Institution · Praxis Business School
Most cited papers from Praxis Business School
What are the most cited papers from Praxis Business School?
The most cited paper from Praxis Business School is "Stock Price Prediction Using Machine Learning and LSTM-Based Deep Learning Models" (Sidra Mehtab, Jaydip Sen, Abhishek Dutta, 2021), with 177 citations. Next come "Robust Analysis of Stock Price Time Series Using CNN and LSTM-Based Deep Learning Models" (70) and "Stock Price Prediction Using Convolutional Neural Networks on a Multivariate Time Series" (60).
Showing 50 of 57 papers. Every paper with more than 4 citations is listed.
| # | Paper | ||
|---|---|---|---|
| 1 | Stock Price Prediction Using Machine Learning and LSTM-Based Deep Learning Models Sidra Mehtab, Jaydip Sen, Abhishek Dutta · Communications in computer and information science | 2021 | 177 |
| 2 | Robust Analysis of Stock Price Time Series Using CNN and LSTM-Based Deep Learning Models Sidra Mehtab, Jaydip Sen, Subhasis Dasgupta · 2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA) | 5 Nov 2020 | 70 |
| 3 | Stock Price Prediction Using Convolutional Neural Networks on a Multivariate Time Series Sidra Mehtab, Jaydip Sen | 2 Aug 2021 | 60 |
| 4 | Stock Price Prediction Using Time Series, Econometric, Machine Learning, and Deep Learning Models Ananda Chatterjee, Hrisav Bhowmick, Jaydip Sen · 2021 IEEE Mysore Sub Section International Conference (MysuruCon) | 24 Oct 2021 | 59 |
| 5 | Stock Price Prediction Using Machine Learning and LSTM-Based Deep Learning Models Jaydip Sen, Sidra Mehtab, Abhishek Dutta | 5 Aug 2021 | 56 |
| 6 | A Proposed Architecture for Big Data Driven Supply Chain Analytics Sanjib Kumar Biswas, Jaydip Sen · SSRN Electronic Journal | 2016 | 46 |
| 7 | Stock Portfolio Optimization Using a Deep Learning LSTM Model Jaydip Sen, Abhishek Dutta, Sidra Mehtab · 2021 IEEE Mysore Sub Section International Conference (MysuruCon) | 24 Oct 2021 | 43 |
| 8 | Accurate Stock Price Forecasting Using Robust and Optimized Deep Learning Models Jaydip Sen, Sidra Mehtab · 2021 International Conference on Intelligent Technologies (CONIT) | 25 Jun 2021 | 43 |
| 9 | Decomposition of Time Series Data of Stock Markets and its Implications for Prediction – An Application for the Indian Auto Sector Jaydip Sen, Tamal Datta Chaudhuri · RePEc: Research Papers in Economics | 2016 | 34 |
| 10 | Volatility Modeling of Stocks from Selected Sectors of the Indian Economy Using GARCH Jaydip Sen, Sidra Mehtab, Abhishek Dutta · arXiv (Cornell University) | 28 May 2021 | 30 |
| 11 | Introductory Chapter: Machine Learning in Finance-Emerging Trends and Challenges Jaydip Sen, Rajdeep Sen, Abhishek Dutta · Artificial intelligence | 22 Dec 2021 | 29 |
| 12 | A Predictive Analysis of the Indian FMCG Sector using Time Series Decomposition - Based Approach Jaydip Sen, Tamal Datta Chaudhuri · RePEc: Research Papers in Economics | 13 Jul 2017 | 27 |
| 13 | Robust Image Classification: Defensive Strategies against FGSM and PGD Adversarial Attacks Hetvi Waghela, Jaydip Sen, Sneha Rakshit | 6 Sep 2024 | 26 |
| 14 | Board characteristics and demand for audit quality: a meta-analysis Deepali Kalia, Debarati Basu, Sayantan Kundu · Asian Review of Accounting | 23 Sep 2022 | 25 |
| 15 | Understanding the sectors of Indian economy for portfolio choice Jaydip Sen, Tamal Datta Chaudhuri · International Journal of Business Forecasting and Marketing Intelligence | 2018 | 23 |
| 16 | Precise Stock Price Prediction for Optimized Portfolio Design Using an LSTM Model Jaydip Sen, Sidra Mehtab, Abhishek Dutta et al. | Dec 2021 | 21 |
| 17 | India’s Rural Employment Guarantee Scheme – How does it influence seasonal rural out-migration decisions? Amarendu Nandy, Chhavi Tiwari, Sayantan Kundu · Journal of Policy Modeling | 6 Oct 2021 | 21 |
| 18 | A Robust Predictive Model for Stock Price Forecasting Jaydip Sen, Tamal Datta Chaudhuri | 12 Oct 2021 | 20 |
| 19 | Do Environmental, Social, and Governance (ESG) practices help mitigate bank default risk? Abhijit Biswas, Arindam Kumar Das, Aviral Kumar Tiwari et al. · Journal of Environmental Management | 12 Mar 2025 | 19 |
| 20 | Hierarchical Risk Parity and Minimum Variance Portfolio Design on NIFTY 50 Stocks Jaydip Sen, Sidra Mehtab, Abhishek Dutta et al. · 2021 International Conference on Decision Aid Sciences and Application (DASA) | 7 Dec 2021 | 19 |
| 21 | Adversarial Attacks on Image Classification Models: FGSM and Patch Attacks and Their Impact Jaydip Sen, Subhasis Dasgupta · IntechOpen eBooks | 14 Aug 2023 | 18 |
| 22 | A Proposed Framework of Next Generation Supply Chain Management Using Big Data Analytics Sanjib Kumar Biswas, Jaydip Sen | 2016 | 18 |
| 23 | A Comparative Study of Hierarchical Risk Parity Portfolio and Eigen Portfolio on the NIFTY 50 Stocks Jaydip Sen, Abhishek Dutta · Lecture notes on data engineering and communications technologies | Sep 2022 | 17 |
| 24 | Design and Analysis of Optimized Portfolios for Selected Sectors of the Indian Stock Market Jaydip Sen, Abhishek Dutta · 2022 International Conference on Decision Aid Sciences and Applications (DASA) | 23 Mar 2022 | 17 |
| 25 | Design and Analysis of Robust Deep Learning Models for Stock Price Prediction Jaydip Sen, Sidra Mehtab · Artificial intelligence | 28 Sep 2021 | 17 |
| 26 | Analysis and Forecasting of Financial Time Series Using CNN and LSTM-Based Deep Learning Models Sidra Mehtab, Jaydip Sen · Lecture notes in networks and systems | 2022 | 17 |
| 27 | An Investigation of the Structural Characteristics of the Indian IT Sector and the Capital Goods Sector -- An Application of the R Programming in Time Series Decomposition and Forecasting Jaydip Sen, Tamal Datta Chaudhuri | 27 Sep 2021 | 17 |
| 28 | Portfolio Optimization Using Reinforcement Learning and Hierarchical Risk Parity Approach Jaydip Sen · Studies in big data | 2023 | 16 |
| 29 | Portfolio Optimization on NIFTY Thematic Sector Stocks Using an LSTM Model Jaydip Sen, Saikat Mondal, Sidra Mehtab · 2021 International Conference on Data Analytics for Business and Industry (ICDABI) | 25 Oct 2021 | 16 |
| 30 | A Robust Predictive Model for Stock Price Prediction Using Deep Learning and Natural Language Processing Jaydip Sen, Sidra Mehtab | 25 Jul 2021 | 16 |
| 31 | A Time Series Analysis - Based Forecasting Approach for the Indian Realty Sector Jaydip Sen | 27 Sep 2021 | 14 |
| 32 | Profitability Analysis in Stock Investment Using an LSTM-Based Deep Learning Model Jaydip Sen, Abhishek Dutta, Sidra Mehtab · 2021 2nd International Conference for Emerging Technology (INCET) | 21 May 2021 | 14 |
| 33 | Stock Price Prediction Using CNN and LSTM-Based Deep Learning Models Sidra Mehtab, Jaydip Sen · 2020 International Conference on Decision Aid Sciences and Application (DASA) | 8 Nov 2020 | 13 |
| 34 | A comparative study of optimum risk portfolio and eigen portfolio on the Indian stock market Jaydip Sen, Sidra Mehtab · International Journal of Business Forecasting and Marketing Intelligence | 2021 | 12 |
| 35 | Robust Portfolio Design and Stock Price Prediction Using an Optimized LSTM Model Jaydip Sen, Saikat Mondal, Gourab Nath · 2021 IEEE 18th India Council International Conference (INDICON) | 19 Dec 2021 | 12 |
| 36 | Designing Efficient Pair-Trading Strategies Using Cointegration for the Indian Stock Market Jaydip Sen · 2022 2nd Asian Conference on Innovation in Technology (ASIANCON) | 26 Aug 2022 | 11 |
| 37 | A Study of the Indian Metal Sector Using Time Series Decomposition-Based Approach Jaydip Sen · SSRN Electronic Journal | 2 Sep 2017 | 11 |
| 38 | Stock composition of mutual funds and fund style: a time series decomposition approach towards testing for consistency Jaydip Sen · International Journal of Business Forecasting and Marketing Intelligence | 2018 | 11 |
| 39 | A time series analysis-based stock price prediction using machine learning and deep learning models Sidra Mehtab, Jaydip Sen · International Journal of Business Forecasting and Marketing Intelligence | 2020 | 11 |
| 40 | Stock Price Prediction Using Deep Learning Models Jaydip Sen, Sidra Mehtab, Gourab Nath | 27 Sep 2021 | 10 |
| 41 | A Framework of Customer Review Analysis Using the Aspect-Based Opinion Mining Approach Subhasis Dasgupta, Jaydip Sen | Dec 2022 | 9 |
| 42 | Stock Volatility Prediction using Time Series and Deep Learning Approach Ananda Chatterjee, Hrisav Bhowmick, Jaydip Sen · 2022 IEEE 2nd Mysore Sub Section International Conference (MysuruCon) | 16 Oct 2022 | 9 |
| 43 | A Robust Analysis and Forecasting Framework for the Indian Mid Cap Sector Using Times Series Decomposition Approach Jaydip Sen | 13 Aug 2021 | 9 |
| 44 | Analyzing Consumer Reviews with Text Mining Approach Subhasis Dasgupta, Kalyan Sengupta · Paradigm A Management Research Journal | 3 May 2016 | 9 |
| 45 | Introductory Chapter: Data Privacy Preservation on the Internet of Things Jaydip Sen, Subhasis Dasgupta · IntechOpen eBooks | 27 Sep 2023 | 7 |
| 46 | A Framework for Predictive Analysis of Stock Market Indices – A Study of the Indian Auto Sector Jaydip Sen, Tamal Datta Chaudhuri · RePEc: Research Papers in Economics | 2015 | 7 |
| 47 | Portfolio Optimization: A Comparative Study Jaydip Sen, Subhasis Dasgupta · Artificial intelligence | 22 Nov 2023 | 6 |
| 48 | A Survey of Cryptography and Key Management Schemes for Wireless Sensor Networks Jaydip Sen · IntechOpen eBooks | 19 Jul 2023 | 6 |
| 49 | Optimum Pair-Trading Strategies for Stocks Using Cointegration-Based Approach Jaydip Sen | Dec 2022 | 6 |
| 50 | A Forecasting Framework for the Indian Healthcare Sector Index Jaydip Sen N.A. · International Journal of Business Forecasting and Marketing Intelligence | 2022 | 6 |
Citations are OpenAlex's own counts, from its 2026-09-23 snapshot, so the ranking can differ from Google Scholar or Web of Science. A paper is listed for an institution when any of its authors gave it as an affiliation; retracted papers and papers whose citation count cannot be traced to citing works are left out, and a preprint and the article it became are shown once. Release dates are OpenAlex's: where a source gave only a month or a year, that is what is shown. How the lists are chosen.