Gerard O’Reilly Dives Deep into Investment Philosophy on ‘Rational Reminder’ Podcast


KEY TAKEAWAYS
  • Dimensional starts with what clients are looking for and then determines how best to deliver rules-based, higher-expected-return strategies to meet those needs. The approach incorporates the benefits of index-based approaches while avoiding the drawbacks.

  • Gerard discusses how the firm integrates multiple factors into its portfolios. While some have claimed the existence of more than 400 factors, Dimensional focuses on six, which are considered reliable and additive, and are discussed at length in the episode: company size, value, profitability, investment, momentum, and profitability growth.

  • The firm has a relatively complete view of differences in expected returns across stocks without needing to consider other variables. If we find a better way to do something, we will do it, but we have a high bar about what is considered better.

Dimensional Co-CEO and Chief Investment Officer Gerard O’Reilly recently joined PWL Capital Portfolio Managers Benjamin Felix and Cameron Passmore on an episode of their Rational Reminder Podcast. The wide-ranging conversation even included a question about whether O’Reilly himself has a financial advisor. (Spoiler alert: He does!) 

Listen to the podcast here. Below are some of the highlights, edited for clarity, along with time stamps.


Market-cap-weighted passive strategies vs. Dimensional’s strategy [0:03:45]

Dimensional starts with what clients are looking for and then determines how best to deliver rules-based, higher-expected-return strategies to meet those needs. The firm’s approach is set apart by its use of market prices as predictors of the future and a belief that optionality has value that should be captured. In a nutshell, Dimensional can be described as: sensible ideas, well implemented. The approach includes a lot of the benefits of index-based approaches, like transparency and low cost, but does not suffer from the drawbacks of passive investing, such as a lack of flexibility.


Who should consider a factor-based portfolio? [0:07:07]

Whether a tilted portfolio is an appropriate approach for an investor is driven by that individual’s sensitivity to deviations from the market. For those who are OK deviating from the market, a factor-based, or tilted, portfolio can be very appropriate. There will be times when returns are disappointing. One must be willing to stay the course and be a long-term investor through those disappointing times in order to be there when the returns are strong. A tilted portfolio can be appropriate for a lot of people if they have the right support, which is where a financial professional comes in.


Diversification in a factor-tilted portfolio vs. a cap-weighted market portfolio [0:10:57] 

People measure and approach diversification different ways. Dimensional’s starting point for diversification is the market. A global market-cap-weighted portfolio is a good starting point on what diversification is at the security, country, and sector levels. If you differ a little from that starting point, you’re probably equally diversified. If you differ greatly from the market cap weights, that may mean you are giving up some diversification.


Criteria we need to meet before variables are considered dimensions of expected returns [0:13:00]

The most significant criteria revolves around whether something is sensible. In other words, before we even look at the data, would we expect this variable to be related to differences in returns across stocks or bonds? Then, the data must be robust. We want to make sure it is a premium worth worrying about. If it only produces a tiny difference, it might not be worth considering in an overall investment portfolio. If there is a meaningful difference, like the fact that value stocks have outperformed growth stocks by three to four percentage points historically over the last 100 years, then it is worth considering. We also aim to understand volatility and ensure that we can capture the benefits in a well-diversified and reasonably low-turnover portfolio.


Factors Dimensional focuses on for portfolio decisions and implementation [0:16:09]

Over the past 30 years, there have been three main data sources used in academic research: market prices, income statement data (revenue, cost of goods sold, etc.), and balance sheet data (assets, liabilities, etc.). Academics essentially use these three data sources to look at two things: current values (market cap) and changes in price over various periods of time (momentum).

While there are more than 400 factors out there, it really comes down to six: company size, value, profitability, investment, momentum, and profitability growth. Dimensional uses all of them except profitability growth, which we are currently exploring.

We use the long-term drivers—size, value, and profitability—to lead the asset allocation. We use the shorter-term drivers—momentum—to help with the timing of increasing and decreasing weights of certain stocks. We are making decisions with a small amount of turnover every day to keep the strategy focused on where we want it to be.


How Dimensional decides between underweighting or excluding securities in portfolios [0:19:59]

It depends on how the return pattern looks when stocks are sorted on a particular variable. Ultimately, size, value, profitability, and investment characteristics are the reasons that we’re buying or selling. On top of that, we consider the momentum characteristics in the day-to-day aspect. Essentially, we are saying that we have a preference to buy stocks in upward momentum, but the fact that they are in upward momentum is not the reason we are buying them.


Why Dimensional uses operating profitability rather than cash-based profitability [0:22:38]

We believe the accrual-based method is more informative of the true economic activities of a firm. Accrual-based accounting methods tend to give you a better representation, a better economic view of the firm. When you’re already considering size, value, and investment, operating profitability and cash profitability perform equally well. It’s more stable and leads to lower turnover.


Dimensional’s view on goodwill [0:29:31]

Every asset is worth something because it produces future cash flows. That’s the value of an asset. Assets, as do liabilities and prices, all have information about future cash flows. That’s why they’re related to returns.

Goodwill is an asset. It gets generated as part of mergers and acquisitions. Around the year 2000, there was a change in accounting practices that required all companies to include goodwill on their book value in an acquisition. Dimensional has used that data to run the numbers many times, and we have consistently found that you can’t tell anything from the numbers. It’s not worth adjusting for it.

If you want to help somebody, you tell them the truth, and if you want to help yourself, you tell them what they want to hear.

When you’re accounting for five or six variables, you can’t really tell anything from the historical data about which blend is better than the other blend if you’re doing the experiments fairly. It really comes down to having the expertise in implementation to catch outliers and those issues that you’re seeing real time in the marketplace and adjusting in real time rather than wholesale adjustments on some particular variable.


The value of including internally developed intangibles in value and profitability metrics [0:37:49]

It is a valid idea to include internally developed intangibles in metrics, but it is not currently implementable. The academic research we have looked at and reproduced has estimates that are just far too noisy. We’d like to include internally developed intangibles if we could get a better assessment of that data point, but we aren’t sure that you can get a better assessment.


Why Dimensional doesn’t combine multiple metrics to measure relative price [0:46:41]

With all the variables we are considering today, we are well positioned to have a relatively complete view of differences in expected returns across stocks without needing to consider these other variables. When you are already considering five or six factors, it doesn’t give you anything extra.


Expected premiums for owning smaller stocks over larger ones [0:58:50]

When you look at different factor models, almost all of them work better when you include small cap factors or small cap stocks. They are an important aspect of the overall portfolio, and regardless of what you feel about small cap premiums, they deserve a place in your portfolio. They improve diversification and help you pursue the other premiums because of that.


The importance of security lending revenue for expected returns on Dimensional funds and improving the investor experience [1:00:12]

Security lending improves the investor experience. It is a value-add. If the process is optimized and integrated with the portfolio management process, then you can loan out stocks and get all the collateral back. There is some risk, but it can be well-managed. Then, you can invest that collateral in a money market fund or something similar and people will pay you, or pay the investors in the fund, money for taking that security out on loan. As a firm, this also gives us information about the securities lending market, which tends to be opaque, that we can use in other areas of how we manage the portfolio.

Dimensional has built different tools so that, when we’re selling a security, we can time the pace of the recalls. We can leave it out for longer if it’s generating revenue, or we have the flexibility that if we see a stock go on loan at a high fee in the marketplace, we can jump into that because we have flexibility. We don’t need to sell that stock today, or we can hold on to that stock for a period of time.


How Dimensional deals with sector weights and the role that diversification plays [1:04:12]

With sector weights, Dimensional deviates from the market but not so far that we give up some form of diversification that could otherwise be managed. All financial variables have warts when it comes to identifying stocks with higher expected returns. The way we deal with those warts is to use the variable but not let it make us look so different in the market that we have a bad outcome if this premium doesn’t show up over the next 10 years.


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