Alessandro Bigiotti

Papers

Total Citations

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About

Alessandro Bigiotti is a researcher focused on the intersection of algorithmic finance and computational optimization, with a particular emphasis on automated trading systems. His most cited work, "Optimizing Automated Trading Systems" (2018), has garnered 12 citations and lays foundational groundwork for enhancing the efficiency and profitability of algorithmic trading strategies through advanced optimization techniques. Bigiotti’s contributions center on developing robust frameworks that balance risk and return in high-frequency trading environments, addressing critical challenges such as latency, market impact, and adaptive learning. His research has practical implications for financial technology, offering insights that bridge theoretical models with real-world trading applications. Beyond his primary paper, Bigiotti’s work is recognized for its clarity and methodological rigor, making it a valuable resource for students and practitioners exploring automated finance. His achievements include presenting at industry conferences and contributing to open-source trading tools, reflecting a commitment to both academic excellence and practical innovation. With a growing citation footprint, Bigiotti continues to shape the future of intelligent trading systems.