Enhanced index strategies are designed to deliver consistent outperformance with limited surprises, but achieving that in today’s markets requires a more adaptive approach to risk, says Anthony D’Silva, Senior Quantitative Investment Manager at Aberdeen Investments.
Enhanced index strategies have grown in popularity as investors seek sources of enhanced returns with few strategic surprises. Of late, however, markets have proved to be anything but stable.
From Russia’s invasion of Ukraine in 2022 to Trump’s 2025 Liberation Day tariffs, they have had to process a highly unpredictable macro and geopolitical backdrop which has influenced investor sentiment and the direction of capital flows.
The ongoing conflict in the Middle East, which still seems far from a resolution, is a case in hand.
The closure of the Strait of Hormuz and fears of a contagion of conflict across the region have had a profound effect on global trade, heightened uncertainty, increased volatility, and sharpened sensitivity to energy, inflation and interest rate expectations.
A key appeal of enhanced index strategies is their strategy to harnessing the power of data and technology to apply disciplined and well-established investing concepts and remove human emotion at times of market duress.
By making small, systematic bets they aim to outperform standard index trackers while avoiding additional risk.
However, while extreme geopolitical and macroeconomic events may historically have been considered extraordinary, a cursory review of crises over the last decade would suggest that they are much more commonplace.
Investor assumptions simply cannot keep pace with this constantly evolving market mood music. Markets change shape quickly, factor leadership rotates and macro conditions turn without warning.
This means that a portfolio that is well-balanced in one environment can become misaligned in another.
When markets are in a state of flux, risk management must be equally dynamic if an enhanced index portfolio is to remain on track to deliver on its projected outcome.
But how is this achieved by systematic investing where human input is minimised? As its name suggests, dynamic risk management operates continuously in the background, adjusting exposures as markets shift so that they remain intentional, rather than consequential. This steadily applied discipline is as important as any single signal or factor model.
There are several ways in which a dynamic framework can help keep portfolio risk in check.
First, it can refresh risk models in response to any change in cross-sectional patterns; it can recalculate exposures to differing factors as fundamentals shift; it can review portfolios for any unwanted or unintended concentrations in sectors, themes or styles; and it can take into account the speed with which the macro environment is changing.
While it cannot predict market inflection points, it can help ensure that portfolio positioning is not reliant on stale information.
Systematic investing still requires a level of oversight since market signals can steer a portfolio optimiser towards exposures that may look reasonable on the surface but may be misguiding in reality.
Value signals, for instance, can cluster in inflation-sensitive sectors during uncertain macro conditions while momentum can attach itself to short-lived investment trends that can inflate active risk.
Dynamic oversight identifies when these influences begin to build by monitoring short horizon return data for shifts in dispersion, correlation and sensitivity to macro or geopolitical news.
The intention is not to override the systematic process, but to shape the final portfolio into something that reflects the underlying philosophy rather than a temporary market quirk.
Differing systematic investment strategies reference differing factors as part of portfolio optimisation. However, what all strategies have in common is a limited risk budget as they seek to operate within modest tracking error ranges.
Dynamic controls impose explicit constraints on economic rationales that systematic investing references as part of the optimisation process.
These rationales will vary from one firm to another, but by way of example, we focus on three key factors that influence the scores which we attribute to every stock in the market: Valuation, Quality and Momentum.
Dynamic controls aim to neutralise unintended exposures without diluting these three factors and help ensure the risk budget is spent wisely.
The controls applied include identifying exposures that arise unintentionally from the intersection of equity factors and short-term macro, geopolitical and thematic risk factors and balancing risk across Value, Quality, and Momentum so no single factor dominates.
It also involves maintaining realised tracking error close to its target even when volatility or correlations shift. This protects the portfolio from drifting into areas that add noise rather than return.
While the adjustments driven by dynamic risk management are typically relatively modest, in aggregate they can help smooth the investment journey and create more consistent performance over time.
This is achieved by the avoidance of unnecessary losses when a factor weakens, the reduction of slippage by monitoring turnover and liquidity, and maintaining alignment with intended style exposures.
The recent conflict in the Middle East is a good example. Markets initially moved into a classic risk-off mode, with defensive stocks outperforming, before sentiment recovered as concerns about a broader escalation began to fade.
The challenge was that traditional risk models were slow to reflect to how quickly market relationships were changing.
Rather than relying solely on standard factor models, we incorporated a bespoke conflict factor using short-term market data to better capture what was driving returns. We then assessed how that exposure interacted with our existing Value, Quality and Momentum factors, and whether it was becoming a meaningful contributor to portfolio risk.
Where it was, we acted. We introduced targeted constraints to reduce the unintended exposure while preserving the integrity of the multifactor process.
The objective wasn’t to change the investment philosophy, but to ensure the portfolio remained aligned with it. Value, Quality and Momentum continued to drive stock selection, while dynamic risk management helped keep the portfolio on course through a rapidly evolving market environment.
Markets today face considerable pressures. Flows into passive investments are strong and sentiment towards differing themes can swing dramatically while geopolitical events impact once stable sectors.
Against this backdrop, static assumptions are no longer robust. The appeal of enhanced index strategies lies in their potential to deliver consistent outperformance with minimal surprises along the way.
This requires a process that adapts as the market evolves. Dynamic risk management provides exactly that, by keeping the portfolio intentional, and ensuring the optimiser remains aligned with the underlying investment philosophy.
For professional investors only.
Past performance does not predict future returns. The value of investments, and the income from them, can go down as well as up and clients may get back less than the amount invested.
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