The objective of Lazard’s investment process for its flagship Global Equity Advantage strategy is to maximize exposure to the most attractively ranked securities subject to strict risk controls on sector, beta, capitalization dispersion, and position size.
“Performance is driven by bottom-up stock selection, which builds core portfolios that avoid biases toward any specific style, capitalisation, geography or sector,” said Antony Creighton, director, head of strategy (Asia ex-Japan) at Lazard Asset Management.
“The investment process is enhanced through a continual quantitative research effort, which has generated consistent excess returns in most market environments,” he told FSA.
The Quantitative investment team at Lazard believe that inefficiencies in equity prices exist as a function of investor emotion and bias. These inefficiencies can create investment opportunities because the market misprices companies based on a combination of their intrinsic worth, growth potential and financial quality.
“These core beliefs are well supported by our own research and numerous academic papers,” said Creighton (pictured).
Moreover, a strategy managed against a large, well-diversified benchmark can produce consistent excess returns over time. By managing a broadly diversified portfolio controlled to the client’s benchmark, a portfolio is constructed with a focus on many small investment decisions. It is designed to be biased toward lower valuations, higher growth and quality measures compared with the benchmark.
“We also do not believe in making large binary decisions such as growth versus value, because such decisions are difficult to predict with a high degree of consistency. Similarly, we see little benefit in attempting to time the success of each factor based on the investment environment,” Creighton said.
Strong performance
In fact, Lazard’s quantitative approach has delivered excess returns in most market environments over the past 20 years, according to Creighton.
For its Global Equity Advantage strategy, the upmarket capture ratio is 1.02 over the 16 years since its inception on 1 January 2008 with downside capture at 0.96 showing that it typically outperforms rising and falling markets.
It also has lower drawdowns than the market during significant declines. For example, over the past 10 years to 31 March 2025, the maximum drawdown was 23.2% (during the market declines in 2022) versus the MSCI World benchmark drawdown of 25.4%.
Similarly, during the years when the benchmark was up substantially, the Lazard Global Equity Advantage strategy has tended to beat the market. For example, in 2021(benchmark +21.8%, strategy +26.7% gross); 2023 (benchmark +23.8%, strategy +25.5% gross) and 2024 (benchmark +18.7%, strategy +22.3% gross).
In current market conditions, it is impossible to predict performance, but Creighton is confident that Lazard’s quantitative team’s alpha model in tandem with its focus on risk management will continue to deliver strong performance.
To the end of March 2025, the Global Equity Advantage strategy had outperformed the MSCI World Index by over 1% year-to- date.
“So far returns this year, despite market volatility, have been good and our quant strategies have continued to perform well,” said Creighton.
Advantages of a quantitative approach
However, investment markets often experience phases that may favour certain conventional investment processes, particularly those that are driven by a particular style bias. This can tempt managers to shift rapidly between various investment styles, capitalisation preferences and sectors to chase returns, which are often unsuitable for core portfolios.
“Instead, quantitative models are predictable and when executed properly, a systematic approach can avoid undue or unconscious biases to investment styles or areas of the market and provide an attractive source of excess return with a high degree of return predictability,” Creighton said.
“We seek to maintain exposures similar to the benchmark allowing security selection to drive excess returns,” he added.
After screening a universe of over 5,000 global stocks for investability, every stock is ranked according to the same criteria relative to their peers. The strategy aims to take the most attractively ranked stocks and build a portfolio matching the benchmark in terms of industry, sector and capitalisation exposure.
The securities are ranked according to four independent proprietary measures: growth, value, sentiment, and quality.
“Growth potential is measured by looking at the consistency of earnings and sales during the past few years and then by leveraging this data, along with margins, research and development, capital expenditures, cash flow growth and other reported financial metrics to project future growth potential,” said Creighton.
Valuation is derived by comparing relative book value, cash flow, intangibles and earnings across companies normalized by industry and region. Sentiment is gauged by looking at relative idiosyncratic price strength, changes in sell-side analysts’ projections for sales and earnings and the street’s enthusiasm for the stock.
Finally, “quality is measured by the strength of a company’s earnings, industry influence and its ability to grow its earnings organically,” said Creighton.
“The ranking for most industries is equally weighted between value, growth and sentiment with quality serving as a ‘tiebreaker’ between stocks equally ranked on the other three measures. Stocks are ranked daily within industry groups as part of the portfolio construction process,” Creighton said.
Managing risk
Lazard has also designed a proprietary approach to risk management that is built to control risk around the client’s benchmark.
“Our approach measures multiple contributors to portfolio risk (for example, beta, capitalisation, sector exposure, style, and position size) and controls them within carefully defined parameters relative to the benchmark,” said Creighton.
Using portfolio optimisation software, the outputs from the return models are combined with capitalisation, sector and position limits to build a portfolio with the highest expected return. Trades and weights are suggested by the optimiser when there is a stock that improves the portfolio’s return after the inclusion of transaction costs.
“All potential trades suggested by the optimiser are reviewed by the team with the strategy’s investment objectives and for the integrity of the data, and the process results in a portfolio of between 150 and 275 securities,” Creighton said.
“No single factor dominates our ranking process, but through a balanced approach, we select companies that we believe offer the best combination of discounted value and improving growth,” he added.
“It is possible that a suggested purchase is overridden during this process, but this is rare and more than 90% of suggested trades are implemented even after a review,” said Creighton.
The sell discipline is applied using the same process and measures that drive purchase decisions. Positions are sold when a more attractive stock is identified or if the investment thesis for owning the stock is invalidated by updated news and information.
Consistent and adaptable
Lazard’s investment philosophy and approach have not changed for more than two decades since the team has been managing multi-factor equity portfolios.
“However, the team is always researching new ideas at the individual factor and portfolio construction levels,” said Creighton.
For instance, Lazard has implemented incremental improvements to each of its factors, including the integration of alternative data sources, as well as computerised text analysis and other data-processing techniques, to help with stock ranking and risk analysis. AI is one of many tools it uses to identify new factors or refinements.
This effort to constantly improve elements of our models is a core component of the investment approach and one that has helped its strategies deliver attractive results over the years in a wide variety of market environments.
