TW202213239A - A predicting the trend of stock prices and trade advising system based on neural networks of analyzing multiple technical analysis indicators - Google Patents
A predicting the trend of stock prices and trade advising system based on neural networks of analyzing multiple technical analysis indicators Download PDFInfo
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本發明是有關於一種證劵交易市場之個股股價預測、趨勢預測及交易決策輔助系統,利用蒐集交易相關資訊,自行產生多個相關技術指標後,基於類神經網路根據市場交易資訊及多個技術指標進行分析後,開盤前預測股價預測、股價趨勢分析,並提供交易決策建議之系統。 The present invention relates to a stock price prediction, trend prediction and transaction decision assistance system in the securities trading market. After collecting transaction-related information, after generating a plurality of relevant technical indicators, based on a neural network, according to market transaction information and a plurality of After analyzing the technical indicators, it is a system that predicts the stock price, analyzes the stock price trend, and provides trading decision suggestions before the market opens.
目前存在於股市分析中已有多種技術指標,如隨機指標(Stochastic Oscillator)、相對強弱指標(Relative Strength Index;RSI)、威廉指標(Williams %R)、動向指標(Directional Movement Index;DMI)、平滑異同移動平均線(Moving Average Convergence Divergence;MACD)布林通道(Bolinger Bands)等,但是在輔助交易或是預測股價上,有無法準確分析情形,如隨機指標會有鈍化現象,即指標已呈現目前高點或低點,但是無法得知將來是否會繼續上漲或下跌,而需要以其他指標輔助判斷,而又存有指標間衝突情形,即兩種以上指標呈現不同預測趨勢,而難以判斷漲跌;更存在各個股票交易特性不同,使得適用分析的指標也有所不同情形,且因需要熟稔多種技術指標,而使得人工進行分析時容易有失誤之情形。 At present, there are many technical indicators in stock market analysis, such as Stochastic Oscillator, Relative Strength Index (RSI), Williams %R, Directional Movement Index (DMI), smoothing Similarities and Differences Moving Average (Moving Average Convergence Divergence; MACD) Bollinger Bands, etc., but in auxiliary trading or forecasting stock prices, there are situations that cannot be accurately analyzed. For example, the stochastic indicator will passivate, that is, the indicator has shown the current High point or low point, but it is impossible to know whether it will continue to rise or fall in the future, and it needs to be judged by other indicators, and there is a conflict between indicators, that is, two or more indicators show different forecast trends, and it is difficult to judge the rise or fall ; There are also different trading characteristics of each stock, which makes the indicators suitable for analysis also different, and because of the need to be familiar with a variety of technical indicators, it is easy to make mistakes in manual analysis.
基於證券交易市場分析之技術指標之交易決策,同樣有指標 鈍化、指標間衝突,及各個股票交易特性不同而使用不同指標,而使交易決策判斷無法準確,失去獲利機會。 Trading decisions based on technical indicators of stock market analysis, there are also indicators Passivation, conflict between indicators, and the use of different indicators for different trading characteristics of each stock make trading decisions and judgments inaccurate and lose profit opportunities.
鑒於上述問題,本發明以類神經網路建構股價預測、趨勢分析及交易決策輔助系統,緩化技術指標鈍化、技術指標間衝突問題,建立及分析歷史交易相關資訊(開盤價、最高價、最低價及收盤價等)及多個技術指標數值,於開盤前預測股價、股價趨勢提供判斷,並輔以使用者常用技術指標提供交易(買、賣)決策建議。 In view of the above problems, the present invention constructs a stock price prediction, trend analysis and transaction decision assistance system with a neural network, alleviates the problems of passivation of technical indicators and conflicts between technical indicators, and establishes and analyzes historical transaction related information (opening price, highest price, lowest price) Price and closing price, etc.) and the values of multiple technical indicators, predict the stock price and stock price trend before the market opens to provide judgment, and provide trading (buy, sell) decision-making suggestions with the help of common technical indicators of users.
本發明係以個股歷史交易資訊,自動延展及計算各個技術指標,讓類神經網路系統以多個技術指標及歷史交易資訊作為訓練資料而學習,而由本發明自動協助判斷其他技術指標,減少使用者學習指標時間,使用者僅需熟稔1~2種技術指標。 The present invention uses the historical transaction information of individual stocks to automatically extend and calculate various technical indicators, so that the neural network system can learn from multiple technical indicators and historical transaction information as training data, and the present invention automatically assists in judging other technical indicators, reducing the use of It takes time for users to learn indicators, and users only need to be familiar with 1~2 technical indicators.
本發明分析係以類神經網路連結歷史交易相關資訊、多個技術指標等作為學習資料,可以自動調整將各個技術指標適用於個股股價分析,可以緩化技術指標鈍化及解決指標衝突問題,並以近期資料作為基礎分析而於開盤前預測個股股價。 The analysis system of the present invention uses a neural network to connect historical transaction-related information, multiple technical indicators, etc. as learning materials, and can automatically adjust and apply each technical indicator to the analysis of individual stock prices. Predict the stock price before the market opens based on recent data as the basis for analysis.
本發明包含一數據蒐集系統,進行蒐集欲分析個股之歷史交易相關資訊,個股歷史交易資訊至少包含歷史開盤價、最高價、最低價及收盤價等,且股票市場上各種歷史交易數值皆可以為歷史數據標的,而存入歷史數據資料庫。 The present invention includes a data collection system for collecting historical transaction-related information of individual stocks to be analyzed. The historical transaction information of individual stocks at least includes historical opening price, highest price, lowest price, and closing price, etc., and various historical transaction values in the stock market can be Historical data objects are stored in the historical data database.
本發明包含一資料延展系統,自歷史數據數據資料庫內擷取數據後,自動計算及產生與開盤價格、最高價格、最低價格之關聯數據, 關聯數據至少包含目前使用之技術指標,隨機指標(Stochastic Oscillator)、相對強弱指標、威廉指標、動向指標、平滑異同移動平均線、布林通道等,並存入基礎數據資料庫,資料延展系統具將來擴充性,得於開發新技術指標後再擴充。 The present invention includes a data extension system, which automatically calculates and generates associated data with the opening price, the highest price and the lowest price after retrieving data from the historical data database, The associated data includes at least the currently used technical indicators, Stochastic Oscillator, relative strength indicator, Williams indicator, trend indicator, smoothed moving average of similarities and differences, Bollinger Bands, etc., and stored in the basic data database. The data extension system has Future expansion can be expanded after the development of new technical indicators.
本發明包含一類神經網路股價分析系統,以數據資料庫資料作為類神經網路之學習數據,而自動建立基礎數據資料庫各數值與歷史股價關聯權重後,並基於基礎數據資料庫於開盤前預測交易最高價、最低價、收盤價及漲跌。 The invention includes a neural network stock price analysis system, which uses data database data as the learning data of the neural network, and automatically establishes the correlation weight between each value of the basic data database and the historical stock price, and based on the basic data database before the opening of the market Predict the highest price, lowest price, closing price and ups and downs of trading.
本發明包含一股價趨勢預測系統,依據類神經網路股價分析系統盤前預測之交易最高價、最低價、收盤價及漲跌,以預測股價漲、跌或平盤。 The invention includes a stock price trend prediction system, which predicts the stock price up, down or flat according to the pre-market trading highest price, lowest price, closing price and ups and downs predicted by the neural network stock price analysis system.
本發明包含一決策輔助系統,以常用隨機指標、布林通道等做基礎,如於KD交叉或股價於碰到通道上軌線或下軌線時,輔以股價趨勢預測系統分析趨勢,緩化解決單靠技術指標發生鈍化而失準情形,並輸出決策買進或賣出。 The present invention includes a decision-making assistance system, based on commonly used stochastic indicators, Bollinger channels, etc., for example, when KD crosses or the stock price hits the upper or lower trajectory of the channel, it is supplemented by a stock price trend prediction system to analyze the trend and slow down the Solve the situation of inaccuracy due to passivation of technical indicators alone, and output a decision to buy or sell.
10:使用者介面 10: User Interface
20:類神經網路分析多技術指標之股價趨勢預測及交易決策輔助系統 20: Neural network-like analysis of multi-technical indicators for stock price trend prediction and transaction decision-making assistance system
21:數據蒐集系統 21: Data collection system
22:歷史數據資料庫 22: Historical Data Repository
23:資料延展系統 23: Data extension system
24:基礎數據資料庫 24: Basic Data Repository
25:類神經網路股價分析系統 25: Neural network-like stock price analysis system
26:股價趨勢預測系統 26: Stock price trend prediction system
27:交易決策輔助系統 27: Trading Decision Aid System
圖一為本發明之系統架構圖。 FIG. 1 is a system architecture diagram of the present invention.
為利理解本發明之技術特徵、內容與優點及其所能達成之功效,爰以圖示及以實施例之表達形式詳細說明本發明,而所使用之圖示,僅為示意及輔助說明使用,未必與本發明實施後之真實比例與精準配置,故不應就所附圖示之比例與配置關係解讀,而侷限本發明於實際實施上之 權利。 In order to facilitate the understanding of the technical features, content and advantages of the present invention and the effects that can be achieved, the present invention is described in detail with diagrams and in the form of embodiments, and the diagrams used are only for illustration and auxiliary description. , which may not necessarily correspond to the real proportions and precise configurations of the present invention after the implementation of the present invention. Therefore, the relationship between the proportions and configurations shown in the accompanying drawings should not be interpreted, but to limit the present invention to the actual implementation. right.
請參閱圖1,圖1係繪示本發明一實施例之一種類神經網路分析多技術指標之股價趨勢預測及交易決策輔助系統各模組之架構圖,整體系統包含使用者介面10及類神經網路分析多技術指標之股價趨勢預測及交易決策輔助系統20。使用者介面10用以輸入欲分析之個股及接收系統輸出結果。交易決策輔助系統20包含數據蒐集系統21、歷史數據資料庫22、資料延展系統23、基礎數據資料庫24、類神經網路股價分析系統25、股價趨勢預測系統26及交易決策輔助系統27。
Please refer to FIG. 1. FIG. 1 is a diagram showing the structure of each module of the stock price trend prediction and transaction decision assistance system of a kind of neural network analysis of multi-technical indicators according to an embodiment of the present invention. The overall system includes a
依據本發明之實施例,數據蒐集系統21,蒐集欲分析個股之各種歷史交易相關資訊,至少包含歷史最高價、最低價、開盤價、成交價等,輸入方式可以藉由使用者輸入或是自動蒐集,並將資料存入至歷史資料庫22,作為將來計算之基礎數據。
According to an embodiment of the present invention, the
依據本發明之實施例,資料延展系統23將自歷史資料庫中擷取資料後,自動計算各個技術指標,至少包含且不限於隨機指標、相對強弱指標、威廉指標、平滑異同移動平均線、動向指標及布林通道等,並保留將來設計新指標,延展與股價相關之資訊,強化歷史股價資訊與各個歷史相關資訊之特徵及關連,而將歷史交易相關資訊及延展所得數據資料存入基礎數據資料庫24。
According to the embodiment of the present invention, the
依據本發明之實施例,類神經網路股價分析系統25以基礎數據資料庫24作為訓練資料,基礎數據資料庫至少包含且不限於歷史交易相關資訊、隨機指標、布林通道、威廉指數、相對強弱指標、動向指標等,並得增加及擴充,而作為訓練資料,並以個股之歷史交易最高價、最低價、
收盤價及漲跌作為驗證資料,以類神經網路進行關聯及訓練,建立各個指標數值與歷史交易資訊關聯,而分析並產生預測之個股交易資訊,使用者僅需熟稔1至2個技術指標作為基礎判斷,系統自動協助分析其他各輸入之指標,簡化交易人員之判斷並減少人工判斷失誤。
According to the embodiment of the present invention, the neural network-like stock
依據本發明之實施例,股價趨勢預測系統26以類神經網路股價分析系統25於開盤前預測之個股最高價、最低價、收盤價及漲跌作為預測股價趨勢,預測系統以2種模式進行股價趨勢預測:一般信心模式及強化信心模式。
According to an embodiment of the present invention, the stock price
一般信心模式:類神經網路股價分析系統25預測之個股最高價及最低價均高於前一日收盤之最高價及最低價,則股價趨勢預測系統26預測個股股價將上漲;類神經網路股價分析系統25預測之個股最高價及最低價均低於前一日收盤之最高價及最低價,股價趨勢預測系統26預測個股股價將下跌;如類神經網路股價分析系統25預測之個股最高價及最低價趨勢不一致,則判斷未知。
General confidence model: the highest and lowest prices of individual stocks predicted by the neural network-like stock
強化信心模式:類神經網路股價分析系統25預測之個股最高價、最低價及收盤價均高於前一日收盤之最高價、最低價及收盤價,股價趨勢預測系統26預測個股股價將上漲;類神經網路股價分析系統25預測之個股最高價、最低價及收盤價均低於前一日收盤之最高價、最低價及收盤價,股價趨勢預測系統26預測個股股價將下跌;如非屬前述情形,則判斷未知。
Confidence enhancement mode: The highest, lowest and closing prices of individual stocks predicted by the neural network-like stock
依據本發明之實施例,於交易決策輔助系統27,使用者得選定常用之技術指標,輔以股價趨勢預測系統26輸出之股價趨勢判斷,如隨
機指標值KD交叉,當K值從低檔往上突破D值的時候,一般認為是買入交易訊號,但是實際上仍存有KD鈍化,股價仍會繼續下跌風險,藉由本發明之股價趨勢預測系統26判斷次一日之股價趨勢,得緩和原技術指標鈍化之瓶頸及風險,提高獲利成功率。
According to the embodiment of the present invention, in the transaction
10:使用者介面 10: User Interface
20:類神經網路分析多技術指標之股價趨勢預測及交易決策輔助系統 20: Neural network-like analysis of multi-technical indicators for stock price trend prediction and transaction decision-making assistance system
21:數據蒐集系統 21: Data collection system
22:歷史數據資料庫 22: Historical Data Repository
23:資料延展系統 23: Data extension system
24:基礎數據資料庫 24: Basic Data Repository
25:類神經網路股價分析系統 25: Neural network-like stock price analysis system
26:股價趨勢預測系統 26: Stock price trend prediction system
27:交易決策輔助系統 27: Trading Decision Aid System
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CN115659832B (en) * | 2022-11-08 | 2023-07-18 | 中国交通信息科技集团有限公司 | Enterprise operation analysis and early warning monitoring method and system based on big data analysis |
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