Combining different managers with different investment styles, also known as split funding, can ensure a much smoother return profile for clients, says the writer. Picture: ISTOCK
Combining different managers with different investment styles, also known as split funding, can ensure a much smoother return profile for clients, says the writer. Picture: ISTOCK

If you want to outperform the crowd, you must do things differently from the crowd, said John Templeton, one of the best stock pickers of the past century.

In the multimanager arena, how you diversify between different investment styles in a fund of funds (FoFs) is one way of doing things differently. Ensuring that underlying managers have complementary investment styles can reduce short-term investment risk, without compromising long-term returns. Avoiding scenarios where investment strategies are highly correlated and will underperform — or outperform — in the same market conditions also promotes effective diversification.

Traditionally, equity investment styles have been broadly divided into either growth or value. Growth investors typically invest in companies whose earnings are expected to grow at an above-average rate compared to their industry or the overall market. The focus of this style is to grow investors’ capital.

Value investing is a strategy where stocks trading for less than their intrinsic values are selected. Value investors select stocks that are undervalued on a price-to-book ratio, a price-to-earnings (P/E) ratio or their dividend yields. This style seeks to profit from the perceived underpricing.

Growth strategies have outperformed value styles over eight of the past 10 calendar years and have dominated conversations. Value and growth investment styles, however, are about as “modern” as the modern portfolio theory and efficient market hypothesis. These concepts are still fundamental, but the investment industry has evolved beyond traditional finance theories and investment styles in the pursuit of alpha and other return-enhancing factors.

Alpha is the return achieved from active stock selection relative to its benchmark and is one strategy employed by active managers. Different investment styles lead to a variation in alpha. Originally, it was perceived as any investment return. In 1964, William Sharpe attributed a portion of portfolio returns to purely having exposure to the stock market. Any return above and beyond market return was deemed alpha.

The robustness of return-predictive signals is often not tested, or only tested to a limited extent, on sample period data. This means the return-predictive signals often fail to perpetuate meaningfully into the future.

Subsequently, various factor models, such as the Fama and French model (1992), further attributed a portion of alpha, and market beta, to specific factors a stock possesses. Size, book-to-market and 12-month momentum of the specific stock were regarded as return signals.

This explained an increasing part of investment returns, and with that, alphas have shrunk as they are reclassified from alpha to exposure to common factors.

As financial theories and investment strategies continue to evolve, the industry has moved far beyond the simplicity of P/E ratios or earnings growth for stock selection. Fund managers have adapted and tailored their strategies to capture their view of the optimal exposure to market beta, factors and alpha drivers.

Some believe that once a successful investment strategy or return-predictive signal is discovered, it won’t work in the future as the market will immediately exploit the relevant opportunities and drive up these investments prices. Others believe certain strategies or return-predictive signals are so robust that they should continue to provide alpha indefinitely. The truth probably lies between these two extremes.

Investors have increasingly looked for other ways to achieve alpha. Research conducted in 2017 by Schroders Investment Management revealed 316 return-predictive signals and factors.

According to research done in 2014 for the Financial Analysts Journal, Fama and French’s three factors (1992) were not among the top 10 return signals for US equities from 1980-2012.

Return-predictive signals are influenced by a variety of factors including research biases, such as data mining or the look-ahead bias. Data mining is where researchers search through historical data to find significant patterns, while look-ahead bias is where research uses information that was unavailable at a particular date.

The robustness of return-predictive signals is often not tested, or only tested to a limited extent, on sample period data. This means the return-predictive signals often fail to perpetuate meaningfully into the future.

Examples of where models based on historical factors have failed to predict the future are the numerous Fifa World Cup models created by UBS and Goldman Sachs. UBS predicted a 60% chance that either Germany, Brazil or Spain would be the overall winner in 2018, Goldman Sachs predicted that Brazil would be the overall winner. Subsequently, these teams didn’t even qualify for the semifinals. UBS’s top pick, Germany, failed to even make it past the group stages.

These examples, though based on soccer, serve as cautionary tales for investors including return-predictive signals in their valuation models. One needs to ensure these signals will continue to result in meaningful outperformance and thus requires comprehensive due diligence.

Investors in multimanager funds essentially “outsource” the burdensome due diligence process to the manager’s research team. The qualitative aspects that form the basis of fund due diligence may be more important than the quantitative research.

Therefore, a lot of time needs to be spent to gain a clear understanding of the various fund managers’ investment philosophies and processes, portfolio construction techniques, track records, and the strength of their teams and overall business. Multimanagers need to be aware of the distinct factors fund managers use in their investment philosophy and then determine whether these factors can contribute to future peer group outperformance.

Combining different managers with different investment styles, also known as split funding, can ensure a much smoother return profile for clients. Smoother returns contribute to investor peace of mind and may discourage investors from switching funds unnecessarily — a practice that has been proven to be detrimental to investor returns over time.

The bar of soap analogy illustrates the effect of switching between recent winners — the more the soap is handled, the smaller it becomes. This strategy has been proven to destroy investment value.

The need for thorough due diligence has perhaps never been as important as it is today. There will always be certain trends creating short-term noise. Quality, active investment teams can adapt to changing circumstances, and filter through short-term noise, and deliver peer group-beating returns.

• Pask is CIO at PSG Wealth.