For investors who are unsure of what side to come down on in the active versus passive debate, the team at Orbis believes it has developed a solution – “Quantamental” stockpicking, which aims to offer investors the best of both worlds.
Passive investing is able to keep costs low as it relies on an algorithm to do all the work. Active investors, meanwhile, argue that there are many qualitative attributes that a computer cannot spot – for example, in a recent article on FE Trustnet, Artemis’ Simon Edelsten said excluding industries with low barriers to entry is the most obvious first step for an active manager to take.
However, Orbis – which only charges investors when their fund outperforms – has combined technology and human decision-making in its ‘Quantamental’ technique. “The real benefit [of this technique] lies in the combination of quantitative insights and fundamental research working together,” said Claire Gallagher, a quantitative analyst at Orbis.
“Machines are unemotional and can process large amounts of data, whilst humans are good at creative problem solving and applying sound judgement in a wider range of situations.”
The word quantamental is a contraction of the words quantitative and fundamental.
Fundamental analysis focuses on a limited number of companies, often in a given sector, and a set of related economic and financial factors and characteristics. However, its success depends on the analyst’s knowledge of the particular company or sector.
The quantitative technique, on the other hand, can process a huge quantity of data using a number of criteria, to pinpoint stocks that present alpha-generating attributes. This approach is based on a mastery of statistical and econometric techniques and can help identify factors that promise excess returns within the acceptable risk parameters.
“We leverage technology to make better bottom-up decisions on individual stocks,” Gallagher said.
“This includes screening for attractive investment ideas based on our proprietary valuation models, portfolio construction and risk management, and performance analysis.”
“The technology and quantitative tools allow us to be efficient with our time and rigorous in our analysis, and the fundamental work helps us develop a deep understanding of each individual business in the portfolio.”
By breaking down the investment process and evaluating decisions at each step, Gallagher said the team “can provide an enriched feedback loop for our analysts and portfolio managers to better understand their behavioural biases”.
The analyst admitted that, like any investment approach, quantamental is at risk of being wrong and losing investors money. However, she said it strikes a good balance between a purely quantitative approach that may rely too heavily on numbers alone and a purely qualitative approach that may rely too heavily on the story.
She added that looking at shares from both quantitative and fundamental perspectives helps the team to stay focused on the most important information, allowing it to make better decisions.
However, she said that while looking at fundamental and valuation metrics is vital when assessing a portfolio’s return prospects, when assessing a portfolio’s risk, it is vital to look at another angle: how the holdings behave compared with each other.
As a result, the team developed a behavioural map that uses a machine learning technique to visualise relationships between stocks, allowing the analysts to quickly assess their historical behaviour.
Source: Orbis
“If two stocks appear close together, their prices move together, and if they appear far apart, their prices move less similarly,” Gallagher explained.
“Don’t worry about whether a stock is high or low on the map, or towards the left or right. The absolute location doesn’t matter.”
“All that matters is a stock’s distance from other stocks. The reddish stocks in the Japan cluster, for instance, broadly hang together, but behave completely differently from the green shares in the South Africa cluster.”
The dots aren’t randomly spread about, but tend to clump together. Gallagher said this is because if the team finds one stock attractive, it will often find its peers interesting as well.
One example of this is in the tech sector in the emerging market funds, with a strong correlation between companies that are not even listed on the same continent. “Although Naspers is listed in South Africa, most of its value comes from the Chinese internet company Tencent Holdings, and that is reflected in how its share price moves – the two stocks, along with NetEase, behave very similarly,” the analyst added.
She said this shows the importance of the quant tools, as while a top-down investor may treat the names above as simply ‘emerging market stocks’, the map shows that they behave nothing like the emerging markets index.
The same could be said about Japan.
“Our selected value shares shown move together and differently from other shares in Japan and globally,” she said. “And in the US, our favoured biopharmaceuticals AbbVie and Celgene are next-door neighbours, but their behaviour is quite distinct from that of, for example, XPO Logistics, which is also in the US.”
Gallagher said the quantitative perspective proves that the portfolio is not taking one big bet, but many smaller bets: “attractive individual stocks, some in clusters, that have emerged from our rigorous fundamental research”.
“Yet they do have one thing in common: in our view, every one of them offers an attractive discount to intrinsic value,” she finished.
Performance of fund vs sector and index over 10yrs
Source: FE Analytics
Data from FE Analytics shows the Orbis Global Equity Standard fund has made 247.35 per cent over the past 10 years compared with 272.81 per cent from the MSCI World index and 205 per cent from its IA Global sector.
The £71m fund charges 50 per cent of any outperformance of its benchmark, which is refundable at the same rate on any underperformance. It has no ongoing charges.