Using the Treynor-Black Model in Active Portfolio Management
Aruna Eluri, David S. Price, Kelly Walker
Course Project for IE590 Financial Engineering Purdue University, West Lafayette, IN 47907-2023 August 1, 2011
Abstract In 1973, Jack Treynor and Fischer Black published a mathematical model for security selection called the Treynor-Black model. The model finds the optimum portfolio to hold in the situation where an investor considers that most securities are priced effectively, but believes he has information that can be used to predict an abnormal performance of a few of them. The theory behind the model is presented, along with numerical examples to highlight specific realistic investment scenarios and how the model performs for each, showing the advantages and disadvantages of the model.
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Introduction
In developing investment strategy, there are two primary portfolio management styles – active and passive. Active management is a portfolio management strategy that has a goal of outperforming the market or some other investment benchmark index by making specific investment selections geared towards outperforming the market. Passive management is a strategy of being content to invest in an index fund that will closely replicate the investment weighting and returns of a specific index as the investor is not seeking to create returns in excess of that benchmark. The first style requires much more attention, effort, and diligence in obtaining and analyzing data, while the second requires much less dayto-day attention by its very nature. [9] To outperform the market and exploit market inefficiencies, the investment manager of an active portfolio purchases undervalued assets such as stocks or he short sells assets that are overvalued, or a combination of the two. Instead of always trying to increase value of a portfolio, the investor might also be trying to reduce the risk with respect to a benchmark index fund. [9]
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Treynor-Black
References: IE590, Financial Engineering, Summer 2011 David S. Price - July 19, 2011 clear all