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Dynamic prediction of Indian stock market: an artificial neural network approach
16 references·1 citing·49 second hopsampled
Dynamic prediction of Indian stock market: an artificial neural network approach (2021)Dynamic prediction of Indian stock market…Stock Price Prediction Using Machine Learning and LSTM-Based Deep Learning Models (2021)Stock Price Prediction Using …Optimizing LSTM for time series prediction in Indian stock market (2020)Optimizing LSTM for time seri…Indian stock market prediction using artificial neural networks on tick data (2019)Indian stock market predictio…The relationship between oil prices, the stock market and the exchange rate: Evidence from Mexico (2018)The relationship between oil …NSE Stock Market Prediction Using Deep-Learning Models (2018)NSE Stock Market Prediction U…Macroeconomic indicators and their impact on stock markets in ASIAN 3: A pooled mean group approach (2018)Macroeconomic indicators and …The Impact of Macroeconomic Indicators on Indian Stock Prices: An Empirical Analysis (2017)The Impact of Macroeconomic I…A Hybrid Artificial Neural Network with Metaheuristic Algorithms for Predicting Stock Price (2017)A Hybrid Artificial Neural Ne…Study of Effectiveness of Time Series Modeling (Arima) in Forecasting Stock Prices (2014)Study of Effectiveness of Tim…Stock Price Prediction Using the ARIMA Model (2014)Stock Price Prediction Using …Prediction of Stock Performance in the Indian Stock Market Using Logistic Regression (2012)Prediction of Stock Performan…Integration of genetic fuzzy systems and artificial neural networks for stock price forecasting (2010)Integration of genetic fuzzy …Stock market prediction of S&P 500 via combination of improved BCO approach and BP neural network (2008)Stock market prediction of S&…Stock market prediction using artificial neural networks with optimal feature transformation (2004)Stock market prediction using…Time series forecasting using a hybrid ARIMA and neural network model (2003)Time series forecasting using…Application of neural networks to an emerging financial market: forecasting and trading the Taiwan Stock Index (2002)Application of neural network…A Hybrid Model to Predict Stock Closing Price Using Novel Features and a Fully Modified Hodrick–Prescott Filter (2022)A Hybrid Model to Predict Sto…A hybrid ARIMA and support vector machines model in stock price forecasting (2004)Forecasting stock market short-term trends using a neuro-fuzzy based methodology (2009)Stock index forecasting based on a hybrid model (2011)A Comparison of ARIMA and LSTM in Forecasting Time Series (2018)A systematic review of fundamental and technical analysis of stock market predictions (2019)The Performance of LSTM and BiLSTM in Forecasting Time Series (2019)Stock market forecasting using hidden Markov model: a new approach (2005)Surveying stock market forecasting techniques – Part II: Soft computing methods (2008)Predicting stock market index using fusion of machine learning techniques (2014)25years at Knowledge-Based Systems: A bibliometric analysis (2015)Stock price pattern recognition-a recurrent neural network approach (1990)Predicting stock price using fuzzy grey prediction system (2002)On the Modeling of Financial Time Series (2014)CNNpred: CNN-based stock market prediction using a diverse set of variables (2019)Book Review: Time Series Analysis: Forecasting and Control (1977)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Forecasting with artificial neural networks: (1998)A novel hybridization of artificial neural networks and ARIMA models for time series forecasting (2010)Recurrent Neural Networks for Time Series Forecasting: Current status and future directions (2020)Forecasting With Dynamic Regression Models. (1993)Model Based Inference in the Life Sciences: A Primer on Evidence (2007)Model Based Inference in the Life Sciences: A Primer on Evidence (2009)A comprehensive review on multiple hybrid deep learning approaches for stock prediction (2022)Novel optimization approach for stock price forecasting using multi-layered sequential LSTM (2022)Stock price prediction using LSTM, RNN and CNN-sliding window model (2017)Stock Market Analysis: A Review and Taxonomy of Prediction Techniques (2019)Stock price prediction using deep learning and frequency decomposition (2020)Generación de series de tiempo financieras sintéticas para "data augmentation" usando redes neuronales generativas adversarias (GAN) (2021)Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul Stock Exchange (2010)Using artificial neural network models in stock market index prediction (2011)A Bayesian regularized artificial neural network for stock market forecasting (2013)The applications of artificial neural networks, support vector machines, and long–short term memory for stock market prediction (2021)Machine learning techniques and data for stock market forecasting: A literature review (2022)Wholesale price forecasts of green grams using the neural network (2024)Financial time series forecasting using independent component analysis and support vector regression (2009)Deep learning with long short-term memory networks for financial market predictions (2017)A CNN-LSTM-Based Model to Forecast Stock Prices (2020)Predicting stock market index using LSTM (2022)The relationship between earnings' yield, market value and return for NYSE common stocks (1983)Persuasive evidence of market inefficiency (1985)Size and Book-to-Market Factors in Earnings and Returns (1995)A time series analysis-based stock price prediction using machine learning and deep learning models (2020)Stock Price Prediction Using CNN and LSTM-Based Deep Learning Models (2020)A Stock Price Prediction Method Based on BiLSTM and Improved Transformer (2023)Economic Forces and the Stock Market (1986)The Cross-Section of Expected Stock Returns (1992)Common risk factors in the returns on stocks and bonds (1993)Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques (2014)A deep learning framework for financial time series using stacked autoencoders and long-short term memory (2017)
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References

  • 2003Time series forecasting using a hybrid ARIMA and neural network model4,583 cited
  • 2014Stock Price Prediction Using the ARIMA Model1,169 cited
  • 2018NSE Stock Market Prediction Using Deep-Learning Models629 cited
  • 2002Application of neural networks to an emerging financial market: forecasting and trading the Taiwan Stock Index537 cited
  • 2008Stock market prediction of S&P 500 via combination of improved BCO approach and BP neural network435 cited
  • 2020Optimizing LSTM for time series prediction in Indian stock market396 cited
  • 2010Integration of genetic fuzzy systems and artificial neural networks for stock price forecasting381 cited
  • 2014Study of Effectiveness of Time Series Modeling (Arima) in Forecasting Stock Prices307 cited
  • 2019Indian stock market prediction using artificial neural networks on tick data271 cited
  • 2021Stock Price Prediction Using Machine Learning and LSTM-Based Deep Learning Models205 cited
  • 2018The relationship between oil prices, the stock market and the exchange rate: Evidence from Mexico174 cited
  • 2004Stock market prediction using artificial neural networks with optimal feature transformation115 cited
  • 2018Macroeconomic indicators and their impact on stock markets in ASIAN 3: A pooled mean group approach97 cited
  • 2012Prediction of Stock Performance in the Indian Stock Market Using Logistic Regression

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91 cited
  • 2017The Impact of Macroeconomic Indicators on Indian Stock Prices: An Empirical Analysis90 cited
  • 2017A Hybrid Artificial Neural Network with Metaheuristic Algorithms for Predicting Stock Price88 cited
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    • 2022A Hybrid Model to Predict Stock Closing Price Using Novel Features and a Fully Modified Hodrick–Prescott Filter27 cited