Financial Instrument Forecast with Artificial Intelligence
نویسندگان
چکیده
In ancient times, trade was carried out by barter. With the use of money and similar means, concept financial instruments emerged. Financial are tools documents used in economy. can be foreign exchange rates, securities, crypto currency, index funds. There many methods instrument forecast. These include technical analysis methods, basic forecasts using variables formulas, time-series algorithms artificial intelligence algorithms. Within scope this study, importance forecast is studied. Since as a means investment all sections society, namely individuals, families, institutions, states, it highly important to know about their future. bring profitability such increased income welfare, more economical adjustment maturities, creation large finances, minimization risks, spreading ownership grassroots, balanced distribution. applying new Long Short Term Memory (LSTM), Recurrent Neural Network (RNN), Convolutional (CNN), Autoregressive Integrated Moving Average (ARIMA) Ensemble Classification Boosting Method. creating network compromising LSTM RNN algorithm, an layer, output layer. ensemble classification boosting method, method that gives successful result compared other algorithm results applied. At conclusion alternative were competed against each gave most suggested. The success rate comparing with different time intervals training data sets. Furthermore, developed yielded than result.
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ژورنال
عنوان ژورنال: Emerging markets journal
سال: 2021
ISSN: ['2159-242X', '2158-8708']
DOI: https://doi.org/10.5195/emaj.2021.229