What can investors learn from academia? [video]

Discover whether academic research really does provide you, as an investor, with beneficial insights

    What can investors learn from evidence-based investing?

    Gerard O’Reilly from Dimensional Fund Advisors discusses the impact that academia can have on investors.

    When we talk about evidence-based investing, what we’re really referring to is academic evidence.

    RP: When we talk about evidence-based investing, what we’re really referring to is academic evidence.

    Some financial professionals are dismissive of academic research, arguing that it’s too far removed from the realities of today’s financial markets. True, academic models are, by their nature, theoretical. But that doesn’t mean investors can’t learn practical lessons from them.

    Here’s Gerard O’Reilly from Dimensional Fund Advisors.

    GO’R: Academics come with models of the world, and those models are usually incomplete. But what do you learn from the models? You gain insight about the real world. The models have to be incomplete for you to learn from them, but you do learn. You can gain insights about better ways to invest, better ways to structure portfolios so that when you come to the real world, you’re better equipped and have better frameworks to make rational investment decisions. So academia, by its nature, has to simplify the real world so that you can understand the real world better. But that’s the beauty of how academics approach the problem: they simplify it just enough so that it’s real enough to be interesting, but understandable enough so that you learn something.

    RP: Dimensional is possibly unique among asset managers in that everything it does is based on empirical evidence. Over the years, the firm has worked with some of the most famous names in academic finance.

    GO’R: Gene Fama, who won a Nobel prize a few years ago, is an academic that we have been very closely related to since the founding of the firm. Along with Kent French who’s a co-author and a very close collaborator with Gene Fama. And what we’ve used from their work, and they have shared their work with us and the world over time, is really the intuition that their work has given to us about prices - securely prices reflecting information.

    Other academics are academics like Robert Merton, who also won a Nobel Prize, Myron Scholes has also won a Nobel prize - and their work has also given us tremendous insights, whether it’s in lifecycle finance or in how to structure portfolios. So they’re to name just a few of what I would call some of the great academics in finance, and there’s many more that were associated with and that we work with. But the work that they have done has really led to some big innovations in the field of practical investing that I think Dimensional has been able to use to the benefit of our clients.

    RP: The most famous contribution that Fama and French have made to our understanding of the financial markets is the so-called Three-Factor Model, and an updated version, the Five-Factor Model.

    In a nutshell, Fama and French have shown how certain types of stocks — for example, small-cap and value stocks, and stocks of firms with high profitability - tend to outperform the market as a whole, over the long term.

    GO’R: We think that there are differences in expected returns across stocks and across bonds. How do you identify those? With the intuition from the Three and Five-Factor Model. Lower price, higher-expected cash flows, higher-expected returns.

    So, we say, "How do we structure portfolios?" Let’s look for low-priced stocks relative to some fundamental measure of firm size, high-expected cash flow i.e. high profitability. That’s higher-expected returns, less overweighting those stocks.

    RP: It’s not necessary for investors to have a detailed understanding of the work of Fama and French, but it pays to use an adviser who does have that level knowledge.

    Academic research really does provide us with insights that you, as an investor, can benefit from.

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