Post-modern portfolio theory uses downside risk to refine portfolio optimization. Learn how PMPT offers an alternative to modern portfolio theory for risk-adjusted returns.
Recent data from Empire State and Philly Fed surveys signal a genuine early-stage rebound in industrial activity. Click for ...
This paper introduces an innovative approach to optimizing the designs of cantilever beams for sensor applications. It combines machine learning techniques with quasi-Newton optimization methods.
portfolio-optimization-rl/ ├── src/ │ ├── envs/ │ │ └── portfolio_env.py # Portfolio optimization environments │ ├── agents/ │ │ └── rl_agents.py # RL agent implementations │ └── config.py # ...
Nanotechnology and machine learning are transforming energy systems by enhancing engine efficiency and sustainability. The integration of advanced nanomaterials, such as gold nanoparticles (AuNPs), ...
Abstract: This research discusses the important and complex issues of retirement planning in India, where the majority of workers must rely on their own savings due to rising life expectancy, low ...
Introduction: The Portfolio Optimization Process Needs to Be Revamped. For decades, portfolio optimization has been the pinnacle of modern finance. In the 1950s, with the introduction of Harry ...
College of Mechanical and Electronic Engineering, Shanghai Jianqiao University, Shanghai, China Introduction: To enhance energy management in electric vehicles (EVs), this study proposes an ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results