This paper presents a systematic exploration of deep reinforcement learning (RL) for
portfolio optimization and compares various agent architectures, such as the DQN, DDPG …

Portfolio Optimization (PO) is a financial problem aiming to maximize the net gains while
minimizing the risks in a given investment portfolio. The novelty of Quantum algorithms lies …

Nowadays, to maximize their income, investors and researchers try to predict the future
prices of stocks in the market using artificial intelligence algorithms. However, noise in stock …

In the dynamic landscape of the stock market, accredited investors in the US are required to
report quarterly holdings in their portfolios to the Securities and Exchange Commission …

This paper investigates portfolio rebalancing strategies within thematic sectors of the NIFTY
Indices, focusing on the period from January 1, 2022, to July 31, 2024. We analyze ten …

This work investigates portfolio optimization strategies in the context of the Indian stock
market, focusing on ten thematic sectors listed in the National Stock Exchange (NSE) of …

Algorthmic Trading Strategy Design Using Deep Reinforcemnet Learning Page 1 Algorthmic
Trading Strategy Design Using Deep Reinforcemnet Learning Jaydip Sen Dept of Data Science …

Portfolio optimization is a fundamental concept in modern finance, aiming to construct a
portfolio that maximizes return for a given level of risk or minimizes risk for a given level of …

Portfolio optimization represents one of the fundamental pillars of modern financial theory.
Since Harry Markowitz introduced the concept of efficient diversification in the 1950s, this …