Gautam Batra is head of Investments at Mediolanum Asset Management.
Every financial era gives rise to its own investment style, the one thought to be best suited to the prevailing market conditions. In the Seventies, hedges against inflation – whether real estate or fine art – were much in demand, while the early years of this decade saw a “hunt for yield” in a changing interest-rate environment.
Since the financial crisis and the subsequent official actions to support economic activity, the passive investment style has seemed to many to meet the needs of the time. Monetary policy, remarkably accommodative by historical standards, has fostered a low-volatility environment in which index tracking has flourished.
Such low volatility makes it more likely that yesterday’s winners will still be on top tomorrow, thus the bias inherent in passive investing towards the success stories of the past is less problematic. Add in continuing criticism both of the fees charged by active managers and their sometimes-underwhelming performance, and the factors have been in place for something of a boom in passive investment strategies.
But no set of conditions lasts for ever, and there are signs that key features of the post-crisis financial era will not be with us in their present form for much longer.
Specifically, the need for quantitative easing (QE) on the scale of which it has been practised is weakening. The United States is proposing to begin unwinding its stockpile of assets, and there are signs that the European Central Bank (ECB), a relative late-comer to the QE party, may trim its asset-purchase programme.
As monetary policy becomes less accommodative, volatility is likely to return to markets. Such a return could have a chilling effect for passive-investment strategies. We believe that we are approaching an inflection point, after which the case for active management will likely strengthen.
As volatility becomes a more prominent factor in the market, so the rationale behind tracking the market – in effect, buying yesterday’s winners, investing in everyone else’s previous investments – will fade.
Within active management, we believe that the industry will see less of a divergence between quantitative investing and fundamental investing. We believe that a third way has begun to emerge.
This approach is called “quantamental”, a portmanteau word created by joining the “quant” of “quantitative” investing with the back half of “fundamental”. Quantamental combines two types of investment strategies.
Quantitative investing utilises complex algorithms, significant amounts of data and large computer systems to invest in securities or determine asset allocation decisions. Fundamental investing relies on the analysis undertaken by the fund manager with regards to the underlying forces that can help to determine the wellbeing of companies, sectors and economies.
By combining the fundamentals of quantitative investing with the expertise and experience of the fund manager, quantamental investing seeks superior returns, not least through the reduction or elimination of behavioural biases in the investment process.
For a quantamental approach to succeed, a significant proportion – perhaps 10 per cent – of the asset-manager’s staff ought to be trained in data science, capable of analysing ‘big data’ and sharing insights in such a way as to derive the full benefit across the business.
It is vital that these data experts are not shut away in the IT department but deployed in all roles, and embedded in areas such as product development, portfolio and risk management.
Following on from this, the quantamental approach will have at its heart a structured, disciplined, yet flexible investment process. This is designed to analyse markets, sectors, economies and trends in a rational and objective way.
Hand-in-hand with the investment process ought to be a risk-budgeting framework, which informs the risks that are being taken on at each stage of the investment process relative to a defined objective.
It may be thought that this process is all very well in-house, but what happens when a quantamental investor engages with external managers, through a fund-of-funds product, for example? Are these external managers beyond the control of the investor?
In such cases, it is important to have a robust manager selection process. For example, analysing a consistent historical record of investment decisions made by a potential target manager helps identify whether those decisions were in accordance with the stated investment process and how they have impacted investment performance.
This rigorous scrutiny of the external manager’s investment process helps ensure the manager is behaving as would have been expected in various market conditions and also helps recognise any inherent behavioural biases.
Biases creep into investment decisions when managers buy on the basis of “how they feel” and “drift” from their investment process. Scrupulously following the investment process should screen out such biases. This is what has been described as cognitive optimisation: delivering better results based on clear thinking grounded in a disciplined framework with a data driven feedback loop to refine the investment process.
The market environment is changing, with the gradual withdrawal of monetary stimulus likely to lead to a fresh appreciation of the benefits of active investment. Within active management we believe that quantamentalism, which blends the big data insights of quantitative investing together with the expertise of the fund manager, can offer the best of both worlds and deliver better performance with improved consistency.