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20192022
most citedRobust Analysis of Stock Price Time Series Using CNN and LSTM-Based Deep Learning Models

70 citations · 172 across the 9 of their papers we have counts for

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Showing 2021Show all

8 papers · 1 filter

cs.LG2021★ 1 cited

Analysis of Sectoral Profitability of the Indian Stock Market Using an LSTM Regression Model

Jaydip Sen, Saikat Mondal, Sidra Mehtab

Predictive model design for accurately predicting future stock prices has always been considered an interesting and challenging research problem. The task becomes complex due to th…

q-fin.PM2021

Stock Portfolio Optimization Using a Deep Learning LSTM Model

Jaydip Sen, Abhishek Dutta, Sidra Mehtab

Predicting future stock prices and their movement patterns is a complex problem. Hence, building a portfolio of capital assets using the predicted prices to achieve the optimizatio…

q-fin.PM2021★ 2 cited

Optimum Risk Portfolio and Eigen Portfolio: A Comparative Analysis Using Selected Stocks from the Indian Stock Market

Jaydip Sen, Sidra Mehtab

Designing an optimum portfolio that allocates weights to its constituent stocks in a way that achieves the best trade-off between the return and the risk is a challenging research…

q-fin.ST2021★ 17 cited

Design and Analysis of Robust Deep Learning Models for Stock Price Prediction

Jaydip Sen, Sidra Mehtab

Building predictive models for robust and accurate prediction of stock prices and stock price movement is a challenging research problem to solve. The well-known efficient market h…

q-fin.CP2021★ 3 cited

Volatility Modeling of Stocks from Selected Sectors of the Indian Economy Using GARCH

Jaydip Sen, Sidra Mehtab, Abhishek Dutta

Volatility clustering is an important characteristic that has a significant effect on the behavior of stock markets. However, designing robust models for accurate prediction of fut…

q-fin.ST2021

Profitability Analysis in Stock Investment Using an LSTM-Based Deep Learning Model

Jaydip Sen, Abhishek Dutta, Sidra Mehtab

Designing robust systems for precise prediction of future prices of stocks has always been considered a very challenging research problem. Even more challenging is to build a syste…