
Contents
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8.1 Hedge Fund Replication Methods 8.1 Hedge Fund Replication Methods
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8.1.1 Factor Replication 8.1.1 Factor Replication
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8.1.2 Rule-Based Replication 8.1.2 Rule-Based Replication
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8.1.3 Dynamic Trading 8.1.3 Dynamic Trading
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8.2 Replication Products 8.2 Replication Products
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8.2.1 Performance 8.2.1 Performance
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8.2.2 Selection Risk 8.2.2 Selection Risk
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8.3 Conclusion 8.3 Conclusion
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References References
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8 Hedge Fund Clones
Get accessNils Tuchschmid is currently Professor of Banking and Finance at Haute École de Gestion, University of Applied Sciences in Geneva, Switzerland. He is also Invited Professor of Finance at HEC Lausanne University and lecturer at the University of Zurich and ULB in Bruxelles. He is the author of books and articles on traditional and alternative investments, on portfolio management, and on optimal decision making processes. Up to 1999, he was a Professor of Finance at HEC Lausanne. Prior to joining HEG in 2008, he worked for various financial institutions, among others, BCV, Credit Suisse, and UBS.
Erik Wallerstein is a quantitative analyst at Credit Suisse in Zurich, Switzerland. Previously he was a research fellow at Haute École de Gestion, University of Applied Sciences in Geneva, Switzerland. He holds an M.Sc. in applied mathematics from Lund University, Sweden, and a master’s in advanced Studies in Finance from ETH-Zurich and University of Zurich. At HEG he was working together with Professor Nils Tuchschmid where they published in the area of hedge fund research.
Sassan Zaker is a manager of Alternative Investments at Julius Bär. He joined Bank Julius är& Co. Ltd. in 2004 as Head Alternative Products and Advisory. Before joining Julius he worked for Swissca Portfolio Management, Finfunds Management AG, and UBS. Sassan Zaker has 17 years of business experience in quantitative analysis, portfolio management, and private and institutional client experience. He holds a master’s and Ph.D. engineering degree from the Swiss Federal Institute of Technology (ETH) and is also a CFA charterholder.
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Published:21 November 2012
Cite
Abstract
The hedge fund replication refers to the process of replicating, or cloning, the returns of hedge funds through a statistical model or algorithmic trading strategy. There are three approaches that are employed for hedge fund replication. The first method, factor replication, is a top-down approach, which tries to estimate asset exposures of hedge funds with various statistical methods. The second is a bottom-up approach, which is referred here to as rule-based replication. The article aims to isolate broad and fundamental characteristics of hedge fund strategies and implement these with automated trading algorithms. The third approach aims to replicate desirable distributional properties of hedge fund returns with dynamic trading techniques. The underlying assumption of factor replication method is that major parts of hedge fund returns can be captured by a set of common risk factors. The dynamic trading approach aims to match the distributional properties such as mean, volatility, and correlation of hedge fund return time-series relative to a portfolio of common assets. The return time-series of hedge funds are not expected to be replicated on a monthly basis. The implementation of dynamic trading involves three steps. Firstly, the investor's portfolio is used to functionally define desirable dependence structures relative to hedge fund returns. The second step is to derive the payoff function, where the reserve asset is the dependent variable, which will give the dependence structure relative to the investor's portfolio. The final and third step is to derive the dynamic trading strategy, which replicates the payoff function.
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