As investors continue to boost their allocations to alternatives, how they address the issue of enterprise risk can have important consequences for the perceived risk within their portfolios, according to a new white paper from BNY Mellon. Enterprise risk analysis, including stress testing and scenario assessment, has become increasingly popular with institutional investors. But alternative investments – hedge funds, private equity, real estate, etc. – present many challenges. In a sometimes complex paper, the bank seeks to provide a checklist for investors that suggests several best practices that will help them best utilise their enterprise risk analysis.
Authored by BNY Mellon and its affiliate HedgeMark, the paper, Considering the Alternatives: A Practical Look at Enterprise Risk Analysis and Alternative Investments, specifically explores the impact of incorporating illiquid or non-transparent investments into enterprise risk analysis. It looks at how different approaches to data management can affect the resulting analysis, the associated benefits and issues, and offers solutions. “With a sharper focus on risk by regulators and other stakeholders, many institutional investors seek a fuller picture of how risk operates across investments within an entire portfolio,” says Frances Barney, CFA, head of Consulting-Americas for Global Risk Solutions at BNY Mellon. “Data is getting more and more critical and investors need to be informed and comfortable with the assumptions of their risk assessment, otherwise, they can come out of it with a false sense of security about their portfolio.”
Enterprise risk includes the many factors that can affect an organisation, including market, reputational, regulatory, compliance, operational and legal risk. Enterprise risk analysis also can include forward-looking, or “ex-ante,” calculations that estimate investment risks across multiple asset classes. The paper focuses on the risks inherent to an investment program with multiple asset classes owned by a single organisation, such as a pension plan or a charitable foundation.
The paper suggests that different approaches to data management can lead to different potential conclusions about the risks within an investment portfolio. It outlines the nuances involved in properly assessing the impact of risks on aspects of business and investment. Exposure-based risk analysis, for example, identifies the relevant risk factors for each investment, enabling the preparation of summaries of portfolio allocations to various categories of exposures or factors, or investment characteristics.
Investment strategies or broad asset classes have characteristics that may be more relevant to one strategy than another. For example, duration is a key risk characteristic for fixed income investments but less relevant for common stock. Other characteristics can be relevant across asset classes. Moreover, credit ratings are often associated with bonds but may also be associated with the issuers of common stock.
Risk management as a function is necessary whenever there is the desire to take and understand risks. The practice of risk management has changed significantly over time, but it continues to be a discipline without definitive standards, says the paper. The best practices discussed in the whitepaper are intended to help others address the challenges presented by opaque or illiquid alternative investments. Specifically, the paper posits the view that investors should use the most granular detail available to evaluate investment risks. Obtaining position-level information for all asset classes is the gold standard. They are also encouraged to consider hedge fund structures that can provide position-level transparency, liquidity and control and explain that dedicated managed accounts and liquid alternative funds are increasingly popular structures that offer such features.
Many firms are establishing a chief risk officer function to supplement their risk management responsibilities. The bank says this new role requires a significant amount of data to allow investment risks to be evaluated across all asset classes. Moreover, if a firm is using a single vendor to pull together an institution’s total investment data it enables a more uniform approach in calculating enterprise-wide risk and exposure, whereas data across multiple platforms can add to the complexity of analysis and introduce the likelihood of errors.
As well, firms are encouraged to evaluate volatility-based measures like Value-at-Risk (VaR) as just one element of a broader risk management framework that considers other factors such as exposure as well. VaR is an estimate that is more useful in relative analysis than as an absolute value. BNY Mellon encourages investors to compare VaR of a total fund over time to help identify changing market conditions, or compare VaR of a single portfolio relative to an asset class, total fund or benchmark to gain insights into how components interact within an overall investment program. Investors are also encouraged to consider VaR for portfolios relative to the total composite, as a benchmark, or over time, rather than as an absolute value.
The paper says investors should compare ex-ante risk measures to ex-post risk measures. Illiquid investments will show lower ex-post risk statistics based on observable quarterly returns than ex-ante risk measures using daily-priced market index proxies based on relevant factor exposures. Volatility based risk measures for illiquid investments will tend to understate the risk of losing money if compared to volatility measures for liquid investments.
The paper explains that already some regulators require reports on stress testing and scenario analysis, such as through Form PF for US investment advisers to hedge funds, and pursuant to Solvency II for insurance companies, and UCITS for European investment funds, Barney adds: “We’ve learned the most crucial component is the veracity of the underlying data, which becomes even more important and difficult to manage as more opaque assets are held in the portfolio.”.