My Account | Careers | Downloads | Blog

PROJECT TITLE :

Sparse Coding-Inspired Optimal Trading System for HFT Industry

ABSTRACT:

The monetary trade has witnessed an exceptionally fast progress of incorporating info processing techniques in designing knowledge-primarily based automated systems for high-frequency trading (HFT). This paper proposes a sparse coding-impressed optimal trading (SCOT) system for real-time high-frequency monetary signal representation and trading. Mathematically, SCOT simultaneously learns the dictionary, sparse features, and the trading strategy in a very joint optimization, yielding optimal feature representations for the specific trading objective. The learning method is modeled as a bilevel optimization and solved by the online gradient descend methodology with quick convergence. During this dynamic context, the system is tested on the $64000 money market to trade the index futures in the Shanghai exchange center.


Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : Flipping Free Conditions and Their Application in Sparse Network Localization ABSTRACT: An essential challenge involves determining the topology of a network based on the distances between its nodes. When there
PROJECT TITLE : Foresee Urban Sparse Traffic Accidents: A Spatiotemporal Multi-Granularity Perspective ABSTRACT: Due to the rapid pace of urbanization, car accidents have evolved into a significant threat to both health and development.
PROJECT TITLE : GraphSAGE-Based Traffic Speed Forecasting for Segment Network With Sparse Data ABSTRACT: The ability to accurately anticipate the flow of traffic is an essential component of intelligent traffic management systems.
PROJECT TITLE : Robust Rank-Constrained Sparse Learning: A Graph-Based Framework for Single View and Multiview Clustering ABSTRACT: Graph-based clustering is an approach that seeks to partition data in accordance with a similarity
PROJECT TITLE : Regularization on Augmented Data to Diversify Sparse Representation for Robust Image Classification ABSTRACT: The process of image classification is an essential part of today's computer vision systems. Due to

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry