Examination Of The Fees And Performance Structure Of Global Macro Hedge Funds
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Examination of the Fees and Performance Structure of Global Macro Hedge Funds
Author | : Michel Guirguis |
Publisher | : |
Total Pages | : |
Release | : 2019 |
Genre | : |
ISBN | : |
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This article aims at testing empirically the major building blocks that affect the performance of global macro hedge funds: incentive fees, management fees, size, age, hurdle rate, high watermark provision and lockup period. Investment risks are spread over different asset classes and investment strategies. Global macro hedge fund managers' focus to generate positive returns based on currency futures and options. He focused on fixed - income securities derivatives products or stock indices futures and options. They are trying to eliminate the market risk by examining carefully the macroeconomic indicators and the political trends. They are checking the appreciation or depreciation of currencies by using options and futures. They use spot and forward rates futures and options by checking the interest rates. They check the monetary policy of each country in relation to the macroeconomic indicators, related to employment, gross domestic product, inflation and production. In addition, they check changes in interest rates resulted from short and long - term US treasury fixed income products. Another strategy is to use index option and futures or commodity futures such as gold, silver, sugar, cocoa, oil to take advantage of inflation or deflation. For example, in an inflationary environment, commodity prices will rise and a long strategy will be profitable. In contrast, in a deflationary environment commodity prices will fall and therefore a short strategy will be profitable. The hedge fund portfolio is leveraged and the degree of risk is very high. The sample is provided from Data Feeder dataset. It is very comprehensive and includes global macro hedge funds for the period 1998 to 2003. There are other factors that could contribute to performance persistence such as lock-up periods, hurdle rate and high water mark. We are going to use a probit binary regression equation to test the factors that create performance persistence.
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