Deconstructiong Black-Litterman - Or How to get the Portfolio You Always Knew You Wanted
- March 14, 3:00 - 4:30, Hill Center 552
The Markowitz (1952, 1959) mean-variance (MV) efficient frontier has been the theoretical standard for defining portfolio optimality for more than a half century. However, MV optimized portfolios are highly susceptible to estimation error and difficult to manage in practice (Jobson and Korkie 1980, 1981; Michaud 1989). The Black and Litterman (BL) (1992) proposal to solve MV optimization limitations produces a single maximum Sharpe ratio (MSR) optimal portfolio on the unconstrained MV efficient frontier based on an assumed MSR optimal benchmark portfolio and active views. The BL portfolio is often uninvestable in applications due to large leveraged or short allocations. BL use an input tuning process for computing acceptable sign constrained solutions. We compare constrained BL to MV and Michaud (1998) optimization for a simple data set. We show that constrained BL is identical to Markowitz and that Michaud portfolios are better diversified under identical inputs and optimality criteria. The attractiveness of the BL procedure is due to convenience rather than effective asset management and not recommendable relative to alternatives.
** Refreshments will be served at @ 2:30pm in Room 503 Hill Center **
***New Frontier is a Boston-based research and registered investment advisory firm specializing in the development and application of state-of-the-art investment technology. Founded in 1999 by the inventors of the world's first broad spectrum, patented, provably effective portfolio optimization process, the firm continues to pioneer new developments in asset management. New Frontier's services help institutional investors worldwide select and maintain more effective portfolios. A globally-recognized independent research authority, New Frontier continues to contribute to the cutting-edge of investment theory in asset allocation, investment strategies, global investment management, optimization, stock valuation, portfolio analysis, and trading costs.
Dr. David Esch, Ph.D; Director of Research at New Frontier Advisors
Dr. Esch is an applied statistician with experience in multiple fields. I specialize in solving difficult numerical problems and am proficient in mathematical analysis and computation. I hope to continue doing research and tackling interesting quantitative problems. Specialties:Quantitative and Data analysis problem solving using compute-intensive methods; Mathematical statistics with applications in finance and econometrics, health care research, and astrophysics; technical writing and computer programming in several languages.