Biases in Hedge Funds Indices
- Editore:
GRIN Publishing
- EAN:
9783640386161
- ISBN:
3640386167
- Pagine:
- 40
- Formato:
- Paperback
- Lingua:
- Tedesco
Descrizione Biases in Hedge Funds Indices
Seminar paper from the year 2005 in the subject Business economics - Banking, Stock Exchanges, Insurance, Accounting, grade: 5,5 (1,5 in GER), University of St. Gallen, course: Doktorandenseminar; Corporate Finance, language: English, abstract: Nowadays, modern investors are well informed by Hedge Funds managers who are not getting tired promoting the merit of investing in hedge funds. These advisers draw elaborated graphs showing the benefits of hedge funds to an active managed portfolio. Investors have to believe in the advantages of shifting a significant part of their portfolio to hedge funds. In terms of the classical risk and return measures the advisers are right, high returns, low volatility and above all low correlations to the other asset classes in the portfolio. But as we know only the half is true. The misleading picture of volatility if measured with the classical portfolio instruments and the correlation effects is not solved in this paper. The research interest in this short paper is the distorted picture of returns given by the Hedge Funds Indices because of biases inherent to those indices. This paper gives an overview of the Hedge Funds Industry and the Hedge Funds Indices that are currently used by investors and highlights the differences between Hedge Funds and traditional Mutual Funds Indices. The problems of setting up those indices because of Hedge Fund idiosyncrasies are discussed. It is also shown why the performance of these indices is misleading due to construction problems. These systematic errors in the Indices are called biases. The paper provides an overview of the biases that can occur, when an Index is set up and why. We will introduce a classification of biases based on three phases. There will be an emphasis on the most popular bias, which is the survivorship bias. To support the existence of biases, the paper gives an overview of some empirical studies, which in general showed quite significant biases, ranging from 0.39 % to 3 % in performance misstating. Additionally the survivorship bias was simulated in this paper, using a methodology introduced in Zimmermann (2000). Then we will provide some advice on how these biases can be reduced and how they can be avoided by investors.
