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Found 15 papers, 2 papers with code
Design and Analysis of Optimized Portfolios for Selected Sectors of the Indian Stock Market
The evaluation of the portfolios is done based on their cumulative returns over the test period from Jan 1, 2021, to Dec 31, 2021.
A Comparative Study of Hierarchical Risk Parity Portfolio and Eigen Portfolio on the NIFTY 50 Stocks
The portfolios are built following the two approaches to historical stock prices from Jan 1, 2016, to Dec 31, 2020.
Precise Stock Price Prediction for Optimized Portfolio Design Using an LSTM Model
Optimum portfolios are designed on the selected seven sectors.
Hierarchical Risk Parity and Minimum Variance Portfolio Design on NIFTY 50 Stocks
Portfolio design and optimization have been always an area of research that has attracted a lot of attention from researchers from the finance domain.
Machine Learning: Algorithms, Models, and Applications
The chapters in the book illustrate how machine learning and deep learning algorithms and models are designed, optimized, and deployed.
Stock Portfolio Optimization Using a Deep Learning LSTM Model
The predicted and the actual returns of each portfolio are found to be high, indicating the high precision of the LSTM model.
Machine Learning in Finance-Emerging Trends and Challenges
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.
Volatility Modeling of Stocks from Selected Sectors of the Indian Economy Using GARCH
Volatility clustering is an important characteristic that has a significant effect on the behavior of stock markets.
Profitability Analysis in Stock Investment Using an LSTM-Based Deep Learning Model
Even more challenging is to build a system for constructing an optimum portfolio of stocks based on the forecasted future stock prices.
Stock Price Prediction Using Machine Learning and LSTM-Based Deep Learning Models
In this work, we propose an approach of hybrid modeling for stock price prediction building different machine learning and deep learning-based models.
The VIA Annotation Software for Images, Audio and Video
In this paper, we introduce a simple and standalone manual annotation tool for images, audio and video: the VGG Image Annotator (VIA).
Ear-to-ear Capture of Facial Intrinsics
We present a practical approach to capturing ear-to-ear face models comprising both 3D meshes and intrinsic textures (i. e. diffuse and specular albedo).
Predicting Performance of a Face Recognition System Based on Image Quality
A practical limitation of such a data driven generative model is the limited nature of training data set.
Predicting Face Recognition Performance Using Image Quality
This paper proposes a data driven model to predict the performance of a face recognition system based on image quality features.
Can Facial Uniqueness be Inferred from Impostor Scores?
In Biometrics, facial uniqueness is commonly inferred from impostor similarity scores.
