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Journal articles on the topic 'Candlestik'

Author: Grafiati

Published: 10 March 2023

Last updated: 19 July 2025

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1

Piasecki, Krzysztof, and Anna Łyczkowska-Hanćkowiak. "Representation of Japanese Candlesticks by Oriented Fuzzy Numbers." Econometrics 8, no. 1 (2019): 1. http://dx.doi.org/10.3390/econometrics8010001.

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The Japanese candlesticks’ technique is one of the well-known graphic methods of dynamic analysis of securities. If we apply Japanese candlesticks for the analysis of high-frequency financial data, then we need a numerical representation of any Japanese candlestick. Kacprzak et al. have proposed to represent Japanese candlesticks by ordered fuzzy numbers introduced by Kosiński and his cooperators. For some formal reasons, Kosiński’s theory of ordered fuzzy numbers has been revised. The main goal of our paper is to propose a universal method of representation of Japanese candlesticks by revised

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Mardianti, Nayla. "Analysis and Study of Candlestick Indicators in Stock Trading." Enigma in Economics 1, no. 2 (2024): 55–58. http://dx.doi.org/10.61996/economy.v1i2.32.

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Candlestick analysis is an invaluable tool in technical analysis for understanding stock price movements. Candlesticks provide a clear visual representation of changes in stock prices over a certain period of time. The color and shape of the candlesticks provide a direct indication of buyer and seller sentiment. A series of candlesticks with continuously light colored bodies indicates an uptrend, while continuously dark colored bodies indicate a downtrend. This helps traders identify the direction of overall price movement. Candlestick patterns, such as doji, engulfing, harami, and others, pro

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EL YOUSSEFI, Ahmed, Abdelaaziz HESSANE, Imad Zeroual, and Yousef FARHAOUI. "Utilizing Machine Learning and Deep Learning for Predicting Crypto-currency Trends." Salud, Ciencia y Tecnología - Serie de Conferencias 3 (March 11, 2024): 638. http://dx.doi.org/10.56294/sctconf2024638.

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In the dynamic and often volatile world of the cryptocurrency market, accurately predicting future market movements is crucial for making informed trading decisions. While manual trading involves traders making subjective judgments based on market observations, the development of algorithmic trading systems, incorporating Machine Learning and Deep Learning, has introduced a more systematic approach to trading. These systems often employ technical analysis and machine learning techniques to analyze historical price data and generate trading signals. This study delves into a comparative analysis

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Orquín-Serrano, Ismael. "Predictive Power of Adaptive Candlestick Patterns in Forex Market. Eurusd Case." Mathematics 8, no. 5 (2020): 802. http://dx.doi.org/10.3390/math8050802.

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The Efficient Market Hypothesis (EMH) states that all available information is immediately reflected in the price of any asset or financial instrument, so that it is impossible to predict its future values, making it follow a pure stochastic process. Among all financial markets, FOREX is usually addressed as one of the most efficient. This paper tests the efficiency of the EURUSD pair taking only into consideration the price itself. A novel categorical classification, based on adaptive criteria, of all possible single candlestick patterns is presented. The predictive power of candlestick patte

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Karmelia, Meilona, Moeljono Widjaja, and Seng Hansun. "Candlestick Pattern Classification Using Feedforward Neural Network." International Journal of Advances in Soft Computing and its Applications 14, no. 2 (2022): 80–95. http://dx.doi.org/10.15849/ijasca.220720.06.

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Investment in the capital market can help boost a country’s economic growth. Without a doubt, in investing, a technical analysis of the condition of the stock is needed at that time. One of the technical analyses that can be done is to look at the historical data of stocks. Candlestick charts can summarize historical data that contain price value for Open, High, Low, and Close (OHLC) in the form of a chart. A group of candlesticks will form a pattern that can help investors to see whether the stock is trending up or down. The number of candlestick patterns and the manual determination of candl

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Mersal, Edrees Ramadan, Kürşat Mustafa Karaoğlan, and Hakan Kutucu. "Enhancing market trend prediction using convolutional neural networks on Japanese candlestick patterns." PeerJ Computer Science 11 (February 27, 2025): e2719. https://doi.org/10.7717/peerj-cs.2719.

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This study discusses using Japanese candlestick (JC) patterns to predict future price movements in financial markets. The history of candlestick trading dates back to the 17th century and involves the analysis of patterns formed during JC trading. Candlestick patterns are practical tools for the technical analysis of traders in financial markets. They may serve as indicators of traders’ documents of a potential change in market sentiment and trend direction. This study aimed to predict the following candle-trend-based JC charts using convolutional neural networks (CNNs). In order to enhance th

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Puteri, Annisa Nurul, Suryadi Syamsu, Topan Leoni Putra, and Andita Dani Achmad. "Support Vector Machine for Predicting Candlestick Chart Movement on Foreign Exchange." MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer 22, no. 2 (2023): 249–60. http://dx.doi.org/10.30812/matrik.v22i2.2676.

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Foreign Exchange, commonly called Forex, is a form of investment in the non-real sector in great demand. Forex is a marketplace that specializes in foreign exchange trading. Technology advancements have made it easy to monitor investment conditions in real time and present them in an easyto - understand graphical form. As a result, predictions are closely related to investment, starting from market sentiment and economic conditions to technical matters. One of the Artificial Intelligence methods that can be used in classifying is the Support Vector Machine (SVM). SVM is a machine learning clas

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Joshi, Dushyant Lal. "Prediction of NEPSE Index Movement Using Technical Analysis." Nepal Journal of Multidisciplinary Research 6, no. 2 (2023): 106–13. http://dx.doi.org/10.3126/njmr.v6i2.57475.

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Due to the nature of the stock and index, predicting index or price movements is a challenging task. The nature of index volatility makes it impossible for investors to profit from stocks. To address this problem, investors need to make accurate predictions about future index or stock price changes. In this study, data has collected for 6 months (December 2022 to May 2023) and technical trading tools such as candlesticks and Google Form Questionnaire Surveys were used to determine the movement of the NEPSE index. A questionnaire survey is completed with 62 answers. Given the Nepalese context a

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Kim, Dasol. "Domesticating the Body of the Exotic Other: The Multisensory Use of a Sixteenth-century Brass Candlestick." Das Mittelalter 25, no. 2 (2020): 311–37. http://dx.doi.org/10.1515/mial-2020-0040.

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AbstractThrough the medium of a brass candlestick made in a sixteenth-century German foundry, I discuss the Christian European household’s sensory engagement and spatial control of the Muslim body. I argue that the Europeans’ sensory experience of the turbaned candlestick reflects and reinforces their conceptualization of Islamic culture, which is a blend of fear and fascination. The turbaned candlestick allows us to explore issues rarely discussed in the study of metalwork and the European imagery of ‘the East’. The shape and scale of the candlestick suggest that it could have been treated bo

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Cahyadi, Yoyo. "Analisis Pola Grafik Candlestick pada Pergerakan EUR/USD." Binus Business Review 3, no. 2 (2012): 737. http://dx.doi.org/10.21512/bbr.v3i2.1357.

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Candlestick chart is one of the charts which is commonly used in technical analysis. Besides for price overview in the past, this chart has patterns that can be analysed to become guidance about next price movement. There are some patterns with specific name in candlestick chart analysis. This paper discusses candlestick chart patterns in the EUR/USD currency pair within daily time frame. The observation shows that candlestick chart patterns indeed gave more guidance about trend changes. Although the candlestick patternsdid not show everyday, in most cases the patterns gave right guidance.

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Ramadhan, Aditya, Irma Palupi, and Bambang Ari Wahyudi. "Candlestick Patterns Recognition using CNN-LSTM Model to Predict Financial Trading Position in Stock Market." Journal of Computer System and Informatics (JoSYC) 3, no. 4 (2022): 339–47. http://dx.doi.org/10.47065/josyc.v3i4.2133.

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Investors need analytical tools to predict the price and to determine trading positions. Candlestick pattern is one of the analytical tools that predict price trends. However, the patterns are difficult to recognize, and some studies show doubts regarding the robustness of the recognizing system. In this study, we tested the predictive ability of candlestick patterns to determine trading positions. We use Gramian Angular Field (GAF) to encode candlestick patterns as images to recognize 3-hour and 5-hour of 6 candlestick patterns with Convolutional Neural Network (CNN), coupled with the Long sh

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Adhiwibowo, Whisnumurti, and Ali As ari. "CUSTOM INDIKATOR PELACAK POLA REVERSAL CANDLESTICK PADA METATRADER 4 MENGGUNAKAN BAHASA PEMROGRAMAN METAQUOTE LANGUAGE 4." Jurnal Pengembangan Rekayasa dan Teknologi 5, no. 1 (2021): 38. http://dx.doi.org/10.26623/jprt.v17i1.3637.

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Kegiatan transaksi pada pasar keuangan terdapat berbagai cara untuk menganalisa dan memprediksi tren atau pergerakan harga dari instrumen keuangan. Salah satu cara menganalisa pergerakan harga dengan mempelajari pola candlestick pembalikan arah tren. Kendala yang dihadapi pada saat menganalisa menggunakan pola candlestick pembalikan arah adalah banyaknya pola dan aturan yang dimiliki untuk menentukan suatu pola pembalikan arah tren pada candlestick. Oleh sebab itu dibutuhkan sebuah alat atau indikator yang dapat menganalisa dan memberikan informasi pola pembalikan arah tren pada candlestick. D

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Prasad, Kulkarni, and Murugaiah V. Dr. "Japanese Candlestick Trading Strategies: A Review of Literature." RESEARCH REVIEW International Journal of Multidisciplinary 03, no. 07 (2018): 469–74. https://doi.org/10.5281/zenodo.1323120.

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The purpose of this study is to review the evidence on the performance of Japanese candlestick trading strategies. To achieve this, the study comprehensively reviews survey, theoretical and empirical studies on the subject of candlestick trading strategies and discusses the consistency and reliability of candlestick trading across markets and over time. The majority of the studies were collected from academic journals published from 1998 to the present and recent working papers, books and magazines. The reviews are arranged under two sections, first section contains review of studies that stat

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Rediehs, Laura. "Candlestick Mysteries*." Quaker Studies 18, no. 2 (2014): 151–69. http://dx.doi.org/10.3828/quaker.18.2.151.

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Li, Xinglong, Qingyang Liu, Yanrong Hu, and Hongjiu Liu. "The Double-Layer Clustering Based on K-Line Pattern Recognition Based on Similarity Matching." Information 15, no. 12 (2024): 821. https://doi.org/10.3390/info15120821.

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Candlestick charts provide a visual representation of price trends and market sentiment, enabling investors to identify key trends, support, and resistance levels, thus improving the success rate of stock trading. The research presented in this paper aims to overcome the limitations of traditional candlestick pattern analysis, which is constrained by fixed pattern definitions, quantity limitations, and subjectivity in pattern recognition, thus improving its effectiveness in dynamic market environments. To address this, a two-layer clustering method based on a candlestick sequence simlarity mat

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Samadan, Ajwanor Razka Ibadilah, and Andreas Kiky. "Analisis Probabilitas Pola Candlestick terhadap Pergerakan Harga Pada Pasar Saham Indonesia." RIGGS: Journal of Artificial Intelligence and Digital Business 4, no. 2 (2025): 1–6. https://doi.org/10.31004/riggs.v4i2.445.

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Penelitian ini bertujuan untuk menganalisis probabilitas pola candlestick terhadap pergerakan harga pada pasar saham Indonesia. Pendekatan statistik digunakan untuk mengukur seberapa akurat pola candlestick dalam memprediksi arah harga saham. Data yang digunakan adalah data historis saham yang terdaftar di Bursa Efek Indonesia (BEI) dengan periode tertentu. Metode penelitian melibatkan analisis statistik deskriptif, penghitungan probabilitas, dan pengujian hipotesis. Hasil penelitian ini diharapkan dapat memberikan wawasan kepada investor mengenai efektivitas analisis teknikal khususnya pola c

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Ardiyanti, Ni Putu Winda, Irma Palupi, and Indwiarti Indwiarti. "Trading Strategy on Market Stock by Analyzing Candlestick Pattern using Artificial Neural Network (ANN) Method." JURNAL MEDIA INFORMATIKA BUDIDARMA 5, no. 4 (2021): 1273. http://dx.doi.org/10.30865/mib.v5i4.3266.

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Technical analysis plays an important role in a stock market. Traders using technical analysis to find the trading strategy on the market stock. There are some technical indicators tools that can support the technical analysis, such as Moving Average, Stochastic, and others. Candlestick pattern also parts of the tools that used in technical analysis to develop the trading strategy since Candlestick represents the stock behavior. Therefore, understanding the Candlestick pattern and technical indicator tools will be valuable for the traders to predict the trading strategy. This study performs th

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Li, Yifan, Ingmar Nolte, Sandra Nolte, and Shifan Yu. "Realized candlestick wicks." Journal of Econometrics 250 (July 2025): 106014. https://doi.org/10.1016/j.jeconom.2025.106014.

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Xu, Rui, Xiaoming Liu, Hang Wan, Xipeng Pan, and Jian Li. "A Feature Extraction and Classification Method to Forecast the PM2.5 Variation Trend Using Candlestick and Visual Geometry Group Model." Atmosphere 12, no. 5 (2021): 570. http://dx.doi.org/10.3390/atmos12050570.

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Currently, the continuous change prediction of PM2.5 concentration is an air pollution research hotspot. Combining physical methods and deep learning models to divide the pollution process of PM2.5 into effective multiple types is necessary to achieve a reliable prediction of the PM2.5 value. Therefore, a candlestick chart sample generator was designed to generate the candlestick chart from the online PM2.5 continuous monitoring data of the Guilin monitoring station site. After these generated candlestick charts were analyzed through the Gaussian diffusion model, it was found that the characte

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Ho, Trang-Thi, and Yennun Huang. "Stock Price Movement Prediction Using Sentiment Analysis and CandleStick Chart Representation." Sensors 21, no. 23 (2021): 7957. http://dx.doi.org/10.3390/s21237957.

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Determining the price movement of stocks is a challenging problem to solve because of factors such as industry performance, economic variables, investor sentiment, company news, company performance, and social media sentiment. People can predict the price movement of stocks by applying machine learning algorithms on information contained in historical data, stock candlestick-chart data, and social-media data. However, it is hard to predict stock movement based on a single classifier. In this study, we proposed a multichannel collaborative network by incorporating candlestick-chart and social-m

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Wicaksono, Soetam Rizky, Rudy Setiawan, and Purnomo. "Candlestick Pattern Research Analysis, Future and Beyond: A Systematic Literature Review Using PRISMA." Journal of Computer Science and Technology Studies 4, no. 2 (2022): 157–64. http://dx.doi.org/10.32996/jcsts.2022.4.2.19.

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Online stock market circumstances allow traders to examine in real time or periodically with free or paid criteria and indicators. Candlestick charts and historical data help traders predict stock values. These forecasting methods rely on traders' experience. Such unscientific judgements lack empirical facts and mathematically established theories, which are rarely published in recognized scientific journals. Initial research revealed a gap between candlestick research and practice, creating a novel idea without scientific backing. Given the different study possibilities, the literature review

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Nikam, Nikita. "Stock Prediction Using AIML Based on Candlestick Chart Analysis." International Journal for Research in Applied Science and Engineering Technology 13, no. 4 (2025): 6867–70. https://doi.org/10.22214/ijraset.2025.69957.

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Abstract: This research presents a novel approach to stock market prediction through the application of Artificial Intelligence and Machine Learning (AIML), with a focus on candlestick chart analysis. Candlestick patterns, widely regarded as essential tools in technical analysis, provide key insights into market sentiment and potential price reversals. However, their manual interpretation can be subjective and limited by human error. In this paper, AIML techniques, particularly Support Vector Machines (SVM) and Convolutional Neural Networks (CNN), are leveraged to automate the identification o

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V.Patil, DR Siddheshwar. "10.55041/IJSREM47795." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem47795.

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Accurate stock market forecasting remains a challenging task due to the unpredictable and volatile nature of financial data. Traditional methods like candlestick chart analysis have helped traders interpret market trends visually, but they often lack predictive capability. In this study, we propose a hybrid model that integrates candlestick pattern recognition with the Prophet algorithm— a time-series forecasting tool developed by Facebook. The model is trained on historical OHLC (Open, High, Low, Close) data from the NIFTY 50 index, with an emphasis on capturing both short- term volatility an

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Leonardo, Johan, and Rilla Gantino. "ANALISA TEKNIKAL PEMBUATAN TRADING PLAN KEPUTUSAN INVESTASI PADA 3 SAHAM PERBANKAN BUMN YANG TERDAFTAR PADA INDEKS LQ45 TAHUN 2014 - 2019." Jurnal Riset Akuntansi 13, no. 2 (2021): 174–85. http://dx.doi.org/10.34010/jra.v13i2.4651.

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Tujuan dari penelitian ini adalah untuk memperoleh bukti empiris tentang pengaruh candlestick, level support dan level resistance, trendline, dan Moving Average Convergence Divergence (MACD) terhadap pengambilan keputusan investasi. Sampel dalam penelitian ini adalah perusahaan perbankan yang terdaftar di Bursa Efek Indonesia selama periode 2014â€“2019. Sumber data penelitian ini berasal dari sotfware pro trader. Penelitian ini menggunakan pendekatan kualitatif dengan metode analisis deskriptif. Hasil dalam penelitian ini menemukan bahwa candlestick, level support dan level resistance, trendli

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Wang, Jun, Xiaohan Li, Huading Jia, Tao Peng, and Jinghua Tan. "Predicting Stock Market Volatility from Candlestick Charts: A Multiple Attention Mechanism Graph Neural Network Approach." Mathematical Problems in Engineering 2022 (September 13, 2022): 1–16. http://dx.doi.org/10.1155/2022/4743643.

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As an important part of financial market, stock market price volatility analysis has been the focus of academic and industry attention. Candlestick chart, as the most widely used indicator for evaluating stock market price volatility, has been intensively studied and explored. With the continuous development of computer technology, the stock market analysis method based on candlestick chart is gradually changed from manual to intelligent algorithm. However, how to effectively use stock market graphical indicators to analyze stock market price fluctuations has been pending solution, and deep le

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Tharavanij, Piyapas, Vasan Siraprapasiri, and Kittichai Rajchamaha. "Profitability of Candlestick Charting Patterns in the Stock Exchange of Thailand." SAGE Open 7, no. 4 (2017): 215824401773679. http://dx.doi.org/10.1177/2158244017736799.

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This article investigates the profitability of candlestick patterns. The holding periods are 1, 3, 5, and 10 days. Two exit strategies are studied. One is the Marshall–Young–Rose (MYR) exit strategy and the other is the Caginalp–Laurent (CL) exit strategy. The MYR applies a prespecified date to exit the market. In contrast, the CL sets an exit price equal to an average holding period closing price, assuming that investors liquidate their positions evenly within this period. The daily data include open, high, low, and close prices of component stocks of the SET50 index (the 50 largest capitaliz

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Flynn, Richard. "Critic over the candlestick." Lion and the Unicorn 21, no. 3 (1997): 453–56. http://dx.doi.org/10.1353/uni.1997.0016.

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Walkiewicz, M. R., P. J. Fox, and R. E. Scholten. "Candlestick rubidium beam source." Review of Scientific Instruments 71, no. 9 (2000): 3342–44. http://dx.doi.org/10.1063/1.1288261.

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Deng, Shangkun, Zhihao Su, Yanmei Ren, Haoran Yu, Yingke Zhu, and Chenyang Wei. "Can Japanese Candlestick Patterns be Profitable on the Component Stocks of the SSE50 Index?" SAGE Open 12, no. 3 (2022): 215824402211178. http://dx.doi.org/10.1177/21582440221117803.

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In this study, we investigate the profitability of 10 well-known Japanese candlestick charting patterns using daily-based data on the component stocks of the Chinese SSE50 index, which involves a lengthy sample period from January 2000 to December 2018. The main contribution of this paper is that we conduct the first predictive power examination of Japanese candlestick patterns on the Chinese SSE50 stocks while taking into account trend and overbought/oversold conditions, and their profitability over different holding periods. Experimental results indicate that several bullish candlestick patt

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Hsu, Yu-Chia. "Using Machine Learning and Candlestick Patterns to Predict the Outcomes of American Football Games." Applied Sciences 10, no. 13 (2020): 4484. http://dx.doi.org/10.3390/app10134484.

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Match outcome prediction is a challenging problem that has led to the recent rise in machine learning being adopted and receiving significant interest from researchers in data science and sports. This study explores predictability in match outcomes using machine learning and candlestick charts, which have been used for stock market technical analysis. We compile candlestick charts based on betting market data and consider the character of the candlestick charts as features in our predictive model rather than the performance indicators used in the technical and tactical analysis in most studies

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Chen, Xiaozhou, Wenping Hu, and Lei Xue. "Stock Price Prediction Using Candlestick Patterns and Sparrow Search Algorithm." Electronics 13, no. 4 (2024): 771. http://dx.doi.org/10.3390/electronics13040771.

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Accurately forecasting the trajectory of stock prices holds crucial significance for investors in mitigating investment risks and making informed decisions. Candlestick charts visually depict price information and the trends in stocks, harboring valuable insights for predicting stock price movements. Therefore, the challenge lies in efficiently harnessing candlestick patterns to forecast stock prices. Furthermore, the selection of hyperparameters in network models has a profound impact on the forecasting outcomes. Building upon this foundation, we propose a stock price prediction model SSA-CPB

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Stasiak, Michał Dominik. "Candlestick—The Main Mistake of Economy Research in High Frequency Markets." International Journal of Financial Studies 8, no. 4 (2020): 59. http://dx.doi.org/10.3390/ijfs8040059.

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One of the key problems of researching the high-frequency financial markets is the proper data format. Application of the candlestick representation (or its derivatives such as daily prices, etc.), which is vastly used in economic research, can lead to faulty research results. Yet, this fact is consistently ignored in most economic studies. The following article gives examples of possible consequences of using candlestick representation in modelling and statistical analysis of the financial markets. Emphasis should be placed on the problem of research results being detached from the investing

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Kulinich, A. A. "SPECIFIC OF THE GLOUCERSTER CANDLESTICK''S EKPHRASIS IN THE NOVEL “THE CHILDREN''S BOOK” BY A.S. BYATT." Juvenis scientia, no. 8 (August 30, 2018): 22–24. http://dx.doi.org/10.32415/jscientia.2018.08.05.

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The article deals with the Gloucerster candlestick's ekphrasis in the novel «The Children's Book» by Antonia Byatt, a famous English writer of the 20th century. Pictorial ekphrasises of the candlestick are analysed in the text through their functions. Ekphrasises of different artefacts have been analysed by modern scholars, the author's works included, but no detailed analysis of the phenomen under study (the Gloucerster candlestick) has been an object of literary research yet, which shows novelty and actual importance of the analysed issue.

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Kiky, Andreas, and Ika Yanuarti. "Candlestick Accuracy and Investor Gain." International Review of Business Research Papers 13, no. 1 (2017): 66–77. http://dx.doi.org/10.21102/irbrp.2017.03.131.05.

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Dwayne Brenna. "Candlestick Park, San Francisco 1984." NINE: A Journal of Baseball History and Culture 18, no. 2 (2010): 158. http://dx.doi.org/10.1353/nin.0.0087.

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Senanayaka, N. I. M. B., and H. A. Pathberiya. "Effectiveness of Using Candlestick Charts to Forecast Ethereum Price Direction: A Machine Learning Approach." Sri Lankan Journal of Applied Statistics 25, no. 1 (2024): 34–48. http://dx.doi.org/10.4038/sljas.v25i1.8131.

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Cryptocurrency is a form of decentralized digital currency. Ethereum is the second-largest cryptocurrency by market capitalization and the largest altcoin. Cryptocurrencies including Ethereum are highly volatile. Hence, shortterm directional forecasts in the cryptocurrency market have become a widely discussing topic. Candlestick charts are useful visualizations of the open, high, low and close prices which can identify patterns and gauge the near-term direction of prices. This research explores the effectiveness of forecasting hourly Ethereum closing price direction based on candlestick chart

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G. P, Kavya, Prof Mr Touffiq, and Prof Rajshekar Cgoudar. "Candlestick Patterns Trading Strategies A Systematic Review." International Journal of Research Publication and Reviews 5, no. 5 (2024): 5582–86. http://dx.doi.org/10.55248/gengpi.5.0524.1259.

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Pan, Wei, Jide Li, and Xiaoqiang Li. "Portfolio Learning Based on Deep Learning." Future Internet 12, no. 11 (2020): 202. http://dx.doi.org/10.3390/fi12110202.

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Traditional portfolio theory divides stocks into different categories using indicators such as industry, market value, and liquidity, and then selects representative stocks according to them. In this paper, we propose a novel portfolio learning approach based on deep learning and apply it to China’s stock market. Specifically, this method is based on the similarity of deep features extracted from candlestick charts. First, we obtained whole stock information from Tushare, a professional financial data interface. These raw time series data are then plotted into candlestick charts to make an ima

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Uzun, Illia, Mykhaylo Lobachev, Vyacheslav Kharchenko, Thorsten Schöler, and Ivan Lobachev. "Candlestick Pattern Recognition in Cryptocurrency Price Time-Series Data Using Rule-Based Data Analysis Methods." Computation 12, no. 7 (2024): 132. http://dx.doi.org/10.3390/computation12070132.

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In the rapidly evolving domain of cryptocurrency trading, accurate market data analysis is crucial for informed decision making. Candlestick patterns, a cornerstone of technical analysis, serve as visual representations of market sentiment and potential price movements. However, the sheer volume and complexity of cryptocurrency price time-series data presents a significant challenge to traders and analysts alike. This paper introduces an innovative rule-based methodology for recognizing candlestick patterns in cryptocurrency markets using Python. By focusing on Ethereum, Bitcoin, and Litecoin,

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Lin, Yaohu, Shancun Liu, Haijun Yang, Harris Wu, and Bingbing Jiang. "Improving stock trading decisions based on pattern recognition using machine learning technology." PLOS ONE 16, no. 8 (2021): e0255558. http://dx.doi.org/10.1371/journal.pone.0255558.

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PRML, a novel candlestick pattern recognition model using machine learning methods, is proposed to improve stock trading decisions. Four popular machine learning methods and 11 different features types are applied to all possible combinations of daily patterns to start the pattern recognition schedule. Different time windows from one to ten days are used to detect the prediction effect at different periods. An investment strategy is constructed according to the identified candlestick patterns and suitable time window. We deploy PRML for the forecast of all Chinese market stocks from Jan 1, 200

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Nugroho, Fauyhi Eko. "TRADING OTOMATIS PERDAGANGAN FOREX MENGGUNAKAN METODE MARTINGALE DAN CANDLESTICK SEBAGAI ACUAN TRANSAKSI DI EXNESS." Simetris : Jurnal Teknik Mesin, Elektro dan Ilmu Komputer 7, no. 1 (2016): 153. http://dx.doi.org/10.24176/simet.v7i1.499.

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Perdagangan forex merupakan suatu perdagangan mata uang asing dimana seorang trader mendapatkan keuntungan dari perbedaan nilai mata uang satu dengan mata uang asing lainnya yang dapat berubah-ubah secara berkala. Salah satu faktor analisa dalam keputusan jual beli dalam perdagangan forex adalah menggunakan analisa teknikal. Analisa teknikal menggunakan data dan metode statistik berdasarkan data histori harga untuk mendukung keputusan jual atau beli. Trader sering mengalami loss karena emosi dan psikologis. Faktor emosi dan psikologis yang dimaksud diantaranya adalah keserakahan, kelelahan, ku

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Farhan, Andi, Tjetjep Djuwarsa, and Radia Purbayati. "Analisis Teknikal Pergerakan Saham PT Bank Jago Tbk dengan Menggunakan Indikator Candlestick dan Moving Average Convergence Divergence." Indonesian Journal of Economics and Management 2, no. 3 (2022): 517–25. http://dx.doi.org/10.35313/ijem.v2i3.3783.

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This study aims to determine the movement of shares of PT Bank Jago Tbk for the period January 1 – May 20 2022 using candlestick indicators and Moving Average Convergence Divergence (MACD), this study focuses on the economic aspect. The method used is descriptive method. The type of data used is qualitative data. The source of data used is secondary data obtained from charts on tradingview.com tools. Referring to the results of the analysis that has been carried out, the movement of PT Bank Jago Tbk's shares shows a decline (downtrend) using both candlestick and MACD indicators. This indicates

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Gruber, Ruth Ellen. "(Candle)sticks on Stone: The Representation of Women in Jewish Tombstone Art." Jewish Folklore and Ethnology 2, no. 1 (2023): 141–64. http://dx.doi.org/10.1353/jfe.2023.a928447.

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Abstract: Candles and candlesticks are a common and potent symbol on the gravestones of Jewish women because lighting the Sabbath candles is one of the three so-called “women’s commandments” carried out by female Jews; it is the only one easily represented in visual terms. This essay describes the author’s field research, photographic, and writing project, “(Candlesticks) on Stone,” carried out mainly in 2009–2011, to explore the variety of ways candles and candlesticks are depicted on women’s gravestones in Eastern Europe. It also questions the transmission of the candle-lighting tradition fr

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Tomà, P. "The “candlestick sign” on cerebral ultrasound." Pediatric Radiology 21, no. 4 (1991): 319. http://dx.doi.org/10.1007/bf02018640.

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Wangchailert, Pempeeorn, and Worapat Paireekreng. "Enhancing FOREX Market Predictions: A Comparative Study of Candlestick Patterns and the MIDDAM Patterns." ECTI Transactions on Computer and Information Technology (ECTI-CIT) 19, no. 1 (2025): 121–34. https://doi.org/10.37936/ecti-cit.2025191.256994.

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Candlestick patterns are widely recognized as tools for predicting price movements, gaining popularity in the stock market. However, their applicability in the FOREX market, which operates continuously 24 hours daily, remains uncertain. This study assesses the accuracy of widely known candlestick patterns, particularly Doji patterns, in the FOREX market. We analyze the top eight most-traded currency pairsEUR/USD, EUR/GBP, GBP/USD, GBP/JPY, USD/JPY, USD/CHF, AUD/USD, and XAU/USDusing 13 years of data. The findings reveal that Doji patterns are unreliable indicators of reversals in the FOREX mar

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Tsao, Chung Chen, Kei Lin Kuo, I. Chien Hsu, and G. T. Chern. "Analysis of Core-Candlestick Drill in Drilling Composite Materials." Key Engineering Materials 419-420 (October 2009): 337–40. http://dx.doi.org/10.4028/www.scientific.net/kem.419-420.337.

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Unlike ductile metals cutting mechanism, the interfaces between fiber and matrix as a transitional layer experience mismatched deformation in machining process. In general, the most frequent operation performed on composite materials is drilling with a twist drill to generate a hole owing to their versatility and low production cost. However, delamination is one of the most common defects in drilling laminated fiber-reinforced composites and can cause a significant reduction in the load-carrying capacity of a structure. At the periphery, using such special drills as saw drill, candlestick dril

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Hassen, Oday A., Saad M. Darwish, Nur A. Abu, and Zaheera Z. Abidin. "Application of Cloud Model in Qualitative Forecasting for Stock Market Trends." Entropy 22, no. 9 (2020): 991. http://dx.doi.org/10.3390/e22090991.

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Forecasting stock prices plays an important role in setting a trading strategy or determining the appropriate timing for buying or selling a stock. The use of technical analysis for financial forecasting has been successfully employed by many researchers. The existing qualitative based methods developed based on fuzzy reasoning techniques cannot describe the data comprehensively, which has greatly limited the objectivity of fuzzy time series in uncertain data forecasting. Extended fuzzy sets (e.g., fuzzy probabilistic set) study the fuzziness of the membership grade to a concept. The cloud mod

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Brim, Andrew, and Nicholas S. Flann. "Deep reinforcement learning stock market trading, utilizing a CNN with candlestick images." PLOS ONE 17, no. 2 (2022): e0263181. http://dx.doi.org/10.1371/journal.pone.0263181.

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Billions of dollars are traded automatically in the stock market every day, including algorithms that use neural networks, but there are still questions regarding how neural networks trade. The black box nature of a neural network gives pause to entrusting it with valuable trading funds. A more recent technique for the study of neural networks, feature map visualizations, yields insight into how a neural network generates an output. Utilizing a Convolutional Neural Network (CNN) with candlestick images as input and feature map visualizations gives a unique opportunity to determine what in the

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Vaughan, Laura. "Butcher, baker, candlestick-maker and… healthcare centre?" Journal of Urban Design 27, no. 1 (2022): 69–72. http://dx.doi.org/10.1080/13574809.2022.1994772.

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Gdakowicz, Anna. "Japanese candlestick charting residential real estate market." Zeszyty Naukowe Uniwersytetu Szczecińskiego Finanse, Rynki Finansowe, Ubezpieczenia 2015, no. 75 (2015): 149–58. http://dx.doi.org/10.18276/frfu.2015.75-12.

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