How Alternative Funds Can Fight off the Passive Investing Threat with Smarter Transparency Tools

The global financial crisis and subsequent financial re-regulation elevated the importance of risk management within the alternative funds industry.

The prevalent view, to date, has been that these additional demands simply equate to a greater compliance burden, and cost, but otherwise it remains business as usual.

That perception is now evolving, and with it, the appreciation of the greater role that risk management can perform. This shift can be attributed to a number of related factors: poor performance; growth of passive strategies; changing investor base; and the concept of beta-adjusted fees.

However, the demand for greater transparency and how funds can use this to their competitive advantage stands apart from these other factors. A recent Preqin survey of investors identified ‘transparency at fund level’ as the leading issue for hedge fund investors, behind fees, with 63% of surveyed investors stating that increased transparency at the fund level needs to improve further.

What lies behind this dissatisfaction is how, after years of mediocre performance, alternative funds, and hedge funds, are under growing pressure to justify both their fees and fee structures. More transparent risk functions provide a means to better communicate a fund’s performance and risk and hence support the fund’s value proposition.

A change in the alternative assets investor base from high worth individuals to institutional investors has also contributed to a greater pressure for transparency.

Prior to the global financial crisis, family offices and ultra-high net worth individuals dominated alternative funds AUM. This segment has shrunken since 2008, and now institutional investors comprise a far greater proportion of total assets. It could be argued that the trust that family offices bestowed on hedge funds to generate returns and manage risk has been slow to recover. Institutional investors require greater transparency to provide a thorough appraisal of performance and risk, and they also now face a growing regulatory burden and associated liability, such as Solvency 2 for insurance companies. While performance remains a critical concern, being able to evaluate a fund’s risk is increasingly important, particularly when the institution may be allocating to dozens of alternative managers to deliver on specific mandates, which requires on-going monitoring that the funds stick to these mandates and do not exhibit ‘style drift’.

Firms that can use risk management as a means for providing transparency and valuable reporting to investors rather than simply a compliance function will be at a competitive advantage. But how specifically can they provide the greater, more granular transparency demanded by their clients?

Answering this question matters hugely, as alternative funds are confronted by the rise of passive investing products. Many institutional investors are moving away from actively managed assets to exchanged traded funds or exchange traded notes. Offering greater transparency is challenging for funds because of the complexities involved and the need to provide insights that must be tailored to the different requirements of the different stakeholders within an institution.

Advances in financial modelling and computation, based on the same mathematical computer modelling used to design fighter aircraft or by central banks to manage risk, can offer a solution, as one leading emerging fund manager has discovered.

Empiric Managed Capital Master Fund is a systematic global long/short equities fund based in London. The fund provides its services to high net worth clients and institutions, and invests in public equity markets across the globe.

Empiric Capital approached the market as a new alternative asset manager. As a quantitative investment firm founded by a team with backgrounds in satellite communications, statistics, signal processing and machine learning, Empiric Capital developed from the beginning sophisticated, proprietary technology, which is employed for both portfolio and risk management. The team at Empiric however, believed there would be added-value in providing independent risk reporting that could also be customised to incorporate feedback from existing and prospective investors. Having reviewed several options, Empiric chose RiskMonitor®, a risk reporting solution developed by Clarus Risk, which provides investor- friendly risk reporting by offering a wide range of graphical and tabular risk analysis within a high-quality presentation format.

Typically risk reports tend to be based on a fixed template which may be inappropriate for a fund with a bias towards specific asset-classes or which follows a specific investment strategy. RiskMonitor allowed Empiric Capital to achieve an appropriate solution for its own strategy and investors, and to communicate risk data in a user-friendly fashion.

This greater flexibility offered RiskMonitor is that it is an object-oriented solution built using MATLAB, and making extensive use of a wide range of MATLAB toolboxes available, along with proprietary code and .NET libraries.

There are several MathWorks toolboxes that RiskMonitor uses to provide a coherent risk solution. MATLAB Report Generator provides functions for the Document Object Model (DOM) API, which facilitates object-oriented report generation. The Datafeed Toolbox enables efficient connectivity with leading market data vendors. The Financial Instruments Toolbox provides flexibility with how to model and incorporate Financial Derivative Instruments (FDIs) into risk reporting. This flexibility is highly valuable as portfolio managers and their counterparties may employ subjectivity as to how to value and model risk exposure. The Econometrics Toolbox helps to model and analyse financial risk systems using statistical methods and the Financial Toolbox provides financial data processing and portfolio logic. The extensive risk modelling and analysis support provided by these toolboxes, coupled with an environment from which RiskMonitor can leverage .NET, has made MATLAB integral to the RiskMonitor.

As a result, Empiric Capital can offer its clients some notable examples of customisable transparency in its risk reports, while allowing their own research and development team to focus entirely on investment management. RiskMonitor’s provision of trade statistics, such as batting average and win/loss ratio, demonstrate the inherent risk management processes employed by Empiric Capital. Losing positions are cut early in a systematic fashion which is reflected in a high win/ loss ratio and visually illustrated in a negatively skewed trade P&L histogram. Such a profile is consistent with strong risk-adjusted performance and is based on hundreds of realised trades whereas typically investors would look to wait for years to be able to evaluate historic monthly fund performance to perform some meaningful quantitative analysis.

The reports also detail the top winning and losing positions over the last month and quarter. The stock- selection strategies employed by Empiric Capital leverage insight and experience gained from outside of financial services and the fund has low exposure to traditional risk factors such as Value and Momentum. Current and historic exposure to risk factors is presented within RiskMonitor reporting. In addition, the reporting provides performance attribution between sector and stock-specific effects as well as liquidity and turnover analysis. The provision of a range of risk metrics enables investors to develop a ‘mosaic’ analysis of Empiric.

RiskMonitor reports are distributed to Empiric’s mailing list on a monthly basis. This list includes fund directors, shareholders, investors and prospects.

Alexandru Agachi, COO, Empiric Capital sees the tools as giving the firm real competitive advantage: “Employing RiskMonitor, with its inherent MATLAB functionality, enables us to offer our clients a powerful way to gain a deeper understanding of the drivers of risk and return, which assists with developing investor relations and client engagement.

Author: Dylan Jones

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