered impossible with respect of chaos theory results. Nevertheless, subsequent prediction that used Elliott wave theory showed to be precise. Finally, agreement of both theories was not confirmed. The diploma thesis proved that knowledge of Elliott wave theory and ability to interpret it correctly is a valuable means of prediction.

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The prices of securities traded on stock exchanges, as well as any other commodity in the financial market fluctuate naturally with the demand for these products. These oscillations, along with the asymmetry of information about the prices of these products generate volatility processes. Charles Dow in the early twentieth century created sector indexes, in which papers met the same area of activity, according to him, several indicators point to the same direction would be a sign that this really would be a tendency to drive the market, thus characterizing the Dow Theory. Ralph Nelson Elliott (1871-1948) studied the average prices of the Dow Jones Industrial and realized repetitions in the market changes, their observations were summarized in what became known as "The Wave Principle." Elliott developed his theory based on so-called Fibonacci sequence, discovered by Leonardo Pizza (Fibonacci) around 1200. In addition to the Dow Theory and the Theory of waves in this work was done using the Theory of Rationality of the agents as a complementary way to explain the decision process of investors, as happens in situations of uncertainty. A rational decision involves selecting the choice which has the largest expected return for a given level of risk.
Os preços dos ativos negociados em bolsas de valores, assim como qualquer outro tipo de commodity do mercado financeiro, oscilam naturalmente com a procura por esses produtos. Essas oscilações, juntamente com a assimetria das informações acerca dos preços desses produtos geram processos de volatilidade. Charles Dow, no início do século XX criou índices setoriais, nos quais reunia papéis da mesma área de atividade, segundo ele, se vários índices apontassem para a mesma direção seria um sinal de que realmente essa seria uma tendência de movimentação do mercado, caracterizando assim a Teoria de Dow. Ralph Nelson Elliott (1871-1948) estudou as cotações médias dos índices Dow Jones Industrial e percebeu repetições nas alterações do mercado, suas observações foram resumidas no que ficou conhecido como O Princípio da Onda . Elliott desenvolveu a sua teoria com base na denominada Sequência de Fibonacci, descoberta por Leonardo de Pizza (Fibonacci) por volta de 1200. Além da Teoria de Dow e da Teoria das Ondas, nesse trabalho, fez-se uso da Teoria da Racionalidade dos agentes como uma forma complementar para se explicar o processo de decisão dos investidores, dado que acontecem em situações de incerteza. Uma decisão racional implica em selecionar a escolha que apresente o maior retorno esperado para um dado nível de risco.

The thesis deals with the possibility of prediction of the exchange rate on forex. The combination of Elliott wave principle and Fibonacci numbers examines to what extent and in what time periods it is possible to predict exchange rate. The thesis use fundamental analysis and MACD oscillator to confirm the accuracy of this prediction.

Using modern methods of share quotations forecasting is the main goal of this thesis. The special accent is placed on forecasting the trend by means of artificial neural network especially on the optimalization of variables in the training process. Elliot's wave theory is applied in the second part of the thesis, particularly on prediction of future share quotation progress. Buying or selling signal generated by these two methods is consequently compared with ex-post signal yielding a profit. Lastly, successfulness of using these methods for forecasting at stock market is evaluated.

This master thesis deals with the price prediction on financial markets. It describes automated trading systems based on technical analysis and discusses a soft computing approach to construction of such systems. Also, this thesis combines conventional trading strategies with the fuzzy logic. The practical part of this thesis contains also a framework for composing, simulation and analysis of the automated trading strategies. The simulator contained in this framework is implemented in the Java language and based on DEVS formalism. Because of this, there is a possibility to embed real-time components into the trading model. This work contains also a database of historical financial data and tools for their automatic actualization.

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Esta dissertação trata das operações realizadas na BM&F BOVESPA chamadas comumente de 'Day Trading', ou seja, operações cuja compra (ou venda) e a liquidação são realizadas no mesmo dia. Tal questão é relevante, principalmente para o pequeno investidor, por possibilitar a otimização do resultado da sua carteira de investimento ao longo do tempo. O objetivo de pesquisa deste trabalho é apresentar e testar algumas técnicas utilizadas pelos operadores do mercado financeiro na modalidade 'Day Trading'. Em conjunto com a verificação das teorias de análise gráfica, o trabalho pretende conciliar tais técnicas preditivas com teorias de gestão de risco e de gestão de portfólio, nesse caso mais precisamente a teoria moderna de portfólio de Markowitz, de forma a testar a eficiência da combinação entre essas teorias no mercado de ações brasileiro, e se existe a possibilidade de otimização dos resultados que um investidor pode alcançar ao longo do tempo. Para atingir este objetivo foi realizada uma pesquisa quantitativa utilizando técnicas de análise gráfica baseadas em teorias amplamente conhecidas no mercado de capitais, como os Princípios de Ondas de Elliott e a Teoria de Dow. A partir dos indicadores de sucesso obtidos por essas técnicas preditivas (através de 'backtests'), o presente trabalho testa a efetividade das questões relativas a eficiência de mercado apresentadas nas Hipótese de Mercados Eficientes de Fama (1970). As principais conclusões desta dissertação sugerem que uma estratégia passiva, de compra e manutenção do Índice Bovespa, domina respectivamente estratégias baseadas na Teoria de Markowitz e estratégias ativas de Day Trading baseadas em análise técnica. Os resultados trazem uma grande contribuição para o pequeno investidor através de uma maior compreensão sobre possibilidades que as operações de curto prazo podem trazer para ao seu portfólio de investimentos e confirma a visão de que o mercado de ações brasileiro é eficiente em sua forma fraca.
This thesis deals with operations carried out on BM&F BOVESPA commonly called 'Day Trading', which are operations whose purchase (or sale) and settlement are carried out on the same day. This issue is relevant, especially for the small investor, because it allows the optimization of the result of their investment portfolio over time. The objective of this research is to present and test some techniques used by financial market traders in the 'Day Trading' modality. In conjunction with the verification of theories of technical analysis, the paper aims to reconcile such predictive techniques with theories of risk management and portfolio management, in this case more precisely the Modern Portfolio Theory of Markowitz, in order to test the efficiency of the combination between these theories in the Brazilian stock market, and whether there is a possibility of optimizing the results that an investor can achieve over time. To achieve this goal a quantitative research is performed using graphical analysis techniques based on theories widely known in the capital market, such as the Elliott Wave Principle and the Dow Theory. From the indicators of success obtained by these predictive techniques (through backtests), the present research explores aspects of market efficiency presented in the Efficient Market Hypothesis of Fama (1970). The main conclusions of this dissertation suggest that a passive buy and hold strategy of the Bovespa Index dominates respectively strategies based on Markowitz Theory and active day trading strategies based on technical analysis. The results make a contribution to the small investor through a better understanding of the possibilities that short-term operations can bring to their investment portfolios and confirms the view that the Brazilian stock market is efficient in its weak form.

碩士
國立臺灣科技大學
電子工程技術研究所
86
This thesis implements the Elliott Wave Principle which is a well-known financial technical analysis method in commodity and stock markets. Today, thisprinciple is one of the most widely adopted methods for market analysis in theworld. The Wave Principle is a detailed description of how groups of people behave.It reveals that mass psychology swings from pessimism to optimism and back ina natural sequence, creating specific and measurable patterns. One of the easiest places to see this phenomenon at work is in the financialmarkets, where changing investor psychology is recorded in the form of pricemovements. The idea is that if we can identify repeating patterns of prices, andfigure out where we currently are in those repeating patterns, then we can predict the future trend. There are two major parts of work in this research. First, we utilize computer-aided technology and computer algorithm to recognize patterns based onElliott Wave Principle. Marking corresponding wave number and degree on eachwave.Second, a prediction for financial market trends in the future is availablebased on current patterns.

by Lee Yat Fai, Frederick, Pang Fai.
Thesis (M.B.A.)--Chinese University of Hong Kong, 2000.
Includes bibliographical references (leaf 34).
Chapter 1. --- Introduction --- p.1
Chapter 1.1 --- Background --- p.2
Chapter 2. --- Methodology --- p.4
Chapter 2.1 --- Approach --- p.5
Chapter 2.2 --- Model Automation Tools --- p.7
Chapter 2.2.1 --- Data --- p.7
Chapter 2.2.2 --- Trend Identification by Regression --- p.8
Chapter 2.2.3 --- Programming variables --- p.13
Chapter 2.2.4 --- Execution --- p.13
Chapter 3. --- Literature Review --- p.16
Chapter 4. --- Trading Models --- p.19
Chapter 4.1 --- 2Premises --- p.19
Chapter 4.2 --- Trading rules --- p.20
Chapter 4.3 --- THE IMPLEMENTATION OF THE TRADING MODEL AND ITS TESTING --- p.20
Chapter 4.4 --- The Test --- p.23
Chapter 4.5 --- Some Arbitrary Inputs and Limitations --- p.24
Chapter 4.6 --- Preliminary Testing and the Grand Trend --- p.25
Chapter 5. --- RESULT & ANALYSIS --- p.26
Chapter 5.1 --- Deals made along Trends Identified --- p.27
Chapter 5.2 --- Pseudo Trends Identified during Corrections of Trends --- p.30
Chapter 5.3 --- Deals made during Corrections of Trends --- p.30
Chapter 6. --- CONCLUSIONS --- p.33
Chapter 6.1 --- Further Studies Recommended --- p.33
Bibliography --- p.34
Appendices
Chapter a. --- Table1 --- p.35
Chapter b. --- Table2 --- p.36

碩士
國立交通大學
資訊管理研究所
98
This study attempt to find the stock price trend based on the rule-based wave theory. As we review technical analysis of the recent study, found that most research emphasize the technical indicators, but few used stock price patterns as the basis for trend analysis. Elliott Wave Theory is one of the most important theories which stresses the stock price variation with certain regularity and consists eight-wave combination to complete stock market cycle. Therefore, if the entire stock market trend could be effectively expressed by those waves combination, investors could get higher returns and lower risks as long as can catch the trend pattern. This study is based on Hung’s N-wave technical indicator（2009）, and further tries to improve the accuracy by verifying the method of extracting N-shaped wave. In addition, we redefine the variables to improve the model’s efficiency, and then use fewer variables to achieve the better results. In this study, the data are collected from daily TAIEX between 7th Feb.1987 to 6th Feb. 2009. This study performed two experiments: the first experiment is to compare the method of extracting N-type waves between our method and Hung’s. The result shows that our method which employed Elliott Wave characteristic rules are better, both on accuracy and profitability. The second experiment is to compare the result of our methodology and Hung’s. We conclude that we only use 26 parameters (Hung used 58 parameters) can be describe the N-type wave, and accuracy and profitability in both of which have shown superior.

碩士
國立交通大學
管理科學系所
101
Taiwan stock market belongs to a shallow-plate market and the long –term trend is often affected by news with high volatility. The investors often bear a huge risk in the opening of the market because of holding stocks overnight. This study uses the intraday trading of TAIEX Futures to avoid overnight risks. Furthermore, this study attempts to find the stock price trend based on the rule of Elliott wave theory. As we find that most researches emphasize on the technical indicators, reviewing technical analysis of the recent researches, but few on stock price patterns as the basis of the trend analysis. Elliott Wave Theory is one of the most important theories, which stresses the stock price variation with certain regularity and consists of eight-wave combination to complete stock market cycle. Therefore, if the entire stock market trend could be effectively expressed by those waves combination, investors could get higher returns and lower risks as long as we can learn the trend pattern. This study used daily TAIEX from 2008 to 2012 this five years data as the research objective, catching the turning point of the wave from different time sections, then normalized physical force value as input of the Back-propagation neural network to predict the trend of the next wave. At the same time, the different threshold was set with trading strategies and the calling of rules of gain and loss and to calculate their accuracy rate and investment performance. The result shows that the trend of TAIEX is indeed affected by the physical force of price trend. When the time interval is 15 minutes, the investment performance was the largest in the intraday trading. Therefore, we should use the time section of 15 minutes to forecast and analysis when trading in the intraday.

碩士
國立成功大學
國際管理碩士在職專班
97
Two theories are compared, Efficient Market Hypothesis (EMH) and Elliot Wave Theory (EWT), using qualitative analysis in the form of a direct comparison and technical analysis in the form of chart analysis. Classical economic theory and its leading proponent Efficient Market Hypothesis EMH represent the status quo and the idea of rational decision making in financial markets, while Elliot Wave Theory represents the idea of mass irrational behavior which is somewhat predictable. These two theoretical extremes represent contrasting views of how finance markets work. Crude oil is the chosen medium through which these two theories are compared. The comparison is made within the framework of gleaning useful trading and investing advice for an amateur with limited resources. The results do not indicate a clear cut winner, but offers insight into the strengths and weaknesses of either theory, and how an amateur could benefit.

by Chiu Man-cheong and Lo Kin-chung.
Thesis (M.B.A.)--Chinese University of Hong Kong, 1994.
Includes bibliographical references (leave 1 (4th gp.)).
ABSTRACT --- p.iii
TABLE OF CONTENTS --- p.iv
ACKNOWLEDGEMENT --- p.vi
Chapter
Chapter I. --- INTRODUCTION --- p.1
Chapter II. --- LITERATURE REVIEW --- p.4
Variations --- p.7
Ratio Analysis --- p.13
Applications on Real Markets --- p.14
Chapter III. --- METHODOLOGY --- p.16
Wave Counting --- p.20
Fibonacci Targets --- p.22
Data Source --- p.23
A Note on Notations --- p.23
Chapter IV. --- RATIO ANALYSIS --- p.25
Fibonacci Relationships --- p.25
Results of Ratio Analysis --- p.28
Wave 2 --- p.29
Wave 3 --- p.30
Wave 4 --- p.30
Wave 5 --- p.31
Summary of Results
Chapter V. --- FORMULATION OF TRADE PLANS AND RESULTS OF SIMULATED TRADING --- p.32
Formulation of Trade Plans --- p.33
Trade Plan No. 1 --- p.35
Pre-conditions of Trade --- p.35
Trade Initiation --- p.36
Cut-loss Mechanism --- p.38
Profit Taking --- p.39
Trade Plan No. 2 --- p.41
Pre-conditions of Trade --- p.42
Trade Initiation --- p.42
Cut-loss Mechanism --- p.43
Profit Taking Point --- p.44
Trade Opportunities Scan --- p.46
Trade Case 1 --- p.52
Pre-conditions --- p.52
Trade Initiation --- p.52
Profit-taking/Cut-loss --- p.53
Trade Case 2 --- p.54
Pre-conditions --- p.54
Trade Initiation --- p.55
Profit-taking/Cut-loss --- p.56
Trade Case 5 --- p.57
Pre-conditions --- p.57
Trade Initiation --- p.58
Profit-taking/Cut-loss --- p.58
Results of Simulated Trade --- p.59
Discussions on Simulated Trading --- p.62
Chapter VI. --- WAVE ANALYSIS AND MARKET PERSPECTIVES --- p.65
Analysis of the Broadest Swing --- p.66
Phase 1 Price Movement --- p.67
Phase 2 Price Movement --- p.70
Future Market Perspectives --- p.78
Chapter VII. --- DISCUSSIONS --- p.82
Experience in Wave Counting --- p.82
Limitations of Elliott Wave --- p.85
Practical Issues --- p.86
Chapter VIII. --- CONCLUSIONS --- p.92
APPENDICES --- p.A-l
Chapter 1. --- RESULTS OF RATIO ANALYSIS --- p.A-2
Chapter 2. --- DETAILS OF SIMULATED TRADING --- p.A-3
BIBLIOGRAPHY --- p.B-l

碩士
國立交通大學
管理學院資訊管理學程
99
Analyzing Taiwan Stock Trend Based on Elliott Wave Theory—Combining Self-Organizing Map and Back Propagation Neural Network Student：Sung-Mao Chiang Advisor: Dr. An-Pin Chen Institute of Information Management National Chiao Tung University Abstract Institute of Information Management National Chiao Tung University The stock market in Taiwan is a shallow-plate market which is affected by international stock market decline. In recent years, global economic is unstable. Investors will suffer great loss once they do the wrong direction. How to determine which space-time environment are upward, downward is an important issue. Technical analysis for quantitative data and information obtained and compared to fundamental analysis, data analysis of pollution leading to a lower chance of error, for the majority of investors often use investment analysis tool . The Elliott Wave Theory for the recent extensive study of technical analysis. Hong’s study (2009) through the back-propagation neural network parameters into the shape of the wave theory of learning, training, and that the stock market in the presence of physical strength. Chen (2010) filtering characteristics meet all the rules of Elliott Wave theory of N-type waves, which can effectively control the stock market rose fell trend. This study attempts to self-organizing map neural networks, "Like attracts like" feature, the wave theory of parameters to be characterized by different grouping plate potential, combined with back-propagation neural network learning, training and predict its decline in inflation, analysis of different plate potential the physical phenomena. The results show that self-organizing map neural network may be the wave theory of N-type waves for effective clustering and collapse of the power of the most obvious cluster physical note. Turning point in considering the purchase of the third day's closing price that case, the cluster rose a turning point in buying costs are relatively high. This study shows the pattern of investment in chase prices rose to be more careful. Keywords: Elliott Wave Theory、Technical analysis、Self-organizing map neural network、Back-propagation neural network.