Challenges and Insights in Hedge Fund Data Analysis
Two young businesswomen working at modern office
Hedge funds, exclusive investment vehicles for professional or accredited investors as per regulations like the U.S. Securities Act of 1933, present distinctive opportunities in financial markets. Various major data vendors, including BarclayHedge, Eurekahedge, Morningstar, HFR, HFM, and others, provide access to hedge fund data. Estimating the total number of hedge funds remains a challenge due to conflicting calculations, such as considering fund subclasses separately and including or excluding Commodity Trading Advisors (CTAs) and hedge fund of funds. The estimated total number of hedge funds ranges from 15,000 to 17,000 when subclasses are excluded and expands to approximately 56,000 when subclasses are included.
Hedge fund data encompasses three primary datasets: descriptive or qualitative information, pricing and assets under management (AUM) data, and holdings information.
Qualitative Information:
This dataset contains up to 4,000 data points, depending on the data vendor. The main mandatory fields include the following ones:
– Fund Name
– Fund Other Fee
– Fund Prime Broker
– Fund Domicile
– Fund Highwater Mark
– Fund Prime Broker Contact
– Fund Type
– Fund Hurdle Rate
– Fund Prime Broker Phone
– Fund Status
– Fund Leverage
– Fund Auditor
– Fund AUM USD
– Fund Subscription Frequency
– Manager Name
– Fund Currency
– Fund Lockup Period
– Manager Address1
– Fund AUM Reported Currency
– Fund Redemption Frequency
– Manager City
– Fund Inception Date
– Fund Redemption Notice Period Days
– Manager State Province
– Fund Reports Daily Data
– Fund Redemption Payout
– Manager Zip Code
– Fund 13F Filing Available
– Fund Strategy
– Manager Country
– Fund Investment Minimum
– Fund Advisor
– Fund SEC Registered
– Fund Reporting Style
– Fund Advisor Contact
– Fund Uses Equalization
– Fund Management Fee
– Fund Advisor Contact Phone
– Fund Equalization Method
– Fund Performance Fee
– Fund Custodian
– Fund Targeted Return
– Fund Redemption Fee
– Fund Custodian Contact
– Fund Targeted Volatility
Performance Data:
This data set usually includes the following data points:
– Fund RoR (rate of return) for the period, usually a month.
– Fund NAV or unit price.
– Fund AUM.
Holdings Data:
Holdings data is an optional dataset provided by only a select few vendors due to the confidentiality of holdings information, which fund managers typically do not disclose publicly. Hedge fund investors may access this information under a non-disclosure agreement (NDA). Another way of evaluating hedge fund risks based on their holdings is through holdings based analysis offered by only a few analytic providers. Although end clients don’t have direct access to hedge fund holdings, they can still assess investment risks calculated on holdings and not fund returns.
Biases in Hedge Fund Data:
1. Survivorship Bias: This bias occurs when hedge fund databases only include funds that have survived over a certain period, excluding poorly performing or closed funds. It can lead to an overestimation of hedge fund returns.
2. Selection Bias: This bias results from the non-random selection of funds included in databases, skewing performance data based on reporting criteria or size.
3. Back Reporting Bias: The practice of retroactively adding successful funds to a database can distort overall performance data by selectively highlighting successful funds.
4. Instant History Bias: Including newly launched funds in databases with historical performance data can create a misleading impression of a fund’s track record.
Short Data Series Challenge:
Hedge fund analysis often faces limited data series, around twenty to sixty monthly observations, compared to stocks and bonds. This necessitates the use of analytical methods that can provide confidence despite limited data, such as the Conditional Value-at-Risk (CVaR). However, concerns about accuracy and reliability arise due to the reliance on a small number of historical observations.
In conclusion, navigating hedge fund data requires addressing challenges like survivorship bias, selection bias, limited data series, and biases in data reporting. Investors must access clean and unbiased data to make informed decisions and enhance their chances of success in hedge fund investing.
