Technical Analysis Indicators in Stock Market Using Machine Learning: A Comparative Analysis

التفاصيل البيبلوغرافية
العنوان: Technical Analysis Indicators in Stock Market Using Machine Learning: A Comparative Analysis
المؤلفون: Yash K. Pardeshi, Preeti Kale
المصدر: ICCCNT
بيانات النشر: IEEE, 2021.
سنة النشر: 2021
مصطلحات موضوعية: Naive Bayes classifier, Profit (accounting), Moving average, Computer science, Technical analysis, Econometrics, Decision tree, Stock market, MACD, Random forest
الوصف: Stock price forecasting is a very interesting topic in financial studies. Technical analysis indicators are mathematical models/calculations that help us predict stock price direction. The share market is not an ideal place for prediction as the share market is very volatile and share prices keep on fluctuating based on multiple factors. According to business reports, more than 90-95% of traders lose their money in the share market. The main objective of this work is to apply understanding of technical analysis indicators like RSI, exponential moving averages, Heiken Ashi candlesticks, price-volume analysis, MACD, decision tree, random forest analysis, Naive Bayes classifier, neural network and KNN. The work in this research paper compares and analyses short-term profit considering 5-year data (2015-2019) for high-traded stocks based on accuracy.
تدمد: 2015-2019
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::2791bd5821312359341e41ea7131afc4
https://doi.org/10.1109/icccnt51525.2021.9580172
حقوق: CLOSED
رقم الأكسشن: edsair.doi...........2791bd5821312359341e41ea7131afc4
قاعدة البيانات: OpenAIRE