How many different ways must there be for an asset manager to invest client money in stocks, bonds and other financial instruments, and to consistently make good returns on those investments?
“The possibilities are endless,” says Raul Leote de Carvalho, deputy head of the Quantitative Research Group. “That’s why it makes sense to apply scientific methods to the investment problem. The objective is to make decisions based on quantifying the impact of all relevant information on expected returns and risk, not on hunches.”
Such, in a nutshell, is the strategy followed more and more today. Known as quantitative finance, the fast-growing discipline involves the use of mathematical models and increasingly larger sets of data to analyse financial markets in order to target and price good investments more accurately, and to reduce risk in the process.
Quantitative finance addresses the investment ‘problem’ in three steps, says Leote de Carvalho.
This meticulous method sets quants, as practitioners of quantitative finance are known, apart from their more traditional asset management counterparts who tend to addresses the ‘problem’ with more judgement.
This can be based on their expectation of a company’s earnings and revenues, growth potential, or their appreciation of the business case and the management team.
“Both investment methods are effective in their own ways,” says Leote de Carvalho. For example, he notes that quants’ use of massive computing power enables them to process vast amounts of data on thousands of financial assets at a time, daily if needed.
They can simultaneously forecast asset attractiveness and propose solid investment portfolio opportunities.
Non-quant asset managers require time to research each individual asset. On the other hand, they can and often do take into account less quantifiable, but relevant types of information that quants would not necessarily consider.
The combination of quantitative and fundamental methods – a technique known as quantamental investing – can prove particularly effective in building a fruitful portfolio.
Another distinction between the two methods is that quants are much less likely to be affected by emotions. Leote de Carvalho explains: “All fund managers are human, but when you delegate the management of assets to models built rationally, the resulting investment decisions are considerably less influenced by human biases such as over-confidence, fear, excitement, empathy or intrigue.”
To illustrate his point, he notes that as a confirmed quant, he would be subject to the same behavioural biases that affect everyday investors. “I am forbidden by the rules of my profession to invest in individual companies, but if I weren’t, I might well be persuaded to invest in a particular company I accidentally hear about, while ignoring the vast amounts of information that exist about this company and about all other companies competing with it.”
“That’s the interest of quantitative finance,” Leote de Carvalho continues. “We can all get taken in by the charm or persuasiveness of a charismatic company CEO, for example, but nobody can persuade a model to invest if those values haven’t been built into it.”
So persuasive is the science of quantitative finance that in 2017, BNP Paribas Asset Management established the Quantitative Research Group, bringing together a number of quants already at the company, but spread among different departments, and hiring highly qualified quantitative finance experts from outside the company.
Today, the QRG team has 28 specialists based in Paris, London, Amsterdam and Hong Kong, who work to supply quantitative inputs and tools to investment teams across the company.
“We’re here not only to help quantitative investment teams who rely solely on quantitative finance to invest, but also to help the fundamental investment teams, by adding a layer of discipline to their decision-making. This is the case in particular when they are faced with large investment universes.”
Leote de Carvalho points to the global stock universe, which includes some 2 500 large and mid-sized companies. “An investment team would need a lot of people to analyse all those companies and come up with a viable investment strategy. We can use quantitative methods to winnow out the weaker companies, providing a pool of fewer, but more promising opportunities.”
Once the Quantitative Research Group has helped investment teams decide which assets to buy, it helps them decide how much of each asset to buy in the portfolio construction process.
“These decisions can be critical to a portfolio’s ultimate performance,” says Leote de Carvalho, “in particular to manage different types of constraints on investing, to minimise the impact of transaction costs, or to make sure that the maximum risk tolerance is not exceeded.”
And that’s just the beginning… Raul Leote de Carvalho and the QRG team have all kinds of tricks up their sleeves – to be revealed in other articles such as Just what the doctor ordered.
Any views expressed here are those of the author as of the date of publication, are based on available information, and are subject to change without notice. Individual portfolio management teams may hold different views and may take different investment decisions for different clients. This document does not constitute investment advice.
The value of investments and the income they generate may go down as well as up and it is possible that investors will not recover their initial outlay. Past performance is no guarantee for future returns.
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