A novel technical analysis-based method for stock market forecasting

Chen, Yuh Jen; Chen, Yuh Min; Tsao, Shiang Ting; Hsieh, Shu Fan

doi:10.1007/s00500-016-2417-2

Cited by 19 publications

(8 citation statements)

References 19 publications

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“…Chen et al [33] developed a new technical analysis method that helps investors improve their quality and profitability decision-making. This methodology includes:…”

Section: Literature Reviewmentioning

confidence: 99%

Stock Prediction Based on Technical Indicators Using Deep Learning Model

Agrawal¹,

Shukla²,

Nair³

et al. 2022

Computers, Materials &Amp; Continua

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Stock market trends forecast is one of the most current topics and a significant research challenge due to its dynamic and unstable nature. The stock data is usually non-stationary, and attributes are non-correlative to each other. Several traditional Stock Technical Indicators (STIs) may incorrectly predict the stock market trends. To study the stock market characteristics using STIs and make efficient trading decisions, a robust model is built. This paper aims to build up an Evolutionary Deep Learning Model (EDLM) to identify stock trends' prices by using STIs. The proposed model has implemented the Deep Learning (DL) model to establish the concept of Correlation-Tensor. The analysis of the dataset of three most popular banking organizations obtained from the live stock market based on the National Stock exchange (NSE) -India, a Long Short Term Memory (LSTM) is used. The datasets encompassed the trading days from the 17 th of Nov 2008 to the 15 th of Nov 2018. This work also conducted exhaustive experiments to study the correlation of various STIs with stock price trends. The model built with an EDLM has shown significant improvements over two benchmark ML models and a deep learning one. The proposed model aids investors in making profitable investment decisions as it presents trend-based forecasting and has achieved a prediction accuracy of 63.59%, 56.25%, and 57.95% on the datasets of HDFC, Yes Bank, and SBI, respectively. Results indicate that the proposed EDLA with a combination of STIs can often provide improved results than the other state-of-the-art algorithms.

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“…Chen et al [33] developed a new technical analysis method that helps investors improve their quality and profitability decision-making. This methodology includes:…”

Section: Literature Reviewmentioning

confidence: 99%

Stock Prediction Based on Technical Indicators Using Deep Learning Model

Agrawal¹,

Shukla²,

Nair³

et al. 2022

Computers, Materials &Amp; Continua

View full text Add to dashboard Cite

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“…(Sezer, Ozbayoglu, & Dogdu, 2017) Dalam mengembangkan teknik untuk prediksi pasar daftar efek syariah berbasis analisis teknis, maka teknik melibatkan klasifikasi saham berbasis tren, pemilihan indiaktor pasar saham adaptif, dan peramalan sinyal perdagangan pasar saham. (Chen, et al, 2018)…”

Section: Kondisi Inilah Yang Sering Menyebabkan False Signalunclassified

Apakah Memilih Saham Daftar Efek Syariah Indonesia Dengan Analisis Teknikal Akan Menguntungkan?

Basrowi¹,

Fauzi

Utami

2020

AJEI

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Tujuan penelitian adalah untuk mengetahui apakah saham daftar efek syariah Indonesia dengan menggunakan analisis teknikal akan memberikan keuntungan. Karena, kemungkinan besar bagi pemula akan kesulitan menggunakan analisis teknikal yang nampak seperti chart. Metode penelitian menggunakan studi literatur dengan pendekatan ekonomi syariah. Hasil studi menemukan bahwa ada strategi khusus yang digunakan untuk membaca pergerakan harga menggunakan analisis teknikal dan apabila tidak memahami dan memprediksi pergerakan harga dengan baik maka kerugian yang akan diperoleh. Analisis teknikal yang digunakan untuk mengetahui pergerakan harga dengan memberi sinyal waktu masuk dan keluar pasar saham pada emiten yang terdaftar di daftar efek syariah tidak banyak berbeda dengan umumnya yang digunakan pada pasar modal. Hanya saja larangan dan ketentuan baik produk, distribusi, dan operaionalnya yang harus sesuai dengan prinsip syariah dan teknik ini disarankan tidak digunakan untuk memperhitungkan keuntungan jangka panjang namun dalan jangka pendek dapat menghasilkan pengembalian yang positif pada investor.

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“…The maximum accuracy achieved is 57.2%. Chen et al [22] proposes a novel technical analysis method for forecasting of stock market to increase the decision support quality and profitability of investors. The techniques utilize trend based classification, indicator selection, and stock market trading signal forecasting.…”

Section: Related Workmentioning

confidence: 99%

Stock Price Prediction using Technical Indicators: A Predictive Model using Optimal Deep Learning

2019

ijrte

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The stock market is highly volatile and complex in nature. Technical analysts often apply Technical Analysis (TA) on historical price data, which is an exhaustive task and might produce incorrect predictions. The machine learning coupled with fundamental and / or Technical Analysis also yields satisfactory results for stock market prediction. In this work an effort is made to predict the price and price trend of stocks by applying optimal Long Short Term Memory (O-LSTM) deep learning and adaptive Stock Technical Indicators (STIs). We also evaluated the model for taking buy-sell decision at the end of day. To optimize the deep learning task we utilized the concept of Correlation-Tensor built with appropriate STIs. The tensor with adaptive indicators is passed to the model for better and accurate prediction. The results are analyzed using popular metrics and compared with two benchmark ML classifiers and a recent classifier based on deep learning. The mean prediction accuracy achieved using proposed model is 59.25%, over number of stocks,which is much higher than benchmark approaches.

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A novel technical analysis-based method for stock market forecasting

Cited by 19 publications

References 19 publications

Stock Prediction Based on Technical Indicators Using Deep Learning Model

Stock Prediction Based on Technical Indicators Using Deep Learning Model

Apakah Memilih Saham Daftar Efek Syariah Indonesia Dengan Analisis Teknikal Akan Menguntungkan?

Stock Price Prediction using Technical Indicators: A Predictive Model using Optimal Deep Learning

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