What is quantitative investing?
Quantitative investing refers to rules-based strategies that build portfolios using mathematical models, statistical analysis and data-driven techniques.
Portfolio managers and traders who use quantitative investing approaches often harness powerful computers, algorithms and big data to capture investment opportunities that might otherwise be unavailable.
By contrast, traditional forms of active investing rely on human judgement, knowledge, experience and research to make investment decisions. Quantitative professionals, or ‘quants’, call this the fundamental discretionary approach.
Quantitative strategies employ an automated framework that directly translates investment research into portfolio positions. This allows for a clear relationship to be developed between portfolio positioning, portfolio risk and portfolio outcomes.
In an efficient quantitative investment process, risk management is the final key component to ensure that risk and return are derived from the portfolio shape suggested by the manager’s research process.
Sean Phayre, PhD, Global Head of Quantitative Index Solutions, abrdn
Systematic investing, which is a type of quantitative approach, removes human bias and emotion from the portfolio construction process. This prevents the portfolio from deviating significantly from the investment strategy and focuses it on intended sources of risk and return.
Types of quantitative investment strategies
The rules-based nature of quantitative investing means that it encompasses a vast array of strategies. Increasingly, these rules may involve artificial intelligence (AI) or machine learning, while others utilise alternative data sources, such as social media trends or investment factors that assets may be exposed to. Below, we expand on a few types of systematic approaches.
Passive index strategies are designed to track the performance of common market indices, such as the S&P 500 US stock market index. They seek to minimise the difference between a fully replicated index (the ‘ideal’ portfolio) and the most efficient investible portfolio, based on minimising constituent trading, relative risk and transaction costs.
Passive index funds carry some degree of ‘tracking error’ – in other words, their performance may slightly deviate from the benchmark index’s due to trading costs or liquidity constraints. Quantitative, systematic techniques provide a comprehensive analysis of the index to reduce these issues and more accurately replicate the benchmark’s performance.
Enhanced index strategies often harness what are known as ‘factor’ investing techniques and seek to outperform a benchmark index by ‘tilting’ (or adjusting) their exposure to underlying constituents.
A fund may allocate an overweight or underweight position to an individual security based on quantifiable factors, such as size, value, quality, momentum, and volatility. These factors can play a significant role in short-term performance – for instance, depending on the prevailing market environment, a fund may benefit from having either more or less exposure to volatility than the benchmark index.
The intention is that the fund adapts to different stages of the market cycle, which could potentially lead to long-term outperformance.
Sustainable index strategies, a more recent development, follow a similar approach by tilting (or sometimes excluding) constituents according to sustainability factors, such as a company’s carbon intensity or ESG scores.
These strategies are typically designed with specific sustainability objectives or metrics in mind – for instance, keeping the portfolio’s overall carbon intensity at least 50% below the standard market-capitalisation index, while maintaining a risk-aware stance against the mainstream index.
The advantages of quantitative investing
Systematic – by removing discretionary human decision-making from the portfolio construction and maintenance processes, a quantitative fund can follow the investment strategy with 100% consistency.Although fundamental discretionary approaches often adhere to investment rules, they are generally exposed to some degree of bias or emotion. Furthermore, systematic solutions are more capable of applying rules to manage increased market index concentration, whether transient or permanent. A recent example of this is the ‘Magnificent 7’ phenomenon in the US. Discretionary processes are less well-equipped to manage such concentration risks in a timely manner.
The rules of a systematic process are designed to ensure that guardrails are in place to maintain a consistent risk profile at all times. Additionally, regular rebalancing is often a feature that ensures buy-sell discipline is adhered to and the portfolio is systematically refreshed while controlling turnover. Consequently, positions are increased or decreased in reaction to ensuing market dynamics, and the impact of concentration is largely dissipated.
Diversification – by focusing on multiple factors, such as those that occur at different stages of the market cycle, an enhanced systematic fund can arguably better diversify against macro and geopolitical risks than is afforded by a fundamental discretionary management process or indeed a traditional passive index tracker.
Cost-effective – systematic funds provide cost-efficient access to regional and global equity markets.
The drawbacks of quantitative investing
Quantitative strategies are only as good as the data and the factor-based models they rely on. If the factors are based on erroneous data, or the data has been misinterpreted, the models will provide false signals on the direction of securities.Additionally, factor models cannot fully explain the performance of financial variables, and there may be other significant influences over the direction of financial assets. These models often require significant amounts of information and, in some cases, only limited amounts of historical data may be available.