A brilliant interview with Aswath Damodaran from May 2019 - A Conversation with NYU Professor Aswath Damodaran Elm Partners
He talks about several interesting aspects
- Value investing vs index investing vs momentum based trading
- What he thinks of factor based investing models
- Why its much more difficult for Wall Street analysts to generate alpha today than before (What he says is good news for retail analysts, the likes of whom are present on Valuepickr)
Quoting a couple of interesting snippets from the interview below:
On why its more difficult to generate alpha today
I’ll give you a simple example: thirty-five years ago, if you were an investor, you had an advantage just being in New York City over being in Des Moines, Iowa. Why? Because the SEC offices were here, and if you wanted to look up a filing by a company, you could physically go to the SEC offices and check out that filing. You had a competitive advantage based on location. And if you worked at a major investment bank, you had access to a computer. Most people in the world did not – so if you had access to computing power and you had access to data, it gave you a leg up.
Now the investing world has become a lot flatter, especially in the US. I can’t think of too many competitive advantages that you would have at Goldman Sachs as an equity research analyst over some person sitting at their own computer. If you’re going to create value in this business now, you’ve got to think of what else you bring to the table. It can’t be that you have better data, it can’t be because you have a more powerful computer – it’s got to be something else, and that’s made investing a lot more difficult than it used to be.
On why factor based model outputs should be interpreted correctly
But you can’t have it both ways, and it becomes interesting when you get a paper that treads in that grey area. One such paper, for instance, is the AQR paper on the size factor: that even though the small cap premium has disappeared over much of the last 37 years, if you screen it for really bad companies, what they call junk, then small cap companies still have excess returns. Now we’re dancing on the head of a pin, because if I really treat it as a factor in the spirit of Fama-French, there’s extra risk associated with it so here’s what I should be doing: when I value a small company I should first assess whether it’s a high quality or low quality company. And then for the high-quality companies, I should use a higher cost of capital than in discounting the cash flows for low-quality companies. That’s a really tough intuitive sell. That if I get a bad company, I should use a lower required return – but this is what happens when we don’t draw the line, when we use those factors to build this premium into a cost-to-capital. This is why I’ve never used the small cap premium in 35 years of valuation practice – because I think the minute you do that, you’re opening the door to including things in your cost-of-capital that really should not be included in there.
How he comes up with expected return metrics for US markets
VH: You write annually about long-term expected returns of the market as a whole. Can you give us a brief description of how you come up with your long term expected return for say, the US equity market, or the global equity market?
AD: I do it on a monthly basis, and I think again this goes back to what I said earlier about mean reversion. In the past the way I would compute those future expected returns was to look backwards: look at the Ibbotson data to 1926, and look at what stocks made on average over T-bonds, and make a leap of faith: if that’s what I made over the last 75 years, that’s what I should expect to make over the next seventy-five.
But as I said, so much of what we know came from the US in the 20th century, but starting about 25 years ago my faith in using historical returns started to get shakier and shakier, so I said we’d be much better if I could get a forward-looking expected return for the market. So I stole from the bond market an idea that’s been around forever: that yield to maturity is basically an internal rate of return. You take the price of the bond today, you take future cash flows, you solve for what kind of expected return you’re going to make, given what you pay.
So at the start of every month I take the S&P 500 and I look at what people are collectively paying for stocks. I do have to make projections of expected cash flow, but that’s not difficult because these are, after all, the 500 largest market cap stocks. So I solve for an internal rate of return every month, and that becomes my expected return for stocks.
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