Sections

Fluid and dynamic

Related Categories

Quantitative equity fund management is a relatively new investment style that has seen remarkable growth in the last few years. Quantitative portfolio management is using systematic and disciplined investment processes to select stocks and make asset allocation decisions. It is simply the rigorous and disciplined implementation of a fundamental strategy (eg, value, momentum, quality) often in a risk-controlled fashion. The central theme of quantitative investing is that history reveals enduring patterns of price behaviour, which can be unlocked by statistical techniques. In addition quantitative analysis aims to explore various stock market inefficiencies and anomalies that have been created by noise trades and less well-informed investors.
Whereas mathematics and statistics have been widely used in fixed income, basic quantitative tools and techniques have only recently been employed in equity portfolio management. These techniques have been used primarily to manage risk and less so during the return enhancement process. In the 1990s most quantitative analysts were mainly concerned with either monitoring the risk of active portfolios, calculating the marginal contribution to risk for each position held by the fund managers or constructing portfolios to mirror the top-down views of fund managers. Some quantitative tools were also used in performance attribution and style analysis of portfolios. In terms of fund management, quantitative investing was simply synonymous with indexing or enhanced index management. Active fund management using quantitative techniques and a model-driven investment process was rather limited in Europe in the late 1990s.
The focus of quantitative input in the equity investment process seems to have changed in the last three years or so. With the markets being very volatile and in a prolonged bear phase and with investors having less obvious opportunities for return enhancement, fund managers start searching for alternative ways to manage portfolios. As a result the process of selecting stocks and deciding on portfolios’ active positions has clearly been more systematic and rigorous. Apart from the desire to try something different, a number of other factors have contributed to this trend.
Increasingly market practitioners have recognised that the market is becoming too complex and relationships between financial variables are not straightforward and linear. Also, with information disseminating faster to market practitioners and the market becoming more efficient investors are faced with fewer obvious arbitrage opportunities. In today’s market, patterns in financial trading data represent arbitrage opportunities that are too subtle for human analysts to detect. The use of technology and systematic quantitative research is therefore becoming essential.
Faster computers, user-friendly software tools and databases with a long history of financial variables have made quantitative analysis of securities easier in the last few years. The sheer volume of data that investors are bombarded with can now be easily analysed with the power of the technology. Investors also every year have more access to information, which increases their ability to make meaningful comparisons.
Investors have also come to realise that emotions should not be involved in investment decisions. Equity investment is not just art but science as well and leaving investment decisions completely to human judgement could lead to irrational behaviour. These behavioural factors could explain a number of inefficiencies we observe.
The need of institutional investors to cut costs and reduce equity research budgets in this challenging and increasingly low-margin environment is another reason that could justify the growing demand for quantitative analysis. Whereas fundamental analysts can cover only a dozen securities, quantitative research analysts using the appropriate technology can cover the entire spectrum of stocks within the market or a particular sector.
Regardless of the driving factor, quantitative analysis has been an integral part of the investment process of many fund management institutions in the last couple of years. Quantitative research departments at investment houses are growing in size and are being allocated more resources. At the same time quantitative analysis is available to portfolio managers via independent software companies and brokerage firms. Access to quantitative tools and analysis is now easier than ever. Quantitative tools are now helping even traditional stock pickers to screen for stocks, find out which style factors are more correlated with stock returns, and explore the sensitivity (or beta) of stocks to macro factors such as currency, inflation or long rates, etc.
Even more interesting, however, is the growth of dedicated quantitative fund management in Europe in the last few years. Whereas some institutions use quantitative analysis to assist in the design of the investment process, some others have gone a step further and are actually offering quant funds as part of their product portfolios.
The majority of the quant investment processes in the European marketplace tend to be multi-disciplined, ie, they rely on a combination of investment styles and factors, not just value or growth or momentum.
In most cases quant funds attempt to add outperformance within a small tracking error budget and by taking small-size bets in many securities. As quantitative managers do not care about understanding the stock-specific drivers of the companies they include in their portfolios (eg, quality of management, litigation costs, business strategy, etc) they are exposed to stock-specific risk. One of their primary concerns therefore is to diversify this risk. Quantitative portfolios tend to be less concentrated compared with traditional funds with the majority of their risk coming from systematic risk factors.
Finally, many quantitative fund managers tend to run money using a sector neutral strategy. In other words, they try to select the best stocks within each sector and avoid overweighing one sector against another.
In Europe the trend has only recently emerged and is obviously lagging many years behind the US. Apart from a few specialised small-size institutions or boutiques that manage money purely with quantitative techniques, there is only a small number of players competing in this area. With the exception of the big, traditional index player with many years of experience in quant investing, a few conservative old-fashioned fund management houses have recently been diversifying their product mix, offering quant portfolios to their clients. The majority of dedicated quant funds can be found in the Netherlands and in France with a few funds being set up in the last couple of years in the UK and Germany. A few other quant funds can also be found in the form of hedge funds. These are normally more sophisticated and their investment process is less transparent.
Despite the relatively good performance of quant portfolios in the last few years, the quantitative investment style is not infallible. As with most disciplines and investment strategies implementation is very important. Not all quant techniques and strategies are able to add value and lead to good performance. There are many examples of unsuccessful attempts to run equity portfolios using quantitative techniques. Emotions are not always kept out of the quantitative investment process and tests are often not objective but biased. Some not very successful quantitative investment strategies are simply based on data mining and not on sound financial theories and academic evidence. In my view the best quantitative fund managers should always try to reinvent themselves, discover new areas of inefficiency in the market and new statistical techniques to explore relationships between stock returns and financial variables. Quantitative investing should not be static but very much a dynamic and evolving process.
Manolis Liodakis is a managing director in the European Equity Research Department of Citigroup, in London. The views expressed in this article are the authors own and not necessarily those of Citigroup

Have your say

You must sign in to make a comment

IPE QUEST

Your first step in manager selection...

IPE Quest is a manager search facility that connects institutional investors and asset managers.

  • QN-2467

    Asset class: Search for a broker (mainly ETFs).
    Asset region: Global.
    Size: 250m.
    Closing date: 2018-08-28.

  • DS-2468

    Closing date: 2018-08-24.

  • QN-2469

    Asset class: All/Large Cap Equities.
    Asset region: Global Emerging Markets.
    Size: USD 500m.
    Closing date: 2018-09-04.

Begin Your Search Here