Stock price prediction using machine learning and LSTM-based deep learning models

S Mehtab, J Sen, A Dutta - … , SoMMA 2020, Chennai, India, October 14–17 …, 2021 - Springer
Prediction of stock prices has been an important area of research for a long time. While
supporters of the efficient market hypothesis believe that it is impossible to predict stock …

Stock price prediction using CNN and LSTM-based deep learning models

S Mehtab, J Sen - … Conference on Decision Aid Sciences and …, 2020 - ieeexplore.ieee.org
Designing robust and accurate predictive models for stock price prediction has been an
active area of research over a long time. While on one side, the supporters of the efficient …

Stock price prediction using convolutional neural networks on a multivariate timeseries

S Mehtab, J Sen - arXiv preprint arXiv:2001.09769, 2020 - arxiv.org
Prediction of future movement of stock prices has been a subject matter of many research
work. In this work, we propose a hybrid approach for stock price prediction using machine …

A time series analysis-based stock price prediction using machine learning and deep learning models

S Mehtab, J Sen - International Journal of Business …, 2020 - inderscienceonline.com
Prediction of future movement of stock prices has always been a challenging task for
researchers. While the advocates of the efficient market hypothesis (EMH) believe that it is …

Analysis and forecasting of financial time series using CNN and LSTM-based deep learning models

S Mehtab, J Sen - Advances in Distributed Computing and Machine …, 2022 - Springer
Designing predictive models for forecasting future stock price has always been a very
popular area of research. On the one hand, the proponents of the famous efficient market …

Robust analysis of stock price time series using CNN and LSTM-based deep learning models

S Mehtab, J Sen, S Dasgupta - 2020 4th International …, 2020 - ieeexplore.ieee.org
Prediction of stock price and stock price movement patterns has always been a crucial task
for researchers. While the well-known efficient market hypothesis rules out any possibility of …

[PDF][PDF] Fitting multi-layer feed forward neural network and autoregressive integrated moving average for Dhaka Stock Exchange price predicting

MA Rubi, S Chowdhury, AAA Rahman… - Emerging Science …, 2022 - researchgate.net
The stock market plays a vital role in the economic development of any country. Stock
market performance can be measured by the market capitalization ratio as well as many …

Long‐and‐Short‐Term Memory (LSTM) NetworksArchitectures and Applications in Stock Price Prediction

J Sen, S Mehtab - Emerging Computing Paradigms: Principles …, 2022 - Wiley Online Library
Although recurrent neural networks (RNNs) are effective in handling sequential data, they
are poor in capturing the long‐term dependencies in the data due to a problem known as …

Introductory chapter: machine learning in finance-emerging trends and challenges

J Sen, R Sen, A Dutta - Algorithms, Models and Applications, 2022 - books.google.com
The paradigm of machine learning and artificial intelligence has pervaded our everyday life
in such a way that it is no longer an area for esoteric academics and scientists putting their …

Algorithmic trading and short-term forecast for financial time series with machine learning models; state of the art and perspectives

D Joiner, A Vezeau, A Wong, G Hains… - … on Recent Advances …, 2022 - ieeexplore.ieee.org
Stock price prediction with machine learning is an oft-studied area where numerous
unsolved problems still abound owing to the high complexity and volatility that technical …