ItemConference Paper

Dynamic Financial Portfolio Optimization Using Temporal Convolutional Networks and Real-Time Data Analysis

Title
Dynamic Financial Portfolio Optimization Using Temporal Convolutional Networks and Real-Time Data Analysis
Creator
Abhijith, E.; Ramasamy, Gobi; Saravanan, K.N.
Description
This paper presents an integrated framework for AI-driven portfolio optimization combining temporal convolutional networks (TCNs) with conditional value-at-risk (CVaR) minimization. Our system processes real-time market data through an automated pipeline implementing volatility-adjusted feature engineering and walk-forward validation. The architecture employs dilated causal convolutions for temporal pattern extraction combined with Ledoit-Wolf shrinkage covariance estimation for robust portfolio optimization. Experimental results demonstrate an 18.7% annualized return with 22.3% volatility, outperforming traditional mean-variance optimization by 14.2% in risk-adjusted returns. The implementation addresses key challenges in numerical stability and computational efficiency through eigenvalue clamping and gradient checkpointing. 2025 IEEE.
Source
Proceedings of 2025 International Conference on Emerging Technologies in Computing and Communication, ETCC 2025;
Date
01-01-2025
Publisher
Institute of Electrical and Electronics Engineers Inc.
Subject
algorithmic trading; Portfolio optimization; real-time data analysis; risk management; temporal convolutional networks
Coverage
Abhijith E., Department of Computer Science, Christ University, Bangalore, India; Ramasamy G., Department of Computer Science, Christ University, Bangalore, India; Saravanan K.N., Department of Computer Science, Christ University, Bangalore, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISBN: 979-833152476-0;
Format
online
Language
English
Type
Conference paper

Citation

Abhijith, E.; Ramasamy, Gobi; Saravanan, K.N., “Dynamic Financial Portfolio Optimization Using Temporal Convolutional Networks and Real-Time Data Analysis,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 19, 2026, https://archives.christuniversity.in/items/show/25829.

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