标题：Leveraged Portfolio Selection under Liquidity Risk: Model, Theory,
and Computation
主讲人：Chanaka Edirisinghe, 美国伦斯勒理工学院 讲席教授, Lally治理学院学术副院长
主持人：陈靖楠 副教授
功夫：
2018年7月9日19:00-21:00
地址： leyu.com新主楼A座618
提要：
When a financial portfolio is rebalanced under market conditions to
satisfy leverage and other restrictions, asset illiquidity adversely-impacts
trading prices, and hence, the portfolio's performance. Using a continuous-time
trading model, we study the Pareto-efficiency between risk-adjusted return,
leverage, and target return. We show analytically that the Sharpe-maximizing
unlevered portfolio is no longer a tangency portfolio, and
proportionate-leveraging is not an optimal strategy under liquidity risk. As
target return increases, the required minimum portfolio-leverage increases at
an increasing-rate, while the Sharpe-Leverage frontiers are
progressively-dominated. These results contrast with the classical portfolio
theory that assumes no liquidity risk, and our empirical analysis using ETF
asset-data verifies that ignoring liquidity impact may lead to severe portfolio
under-performance.
If time permits, I will also consider a specific situation involving only
de-leveraging, where the model is simplified to maximize portfolio’s expected
value under leverage and margin limits. This leads to a separable model, but it
is extremely difficult to solve due to non-convexity. I will present a new and
general dual cutting plane technique that solves the Lagrangian dual
more-efficiently. The sensitivities of the optimal deleveraging strategy to
leverage and margin limits will be discussed in the context of the above data
set.
当调整投资组合以满足杠杆和其他限度时，资产流动性对买卖价值会产生不利影响，进而影响投资组合的阐发。使用陆续功夫的买卖模型，我们钻研风险调整收益率、杠杆率和指标收益率之间的帕累托效能。leyu.com解析了局批注，夏普率最大化的无杠杆投资组合不再是切向投资组合，在流动性风险下按比例加杠杆也不再是最优战术。随着指标收益的增长，所需的最低投资组合杠杆率以递增的速度增长，而夏普杠杆前沿逐步被主导。这些了局与忽略流动性风险的经典的投资组合理论分歧，并且我们基于ETF资产数据的实证分析证实忽略资产流动性会严沉影响投资组合阐发。
若是功夫允许，我还会思考一个特定的情况，只涉及去杠杆化，其中模型被简化以最大化投资组合在杠杆率和保障金限度下的预期价值。这导致了一个可分离的模型，但是由于其非凸性，求解极度难题。我将提出一个新的通常的双切割平面技术，更有效地解决拉格朗日对偶问题并会商最佳去杠杆化战术对杠杆率和保障金限度的敏感性。
主讲人简介：
Dr. Chanaka Edirisinghe holds a BS (Mechanical Engineering), an M.Eng
(Industrial Engineering and Management), and a Ph.D. (Management Science) from
University of British Columbia, Canada. He has published extensively in
operations research and finance, focusing on quantitative finance topics, as
well as stochastic and quadratic optimization. His research appears in
Management Science, Operations Research, Mathematical Programming, Mathematics
of Operations Research, as well as in Journal of Financial and Quantitative
Analysis, Journal of Banking and Finance, and Quantitative Finance, among
others. He received the Citation of Excellence Award by Emerald Management Reviews
in 2009 for publishing one of the top 50 management research articles in the
world. He was a former Vice Chair of Financial Services Section, as well as
Optimization Society of INFORMS, and he was the General Chair of the INFORMS
2016 annual conference.
Chanaka Edirisinghe教授于加拿大英属哥伦比亚大学获得治理科学博士学位、工程学硕士学位及工业机械工程学士学位，并在运筹学和金融学领域颁发了大量文章，他专一于量化金融、随机和二次优化。他在Management Science,
Operations Research, Mathematical Programming, Mathematics of Operations
Research, Journal of Financial and Quantitative Analysis, Journal of Banking
and Finance, Quantitative Finance
等杂志上颁发过文章，并于2009年获得Emerald Management Reviews宣告的Citation of Excellence Award。他曾担任美国运筹与治理科学协会（INFORMS）金融服务分会和优化分会副主席，并且担任INFORMS 2016年会的大会主席。
编纂：宋超
