应gg999策略手机白菜的邀请,剑桥大学M.A.H. Dempster教授将于近期访问我校,并为师生做学术报告。
报告(一)
时间:2015.6.8, 10:10—11:30am
地点:理科楼407
题目:FINANCIAL INNOVATION AND BACKWARD STOCHASTIC DIFFERENCE EQUATIONS
报告摘要:
Economic agents are exposed to the uncertain outcomes of future events. By enabling the exchange of securities, financial markets allow agents to reallocate their exposures in more efficient and mutually convenient arrangements which reduce perceived risks. The complexity and changing nature of the world in which agents operate make all markets incomplete, which means that there is potential for further risk reduction by the introduction of new market securities to cover previously un-priced risks. The creation of new financial instruments is called financial innovation and is the topic of this paper.
Our mathematical tool for studying trading market equilibria is a novel theory of backward stochastic difference equations in discrete time, which we develop in analogy to the currently incomplete theory of backward stochastic differential equations in continuous time. Our approach allows the characterization of unique dynamic trading equilibria, optimal instrument design, inter-agent risk transfer and the implications for various real-life financial market structures which elude the continuous time BSDE theory. Some simple intuitive examples are presented.
报告(二)
时间:2015.6.8, 14:30—15:30pm
地点:理科楼407
题目:Life Cycle Goal Achievement or Portfolio Volatility Reduction?
报告摘要:
We concern with the use of currently available technology to provide individuals, financial advisors and pension fund financial planners with detailed prospective financial plans tailored to an individual's financial goals and obligations. By taking account of all prospective cash flows of an individual, and simultaneously optimizing prospective spending, saving, asset allocation, tax, insurance, etc. using dynamic stochastic optimization, we address the question of the title by comparing the results of such a goal-based fully dynamic strategy with representative current best practices of the financial advisory industry. Making use of the same data and market calibrated Monte Carlo stochastic simulation for all the alternative portfolio strategies, we find that flexibility turns out to be of key importance to individuals for both portfolio and spending decisions. The performance of the adaptive dynamic goal-based portfolio strategy is found to be far superior to all the industry’s Markowitz-based approaches. These empirical results should put paid to the commonly held view amongst finance professionals that the extra complexity of holistic dynamic stochastic models is not worth the marginal extra value obtained from their employment. We hope that such approaches implemented in currently available technologies will rapidly find acceptance by individuals, financial advisors and pension funds to the genuine benefit of individual investors.
报告人简介:
Michael A H Dempster 教授1965年于Carnegie Mellon大学获得数学博士学位,现为剑桥大学数学科学中心和剑桥商学院的教授。他是剑桥大学金融研究中心的创始人,培养了大批相关领域的专家和教授,并将其发展成世界金融工程与风险管理的研究中心。Dempster教授长期从事随机规划、金融管理等方面的研究工作,在国际顶尖学术期刊等上发表了110余篇学术论文,并编撰了13本专著。Dempster教授是伦敦数学协会、美国数学协会、国际数学规划协会和运筹学协会等多个国际学术协会的会员。他现任《Quantitative Finance》的主编,以及《Stochastics, Computational Finance》与《Journal of Risk Management in Financial Institutions》的 副编辑。并曾担任Journal of Economic Dynamics and Control、Computational Economics、Computational Finance等多个国际学术期刊的编委。
欢迎感兴趣的师生参加!