Funds of Hedge Funds

Even though hedge funds are very popular, they are not accessible to small investors because of the higher amount of investment required. An alternative is a fund of hedge funds that allows all kinds of investors easy access to the hedge funds. Unlike a hedge fund that invests in stocks, bonds and other securities, a fund of funds invests in a selection of hedge funds. As an FOFs client base grows, it can invest larger amounts of money in hedge funds.

Benefits

Funds of Funds provide several benefits to investors:

  • Retail investors: Using FOFs, even retail investors get access to huge funds.
  • Access: Sometimes a hedge fund may not be accessible to investors because it has reached maximum number of investors or any other factor. An FOF may be able to provide investment in such hedge funds.
  • Diversification: Instead of investing in a single hedge fund, an investor can diversify its portfolio.
  • Expertise: Individual investors may not have the skill and expertise to find good hedge funds. Funds of funds provide the expertise of the managers who have experience and skill in selecting hedge funds.
  • Due Diligence Process: While selecting a hedge fund, even institutional investors have to perform due diligence which is a specialized process and is also time consuming. An FOF may be more suited for this job.

Drawbacks

Funds of Funds also have some drawbacks:

  • Fees: The total fee can be very high because the investors also have to pay the manager's fees apart from the fee charged by each hedge fund.
  • Performance: It's not necessary that an FOF will perform better or provide consistent performance.
  • Diversification is not always good: Mixing high performing hedge funds with other funds to lower the risk may defeat the overall purpose of investing in hedge funds.

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Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

Each book comes with PDFs, detailed explanations, step-by-step instructions, data files, and complete downloadable R code for all examples.