Measuring moving targets
Increased volatility in equities, greater diversification and investment in more exotic and complex asset classes are reasons often given for the ascendancy of risk measurement and management solutions. There is no shortage of tools to tackle risk but the latest changes have lead many large consultants, managers and risk specialists to reconsider existing products or launch more complicated solutions. Much emphasis is placed on tracking anomalies, or at least trying to understand them, and on producing decent measures with which to compare funds. There is also a shift to a more micro approach to risk analysis, breaking down the investment process step-by-step.
Edinburgh-based investment manager Standard Life latest quarterly report says traditional methods of controlling investment risk have recently understated risk. Head of Strategy Ken Forman says one of the key assumptions backing tracking error theory - that asset returns are normally distributed- is invalid. The recent, well-publicised volatility in technology stocks over has blown many index-based comparisons out of the water- tracking error is a historical concept and the wild fluctuations simply didn’t fit many underlying assumptions.
Standard Life says overreliance on computer models can do more damage than good and in response is changing its risk management approach. Its latest research looked at so-called ‘fat tails’ of equity returns- in other words the two extremities of the distribution- and witnessed an alarming growth in ‘bombs’- equities suffering serious falls, and ‘rockets’- equities leaping in value. “This does not make tracking error theory itself redundant, rather, it strengthens the case for a multi-tool approach particularly given the extreme market conditions we have witnessed in the last year or so,” says Forman. In response the company has modified its computer models for current market conditions and introduced tools that can spot emerging trends in markets with minimal lag. At a more micro level, it has also provided its fund managers with systems that trace the risk within their portfolios.
Other feel the same and have extended their products’ scope. performance measurement and analysis firm The WM Company say trustees believe return data for their pensions is insufficient to gauge risk.There is increasing pressure for more detailed analysis of investment risk to supplement basic investment returns. In response, WM Company and risk specialists Barrie & Hibbert have developed what they have dubbed the relative risk service to tackle investment risk. The package helps trustees understand the risks managers are taking, identifies to what extent risks are rewarded, reduces shocks by predicting underperformance and emphasises the appropriate risk necessary to achieve set targets.
As with many approaches, a relative risk report breaks down the investment process. First there’s a summary allowing you to monitor the relative long term performance of the fund. Policy weightings allow a comparison of your asset mix with that of similar funds. There are then three sections on returns and risk from policy decisions, stock selection decisions and asset categories, each allowing further comparison. Finally, a section on prospective risk shows future risk faced by your fund relative to others and highlights the worst culprits.
Eric Lambert, executive director at WM Company says it’s necessary to look at the distribution of monthly returns along with return over the three year period to get a comprehensive measure of performance. “It is useful, for example, to know what the maximum and minimum monthly returns were or how many returns were less than the benchmark return,” he says.
State Street’s Askari Risk Management Solutions already offers numerous risk management tools and one of particular interest is TruView, a system it claims is the first risk management approach designed exclusively for asset managers. Askari cites increased diversification into more complex and less traditional asset classes as the rationale behind the product. Askari recognises many markets are more complex with non-normal returns, non-linear instruments and unstable correlation longer have normally distributed returns. TruView models normal market behaviour as well as the fat tails (also cited by Standard Life) that they say are increasingly the source of underperformance for aggressive investment strategies.
Northern Trust Risk Services, a division of Northern trust, and RiskMetrics, the risk measurement specialists, recently launched PensionMetric Risk Universe, a similar service allowing institutional investors to compare their risk profile with other similar funds. Each calculation is a value at risk (VAR) calculation for a plan’s overall risk, highlighting predictive risk for various confidence intervals and time horizons. Says Ravi Gautham, vice president of Northern Trust Risk Services, “The Universe allows sponsors to quickly get a feel for how the risk of their program compares to their peers , and it will enable them to make more informed investment decisions.” Don Rieck, vice president and manager of Northern Trust Risk Services, says increased volatility and a broader range of market exposure means institutional investors need to concentrate on the risks associated with their investment program.
Northern Trust has a strong partner in RiskMetrics. JP Morgan set the company up in 1994 and it already offers numerous risk management products. RiskManager (RM) is a stand alone application used to measure and analyse market-based value at risk. RM uses Monte Carlo, historical and VAR methods along with stress testing to give institutional investors a full breakdown of risk. JP Morgan recently contributed to a $22m private equity investment that RiskMetrics says will help develop its RiskGrades program, a measure of volatility for an individual asset or portfolio of assets.
Also under development is consultant Bacon & Woodrow’s simulated investment analysis, or Simian, which breaks down fund managers’ portfolio construction and measures the skill associated with each step. “It’s a risk and performance attribution tool but very much looking at exactly how a particular fund manager is putting together portfolios,” says Sally Bridgeland, partner and head of investment research at Bacon & Woodrow. “In terms of risk management, what it also demonstrates is the range of results that the manager could have got- whether they were being skilful or not- so you can really see the risks that are inherent at each step of the process,” she says. Simian creates an artificial peer group by taking thousands of simulations based on random samples for other managers. A manager’s performance is thereby put into some kind of context.
Germany’s RiskLab takes a slightly different approach to risk. The private research institute was launched three years ago as a subsidiary of Allfonds International Asset Management. With partners HypoVereinsbank and associations with universities its approach veers to the theoretical. Its Interest rate manager produces a current value and risk analysis of your portfolio in terms of possible changes in interest rates. A risk optimiser then makes suggestions for tailoring a portfolio to a specified risk structure. More specifically, the system, like many others, uses scenario-based ‘what if’ analysis, stress testing and VAR.
Some remain unsatisfied though, criticising existing systems as inadequate. Recognising the non-linear nature of returns and breaking down the investment process makes sense but claiming risk management is more pressing due to greater volatility, a reason often listed, might perhaps be ironic. Now comes Avinash Persaud, managing director of global trading and research at State Street, with an award-winning essay suggesting market-sensitive risk management systems can actually promote market instability*. His thesis is simple but compelling. The latest fashion in risk management, and one supported by the Basle Committee on Banking Supervision, is a move from discretionary judgements about risk to a more quantitative, market-sensitive approach.
This is demonstrated by banks’ penchant for managing market risk by making a DEAR (daily earnings at risk) setting- one calculated by taking the bank’s portfolio of positions and estimating the future distribution of daily returns based on past measures of market correlation and volatility. DEAR suggests an amount the bank is prepared to risk losing with an X% probability. Market participants behave strategically in relation to one another whereas DEAR measures risk strategically and without strategic considerations. Persaud says there’s growing evidence of herding within market places- the best way of exploiting others’ information is mimicry and managers are often measured and rewarded by relative performance so it pays not to stray too far- so the argument goes.
“In a world of herding, tighter market-sensitive risk management regulations and improved transparency can, perversely, turn events from bad to worse, creating volatility, reducing diversification and triggering contagion,” says the essay. Stress testing as a means of alleviating this contagion also comes in for criticism as past crises (the most common test) are never repeated identically. Persaud admits it is hard to estimate the spread and depth of positions or the impact on liquidity and hence potential losses. Risk managers are too prone to concentrate their efforts on quantifiable opposed to unquantifiable risks and, the paper concludes, “the whole concept of market-sensitive risk management practices needs reassessing in the context of herding”. IPE
*Sending the herd off the cliff edge: The disturbing interaction between herding and market-sensitive risk management practices.