Ruijing Yang, Ph.D. Candidate in Financial Engineering

Bio

Ruijing Yang is a Ph.D. candidate in financial engineering at Stevens Institute of Technology with a strong background inquantitative analysis, financial modeling and computational finance. She is experienced in programming (Python, C++) and developing quantitative strategies for optimal portfolio execution.

Skillset

She is proficient in financial computing, stochastic calculus, and advanced optimization techniques, with hands-on experience inPython and C++ for model development. Skilled in statistical analysis, machine learning, and numerical algorithms for quantitative trading.

Dissertation Summary

Optimal Portfolio Execution under Capital Ratio Constraint

This dissertation investigates strategies for liquidating portfolios of risky assets over a given time frame,considering regulatory capital adequacy requirements and price impacts.Capital adequacy ratios are crucial for financial institutions as they serve to prevent excessive leverage and therisk of insolvency. The study focuses on optimal liquidation policies that incorporate these capital constraints,ensuring that institutions maintain adequate capital buLers throughout the liquidation process.The research addresses the challenges posed by chance constraints designed to ensure compliance withcapital adequacy requirements. Two distinct formulations of chance constraints are examined to manage thecapital adequacy ratio eLectively during liquidation. The first approach enforces a constraint at each individualtime step, requiring that the capital adequacy requirement is met consistently with a specified probability throughout the liquidation period. This method aims to maintain compliance in a stepwise manner, oLering arobust approach to managing capital.The second approach focuses on the overall trajectory of capital adequacy across the entire liquidationperiod. This oLers a more holistic view of the institution’s capital adequacy over time but poses additionalcomplexities in ensuring compliance over the complete liquidation process.

For the problem utilizing individual time step constraints, a conservative reformulation is developed, along withsuLicient conditions for convexity. These methods simplify the computational challenges associated withmanaging capital constraints in real-time. The joint constraint problem, which examines the trajectory of capitaladequacy across time, is addressed using stochastic approximation methods to derive an optimal strategy forasset liquidation. The comparison between these two formulations reveals that the conservative approximationmethod is generally more computationally eLicient, providing practical advantages for real-world implementation.

Numerical results are presented for both single-asset and multi-illiquid asset scenarios, oLering insights intooptimal strategies under diLerent market conditions. The findings suggest that the presence of capitaladequacy constraints tends to change the behavior of optimal liquidation strategies, as it needs to balanceimmediate liquidation revenue against the necessity to maintain suLicient capital buLers.

Overall, the dissertation contributes to the field of financial engineering by providing novel approaches to assetliquidation under regulatory constraints, enhancing both the theoretical understanding and practical application of capital adequacy compliance in portfolio management. The results also have implications forfinancial institutions seeking to optimize their liquidation strategies while adhering to regulatory standards and managing market impacts.