Aurum Hedge Fund Data Engine
The Hedge Fund Data Engine is a proprietary database maintained by Aurum Research Limited (“ARL”) containing data on around 3,000 active hedge funds representing around $3.1 trillion of assets as at June 2022.
Data from the Hedge Fund Data Engine is provided on the following basis: (1)Hedge Fund Data Engine data is provided for informational purposes only; (2) information and data included in the Hedge Fund Data Engine are obtained from various third party sources including Aurum’s own research, regulatory filings, public registers and other data providers and are provided on an “as is” basis; (3) Aurum does not perform any audit or verify the information provided by third parties; (4) Aurum is not responsible for and does not warrant the correctness, accuracy, or reliability of the data in the Hedge Fund Data Engine; (5) any constituents and data points in the Hedge Fund Data Engine may be removed at any time; (6) the completeness of the data may vary in the Hedge Fund Data Engine; (7) Aurum does not warrant that the data in the Hedge Fund Data Engine will be free from any errors, omissions or inaccuracies; (8) the information in the Hedge Fund Data Engine does not constitute an offer or a recommendation to buy or sell any security or financial product or vehicle whatsoever or any type of tax or investment advice or recommendation; (9) past performance is no indication of future results; and (10) Aurum reserves the right to change its Hedge Fund Data Engine methodology at any time and may elect to supress or change underlying data should it be considered optimal for representation and/or accuracy.
The Aurum Hedge Fund Data Engine (“Hedge Fund Data Engine”) is a proprietary database and analytics tool which captures monthly hedge fund performance, AUM, P&L and net flows (amongst other metrics and qualitative data points) on a broad section of the hedge fund industry, with datasets going back, in some cases, 25 years.
As at June 2022 ARL tracked ~3,000 active hedge funds (“active” being defined as funds which have reported numbers within the last 12 months), representing ~ $3.1 trillion of assets. Information in the Hedge Fund Data Engine is derived from multiple sources: ARL’s own research, regulatory filings, public registers and other database providers.
Constituent hedge funds are assigned a Master Strategy and Sub Strategy. In total there are nine master hedge fund strategies, as shown below (with these Master Strategies’ Sub Strategies shown in parenthesis):
- Arbitrage (Convertible Bond, Opportunistic, Tail Protection and Volatility Arbitrage)
- Credit (Distressed and Credit)
- Equity Long/Short (Asia Pacific Long/Short, European Long/Short , Fundamental Equity Market Neutral, Global Long/Short, US Long/Short , Sector Long/Short and Other Long/Short)
- Event (Activist, Merger Arbitrage, Multi-Strategy and Opportunistic)
- Long Biased (Commodities, Diversified Growth, Equity and Long Biased Other)
- Macro (Commodities, Fixed Income Relative Value, Global Macro, Macro Emerging Markets)
- Multi Strategy
- Quant (CTA, Quant Macro/GAA, Quantitative Equity Market Neutral, Risk Premia and Statistical Arbitrage)
- Other (Insurance, Other)
Each Master Strategy must have a minimum of 100 funds to qualify as a Master Strategy for these purposes.
POPULATING AND UPDATING THE DATABASE
ARL’s analysts are responsible for the classifications of funds within the database to Master and Sub Strategies. At times this might differ from the underlying manager’s classification, for example due to the manager’s marketing objectives. ARL reserves the right to apply its own classification, and to reclassify a fund to a different strategy if, for example, the fund undergoes style drift.
In order to be included in the Hedge Fund Data Engine, a fund’s strategy must be truly representative of a hedge fund. For instance, the Hedge Fund Data Engine generally by excludes long only mutual equity and bonds funds (and those that have been identified to have similar structures). Aurum reserves the right to include and exclude funds at its discretion.
There is no minimum AUM or minimum performance reporting period required for a fund to be eligible for inclusion in the database.
Fund performance is reported net of fees.
Whilst ARL collects daily and weekly data on many hedge funds, the Hedge Fund Data Engine itself uses monthly data series only. This data is populated as and when available to ARL where fund performance is not reported on a timely basis, this can have an impact on monthly indices performance previously produced by the Hedge Fund Data Engine. Equally, historically published numbers may change due to ARL reclassifying a hedge fund, or because a new manager is added to the database, bringing a previously unreported track record. ARL seeks to continually build and improve the Hedge Fund Data Engine, though this can have the effect of restating previously reported data.
ARL reserves the right to alter or suppress a fund’s reported numbers (AUM or performance) from an index where it believes such action to be appropriate. Such instances may occur for many reasons such as where it is apparent that a ‘fat finger’ error has occurred ( for example where a manager which has consistently reported a $1bn AUM reports a $100bn AUM, before reverting to a $1bn AUM or where a fund only reports annually (in which case performance and AUM are allocated monthly on a straight line basis over the period). In such instances ARL reserves the right to overwrite a manager’s numbers without consultation. At other times ARL may query manager track records directly with managers, or refer to other external databases.
ARL reserves the right to carry forward a fund’s reported AUM when it has stopped reporting for a period and subsequently restarts reporting at a later date. Fund AUM is normally estimated on a reasonable basis across this period so flows are not impacted dramatically.
ARL reviews ‘new’ funds which have either launched or started reporting on a quarterly basis or ad hoc when required. These funds are reviewed to ensure they fit the required Hedge Fund criteria, are allocated a strategy and then released into the Hedge Fund Data Engine.
ARL carries out an annual review of the Hedge Fund Data Engine to remove or reclassify funds which cease to meet the relevant criteria. A review may be carried out between annual reviews where exceptional circumstances require an update. Where a fund is reclassified, all historic returns will fall under the revised strategy. Funds that are removed are removed entirely, including in respect of historic returns. ARL reserves the right to carry forward a fund’s reported AUM when it has stopped reporting but is considered to still be ‘alive’. Funds normally are required to be greater than $2bn to be considered for this review due to their impact to the universe. This is referred to as ‘rolled forward’ AUM. Rolled forward AUM is not included in any calculations when statistics that include performance data are generated.
Please see “Historical Changes” below for impactful changes made to the Hedge Fund Data Engine.
Liquidated funds are maintained within the database to prevent look back survivorship bias.
All funds’ AUM within the Hedge Fund Data Engine are reported in USD. Where funds report in a different currency ARL generally applies the relevant month end FX rate to the non-US AUM for the month in question to create an equivalent USD AUM. Fund returns are typically reported in USD performance terms.
Performance data is typically based on month end estimates, as opposed to finalised performance. As such there may be reporting differences, where a fund’s performance estimate differs from final performance. Given the number of index constituents, ARL considers it unlikely that this would have any material impact on overall index reporting.
When a new fund is added to the database its performance returns and AUMs are typically backfilled as far as possible, which may alter previously reported index performance.
When a fund closes to capital it is still included in full in the database. The Hedge Fund Data Engine indices are not produced for investment purposes, but for relative performance measurement purposes.
AUMs and performance are typically reported by the managers and are therefore unaudited. ARL places reliance upon these self-reported numbers and does not generally independently validate them.
Whilst AUM and performance numbers are typically reported to ARL, calculation and assumptions are made with regard to the dollar P&L and net flow movements used by ARL. Dollar P&L (this is referred to within ARL as Dollar Creation/Destruction) is simply calculated based on a fund’s starting AUM multiplied by the monthly net performance return. Net flow data is then calculated by acknowledging the difference from the subsequent AUM and the prior month’s AUM with reference to the Dollar P&L. For instance, a fund reports a month 1 AUM of $100m and a month 2 AUM of $120m. If reported performance for month 1 was 10%, ARL calculates Dollar P&L as $10m and therefore can assume that the net difference relates to net flows into the fund at the end of month 1, i.e. +$10m.
ARL seeks to ensure that, where possible, only unique funds are included, deleting duplicate funds where double counting may be occurring, e.g. where onshore and offshore funds, or different share classes, are reported. In these cases ARL takes the aggregate AUM and typically applies the lead series or performance of the largest or longest-running vehicle, as may be appropriate or available.
- June 2022
- The Long Biased strategy was closely reviewed to remove funds Aurum would not classify as “Hedge Funds”. This removed ~$290bn or ~270 funds from the Hedge Fund Universe
- December 2020
- A Master Strategy level clean up exercise was carried out. This involved removing dead hedge funds from the ‘rolled forward’ AUM and saw the removal of approximately 590 funds representing approximately $117bn of AUM across all strategies.
- October 2020
- An exercise was completed to clean the Alt-UCITS funds within the Hedge Fund Data Engine, this removed ~200 funds or ~$76bn of AUM, mostly those within Long Biased.
ARL maintains three main index types, Asset Weighted, Equally Weighted and Median Weighted, but also maintains various other percentile/decile related indices.
Asset Weighted indices have their performance applied with respect to the AUMs of their constituents. In certain cases, where managers’ report performance for a particular month, but not AUM, ARL may ‘fill’ AUM as it considers appropriate, usually using a roll forward methodology. Equally, at times, a manager may fail to report a particular month’s AUM, or may only report AUMs on a quarterly basis. In such instances ARL reserves the right to fill, or roll forward, AUMs as it considers appropriate.
Equally Weighted (mean average) indices give all constituents with performance reported an equal weighting in the index, regardless of AUM. As such, a recently launched $10m vehicle may have the same impact on an index as a long established $10bn hedge fund.
Median (or Percentile). The performance of the 50th percentile fund is taken as the representative performance for the index. All performance values from funds reporting above or below the 50th percentile are ignored. It is acknowledged that where skew (tail distribution) occurs, the impact can create sizeable differences to that of an equally weighted index.
It should be noted that the Hedge Fund Data Engine does not engage in Windsorization of its equally weighted indices. Windsorization is a systematic process where the extreme ends are cut, for instance at the 5th and 95th percentile. This process can reduce the impact of outliers on an index.
Using the Database
It should be noted that, whilst the Hedge Fund Data Engine’s indices can be scrutinised down to constituent fund level, the constituent funds are never disclosed outside the Aurum group. ARL only shares appropriately aggregated data within its indices.
The Hedge Fund Data Engine can create many indices using numerous hedge fund characteristics, referred to as “dimensions”, for which each fund in the database has been tagged where possible. For instance, a fund can be tagged by the dimensions of Strategy, Sub Strategy, Size, Liquidity Terms, Service Providers, Correlation to Indices, Aurum Analyst Rating, Management Entity, and Fee Structure, to name but a few.
Where an index is created on a regional basis (City, State, Country, World Region), this refers to the manager’s headquarters, which may not be the region in which the fund is active. For instance, a Japan-focused fund with a New York-based manager is classified within the US region, despite its trading strategy being entirely Japan-focused. For a large multi-locational multi-strategy vehicle, the dimension tagged is the manager’s main headquarters. Investment Manager investment exposure is different to Sub-Strategy geographical location when it comes to the regional classifications.
Indices may suffer from self-reporting bias, where managers cease reporting due to poor performance, leading to over performance of the index. Conversely, successful funds may hard close or return capital to investors and stop reporting their performance; this may lead to underperformance of the index.