Building a Dynamic DCA-Leverage Algorithm to Reduce Liquidation Risk

🚀 I'm excited to finally share one of my quantitative finance research projects with my network.

Although this paper was published on SSRN earlier, I never got around to posting it here. I'm happy to finally share it.

"A Dynamic DCA-Leverage Algorithm for Optimized Average Positioning and Reduced Liquidation Risk."

This research presents a quantitative framework that dynamically adjusts Dollar-Cost Averaging (DCA) and leverage to improve average entry prices while reducing liquidation risk in highly volatile markets.

Rather than relying on fixed DCA intervals or static leverage, the proposed framework adapts to changing market conditions through systematic risk management and algorithmic decision-making.

Key areas covered

• Dynamic DCA allocation
• Adaptive leverage management
• Liquidation risk reduction
• Quantitative risk modeling
• Portfolio optimization concepts
• Algorithmic trading methodologies

Working on this research deepened my understanding of quantitative finance, financial mathematics, systematic investing, and algorithmic trading.

This paper was originally published on SSRN on January 12, 2025, and I'm looking forward to hearing thoughts from researchers, developers, traders, and quantitative finance enthusiasts.

📄 Read the paper:
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5662110

Constructive feedback and technical discussions are always welcome.