no code implementations • 9 Apr 2024 • Anamitra Maiti, Subham Laha, Rishav Upadhaya, Soumyajit Biswas, Vikas Chaudhary, Biplab Kar, Nikhil Kumar, Jaydip Sen
In today's digital age, the internet is essential for communication and the sharing of information, creating a critical need for sophisticated data security measures to prevent unauthorized access and exploitation.
no code implementations • 8 Apr 2024 • Roopkatha Dey, Aivy Debnath, Sayak Kumar Dutta, Kaustav Ghosh, Arijit Mitra, Arghya Roy Chowdhury, Jaydip Sen
In various real-world applications such as machine translation, sentiment analysis, and question answering, a pivotal role is played by NLP models, facilitating efficient communication and decision-making processes in domains ranging from healthcare to finance.
no code implementations • 5 Apr 2024 • Trilokesh Ranjan Sarkar, Nilanjan Das, Pralay Sankar Maitra, Bijoy Some, Ritwik Saha, Orijita Adhikary, Bishal Bose, Jaydip Sen
Furthermore, the study proposes the robustness of defensive distillation as a defense mechanism to counter FGSM and CW attacks.
no code implementations • 2 Apr 2024 • Rohit Pandey, Hetvi Waghela, Sneha Rakshit, Aparna Rangari, Anjali Singh, Rahul Kumar, Ratnadeep Ghosal, Jaydip Sen
This work delved into the realm of automatic text generation, exploring a variety of techniques ranging from traditional deterministic approaches to more modern stochastic methods.
no code implementations • 30 Mar 2024 • Jaydip Sen, Joceli Mayer, Subhasis Dasgupta, Subrata Nandi, Srinivasan Krishnaswamy, Pinaki Mitra, Mahendra Pratap Singh, Naga Prasanthi Kundeti, Chandra Sekhara Rao MVP, Sudha Sree Chekuri, Seshu Babu Pallapothu, Preethi Nanjundan, Jossy P. George, Abdelhadi El Allahi, Ilham Morino, Salma AIT Oussous, Siham Beloualid, Ahmed Tamtaoui, Abderrahim Bajit
In the era of generative artificial intelligence and the Internet of Things, while there is explosive growth in the volume of data and the associated need for processing, analysis, and storage, several new challenges are faced in identifying spurious and fake information and protecting the privacy of sensitive data.
no code implementations • 17 Mar 2024 • Hetvi Waghela, Sneha Rakshit, Jaydip Sen
This paper introduces a novel adversarial attack method targeting text classification models, termed the Modified Word Saliency-based Adversarial At-tack (MWSAA).
no code implementations • 28 Dec 2023 • Jaydip Sen, Abhiraj Sen, Ananda Chatterjee
The notion of adversarial attacks on image classification models based on convolutional neural networks (CNN) is introduced in this work.
no code implementations • 23 Oct 2023 • Jaydip Sen, Arup Dasgupta, Partha Pratim Sengupta, Sayantani Roy Choudhury
The top stocks of each cluster are identified based on their free-float market capitalization from the report of the NSE published on July 1, 2022 (NSE Website).
no code implementations • 15 Oct 2023 • Jaydip Sen, Arup Dasgupta, Subhasis Dasgupta, Sayantani Roychoudhury
The portfolios are designed based on the training data from January 4, 2021 to June 30, 2022.
no code implementations • 24 Sep 2023 • Abhiraj Sen, Jaydip Sen
Three portfolios are designed following the above approaches choosing the top ten stocks from each sector based on their free-float market capitalization.
no code implementations • 11 Jul 2023 • Jaydip Sen, Subhasis Dasgupta
These three approaches to portfolio design are applied to the historical prices of stocks chosen from ten thematic sectors listed on the National Stock Exchange (NSE) of India.
no code implementations • 5 Jul 2023 • Jaydip Sen, Subhasis Dasgupta
However, very powerful and pre-trained CNN models working very accurately on image datasets for image classification tasks may perform disastrously when the networks are under adversarial attacks.
no code implementations • 27 May 2023 • Jaydip Sen, Aditya Jaiswal, Anshuman Pathak, Atish Kumar Majee, Kushagra Kumar, Manas Kumar Sarkar, Soubhik Maji
Three approaches of portfolio optimization that are considered in this work are the mean-variance portfolio (MVP), hierarchical risk parity (HRP) portfolio, and reinforcement learning-based portfolio.
no code implementations • 1 Apr 2023 • Jaydip Sen, Subhasis Dasgupta
Recent developments in hardware and information technology have enabled the emergence of billions of connected, intelligent devices around the world exchanging information with minimal human involvement.
no code implementations • 20 Dec 2022 • Subhasis Dasgupta, Jaydip Sen
Opinion mining is the branch of computation that deals with opinions, appraisals, attitudes, and emotions of people and their different aspects.
no code implementations • 14 Nov 2022 • Jaydip Sen
This paper presents a cointegration-based approach that identifies stocks listed in the five sectors of the National Stock Exchange (NSE) of India for designing efficient pair-trading portfolios.
no code implementations • 8 Oct 2022 • Jaydip Sen, Abhishek Dutta
The evaluation of the portfolios is done based on their cumulative returns over the test period from Jan 1, 2021, to Dec 31, 2021.
no code implementations • 5 Oct 2022 • Ananda Chatterjee, Hrisav Bhowmick, Jaydip Sen
It has been observed the LSTM performed better in predicting volatility in pharma over banking and IT sectors.
no code implementations • 3 Oct 2022 • Jaydip Sen, Abhishek Dutta
The portfolios are built following the two approaches to historical stock prices from Jan 1, 2016, to Dec 31, 2020.
no code implementations • 1 Jul 2022 • Jaydip Sen, Arpit Awad, Aaditya Raj, Gourav Ray, Pusparna Chakraborty, Sanket Das, Subhasmita Mishra
We have built a minimum variance portfolio and optimal risk portfolio for all the six chosen sectors by using the daily stock prices over the past five years as training data and have also conducted back testing to check the performance of the portfolio.
no code implementations • 2 Mar 2022 • Jaydip Sen, Saikat Mondal, Gourab Nath
Six months after the construction of the portfolios, i. e., on Jul 1, 2021, the actual returns and the LSTM-predicted returns for the portfolios are computed.
no code implementations • 2 Mar 2022 • Jaydip Sen, Sidra Mehtab, Abhishek Dutta, Saikat Mondal
Optimum portfolios are designed on the selected seven sectors.
no code implementations • 6 Feb 2022 • Jaydip Sen, Saikat Mondal, Sidra Mehtab
Optimum risk and eigen portfolios for each sector are designed based on ten critical stocks from the sector.
no code implementations • 6 Feb 2022 • Jaydip Sen, Sidra Mehtab, Abhishek Dutta, Saikat Mondal
Portfolio design and optimization have been always an area of research that has attracted a lot of attention from researchers from the finance domain.
no code implementations • 14 Jan 2022 • Jaydip Sen, Ashwin Kumar R S, Geetha Joseph, Kaushik Muthukrishnan, Koushik Tulasi, Praveen Varukolu
In this project, we have built an efficient portfolio and to predict the future asset value by means of individual stock price prediction of the stocks in the portfolio.
no code implementations • 6 Jan 2022 • Jaydip Sen, Sidra Mehtab, Rajdeep Sen, Abhishek Dutta, Pooja Kherwa, Saheel Ahmed, Pranay Berry, Sahil Khurana, Sonali Singh, David W. W Cadotte, David W. Anderson, Kalum J. Ost, Racheal S. Akinbo, Oladunni A. Daramola, Bongs Lainjo
The chapters in the book illustrate how machine learning and deep learning algorithms and models are designed, optimized, and deployed.
no code implementations • 23 Dec 2021 • Hrisav Bhowmick, Ananda Chatterjee, Jaydip Sen
A recommender system, also known as a recommendation system, is a type of information filtering system that attempts to forecast a user's rating or preference for an item.
no code implementations • 9 Nov 2021 • Jaydip Sen, Saikat Mondal, Sidra Mehtab
This paper presents an optimized predictive model built on long-and-short-term memory (LSTM) architecture for automatically extracting past stock prices from the web over a specified time interval and predicting their future prices for a specified forecast horizon, and forecasts the future stock prices.
no code implementations • 8 Nov 2021 • Jaydip Sen, Abhishek Dutta, Sidra Mehtab
The predicted and the actual returns of each portfolio are found to be high, indicating the high precision of the LSTM model.
no code implementations • 1 Nov 2021 • Ananda Chatterjee, Hrisav Bhowmick, Jaydip Sen
This paper demonstrates a set of time series, econometric, and various learning-based models for stock price prediction.
no code implementations • 8 Oct 2021 • Jaydip Sen, Rajdeep Sen, Abhishek Dutta
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 effort to solve a challenging research problem.
no code implementations • 23 Jul 2021 • Jaydip Sen, Sidra Mehtab
Three portfolios are built for each of the seven sectors chosen for this study, and the portfolios are analyzed on the training data based on several metrics such as annualized return and risk, weights assigned to the constituent stocks, the correlation heatmaps, and the principal components of the Eigen portfolios.
no code implementations • 17 Jun 2021 • 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.
no code implementations • 28 May 2021 • Jaydip Sen, Sidra Mehtab, Abhishek Dutta
Volatility clustering is an important characteristic that has a significant effect on the behavior of stock markets.
no code implementations • 3 May 2021 • Gourab Nath, Jaydip Sen
The algorithm is based on the perspective that, since the grocery items are usually bought in bulk, a grocery recommender system should be capable of recommending the items in bulk.
no code implementations • 6 Apr 2021 • Jaydip Sen, Abhishek Dutta, Sidra Mehtab
Even more challenging is to build a system for constructing an optimum portfolio of stocks based on the forecasted future stock prices.
no code implementations • 28 Mar 2021 • Jaydip Sen, Sidra Mehtab
Designing robust frameworks for precise prediction of future prices of stocks has always been considered a very challenging research problem.
no code implementations • 7 Nov 2020 • Sidra Mehtab, Jaydip Sen, Subhasis Dasgupta
Prediction of stock price and stock price movement patterns has always been a critical area of research.
no code implementations • 22 Oct 2020 • Sidra Mehtab, Jaydip Sen
In this approach, the open values of the NIFTY 50 index are predicted on a time horizon of one week, and once a week is over, the actual index values are included in the training set before the model is trained again, and the forecasts for the next week are made.
4 code implementations • 20 Sep 2020 • Sidra Mehtab, Jaydip Sen, Abhishek Dutta
In this work, we propose an approach of hybrid modeling for stock price prediction building different machine learning and deep learning-based models.
no code implementations • 10 Sep 2020 • Jaydip Sen, Sidra Mehtab
Machine learning and data mining algorithms play important roles in designing intrusion detection systems.
no code implementations • 17 Apr 2020 • Sidra Mehtab, Jaydip Sen
We contend that the agglomerative approach of model building that uses a combination of statistical, machine learning, and deep learning approaches, can very effectively learn from the volatile and random movement patterns in a stock price data.
no code implementations • 10 Jan 2020 • Sidra Mehtab, Jaydip Sen
Based on the NIFTY data during the said period, we build various predictive models using machine learning approaches, and then use those models to predict the Close value of NIFTY 50 for the year 2019, with a forecast horizon of one week.
1 code implementation • 9 Dec 2019 • Sidra Mehtab, Jaydip Sen
Based on the data of 2015 to 2017, we build various predictive models using machine learning, and then use those models to predict the closing value of NIFTY 50 for the period January 2018 till June 2019 with a prediction horizon of one week.