The Ledger
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O'Shaughnessy: High quality metrics do not generate excess returns; low quality destroys them
“In the quantitative sense, high ROEs or gross profitability or whatever your measure of quality is really isn't indicative of strong future excess returns. What's really useful about quality is that very bad quality, so really over levered balance sheets, comp…”
O'Shaughnessy: Publicly sharing quant findings produces stronger signals via feedback
“In quant research, this is really interesting, which is that you actually get a stronger signal. We found when you share your general findings, not necessarily the code or the particulars, but the general findings with a broad audience, then all of a sudden yo…”
O'Shaughnessy: Momentum forecasts fundamental growth better than valuation multiples
“What fascinates me about this is momentum does a better job of forecasting future fundamental growth than price does. So the highest momentum decile has better future fundamental growth than the most expensive, let's say PE decile or free cashflow yield decile…”
O'Shaughnessy: Momentum Alpha Exhausts Within One Year and Reverts to Negative Returns
“So you earn all of your momentum, all of your alpha, rather, in the first one year holding period, and then you actually need to get the hell out, because it reverts. And typically, depending on where you're looking at the data, within two years or so, it's ac…”
O'Shaughnessy: Almost No Funds Have Pure Machine Learning Models in Live Production
“To be clear, I don't think almost anybody has a lot of that in production today, but those tools are becoming more and more useful.”
O'Shaughnessy: OSAM has almost zero portfolio overlap with AQR and LSV
“Our overlaps with other quants are shockingly low. Like we have this little cool program that we can show people this on the fly and they won't believe us. Like they'll ask about AQR and LSV and these other great managers, you know, really, really, really stro…”
O'Shaughnessy: Machine learning algorithms always fail at predicting stock returns directly
“You can feed all the best data in the world to whatever ML algorithm you choose. Let's say it's like a decision tree or something. And if you're trying to predict returns, it always falls apart. It never works.”
O'Shaughnessy: Reducing tracking error is much easier than finding new alpha
“It's actually far easier to shape down tracking error than it is to find new alpha. I could run a much lower tracking error process with not that much additional research. I can't just go find new alpha.”
O'Shaughnessy: Quants will inevitably replicate any repeatable investment strategy
“If there is a repeatable strategy where we can build a big enough sample size and do the right kind of research, a quant is going to figure it out. And the question is when, not if.”
O'Shaughnessy: Factor alpha comes from execution discipline, not awareness
“That says that the source of the excess return is not knowing about the thing. It's doing the thing.”
O'Shaughnessy: No asset manager is applying tech platform principles holistically
“Asking whether or not we can apply those principles to a very simple old school asset management business. And the answer, at least in my view, unequivocally so far as yes, and nobody else is doing it. Or at least they're not doing it holistically as part of h…”
O'Shaughnessy: A High-Quality Twitter Following Functions Like Having an AGI
“That having a big, smart, diverse group of people that follow you on Twitter is literally like having an AGI. I believe that that is true. It's the best search engine in the world. So if you're looking for something, ask a big group of people, you're going to …”
O'Shaughnessy: S&P 500 still beats hedge funds on a Sharpe ratio basis
“I think on Sharpe ratio, it still would have been the S&P.”
O'Shaughnessy: Factor Strategies Like Momentum Should Never Be One-Off Trades
“So unless you really buy into these concepts at a deep level and are willing to stick with them through cycles, I think you probably shouldn't apply them at all. You shouldn't apply momentum into a one off trade. You should apply it in the right way systematic…”
O'Shaughnessy: Equity returns only stem from growth, multiple expansion, or capital returns
“When you're holding for that long, and you think about equities at an elemental level, I think there's just three ways to earn return. The businesses you own grow. In sales, earnings, EBITDA, whatever it is, free cash, the multiples of those fundamentals expan…”
O'Shaughnessy: Companies buying back 5%+ shares annually historically outperform peers
“Super normally high buyback yields, and a simple definition of this might be a company which is buying back five percent of its shares or more in a one-year period of time, which is a lot. That's a big deployment of capital. That kind of company historically h…”
O'Shaughnessy: Top Decile Momentum Stocks Show Supernormal Operational Growth in Year One
“All we know is that of the highest momentum decile stocks, just in very, very simple terms, those stocks in the next year have super normally high operational growth.”
O'Shaughnessy: Value Stocks Continue Generating Marginal Alpha for Up to 10 Years
“So if you buy in value today, you, on average, earn a little bit of alpha for a really long time. Most of it's early on, but you continue to earn marginal monthly alpha for up to 10 years.”
O'Shaughnessy: R&D spending factor added zero incremental alpha to master model
“So we did a lot of work around like R and D type spending. And when you plug it in, it Is both value and momentum in some interesting different ways and sectors. But when you plug it in into the master model as a factor, it was completely gone. It literally di…”
O'Shaughnessy: Negative stock returns are concentrated in the worst factor decile
“Most of the really interesting return, in this case, negative, bad return that you want to avoid, is concentrated in the tails, in the worst decile.”
O'Shaughnessy: Qualitative analysis and portfolio concentration protect discretionary managers
“If you can handicap future scenarios based on all that you know about a business or an industry or a trend or whatever it might be, that's going to be hard for quants to replicate. And if you can concentrate In portfolio construction, that's also going to be v…”
O'Shaughnessy: OSAM Strictly Prohibits Researchers From Discarding Failed Studies
“And in our case as a business building, we've got a pretty strict rule around OSAM when it comes to building. You can't just do a research study and if it doesn't work, just like forget about it. You need to bring it into our ecosystem in a way that can be use…”
O'Shaughnessy: All OSAM investment factors have behavioral explanations
“So I would argue all the factors that we use here have a behavioral component, or at least a compelling behavioral explanation for why they work.”
O'Shaughnessy: 30% to 50% of Top Thinkers in Any Field Are on Twitter
“Something like, 30 to 50% of the most thoughtful people in that domain are gonna be on Twitter talking about what they do.”
O'Shaughnessy: Pure quantitative strategies fail on concentrated portfolios
“If you're going to build a concentrated portfolio of a handful of positions, you can't do quant. It can't be pure quant. The stats don't work. You need to build a pretty diversified portfolio for a pure quant approach to make sense.”
O'Shaughnessy: Quant methods will never fully replace relationship-driven private equity
“Then your relationship with the seller, your skill in negotiation and deal structure, all of these things are critical and Again, can quant help inform some of that? Probably, but I don't think it's ever going to completely eat the whole thing.”
O'Shaughnessy: Quants typically avoid sector-specific data in favor of broad cross-sectional metrics
“Typically quants don't do deep industry sector specific
Data sets outside of like financials, which has been like a common problem for quants. Quants typically are looking for something you can compare cross-sectionally across the entire population of stocks.”
O'Shaughnessy: 4x Free Cash Flow Signals Distress in Public Equities, Not Private
“And, you know, when he first told me that he was buying businesses at a little bit north of four times free cashflow, you know, I kind of laughed. I thought, okay, like, so they're going out of business in three years. I mean, in the public markets, that multi…”
O'Shaughnessy: Best quant researchers are defined by extensive failure experience
“The best way to know that someone's going to be an effective and efficient researcher going forward into the future is that they know what not to do. And I think the only way to do that is to build up that experience of failure through time.”
O'Shaughnessy: OSAM failed to make factor timing work despite massive research effort
“We have burned an insane amount of our time Capital, human capital, stress, just every kind of capital trying to make this work, and it has not.”
O'Shaughnessy: Predictive modeling will get easier, shifting advantage to input data
“I believe that the predictive modeling part of this is going to get easier and easier. So what that means is what you put into those models is of critical importance.”
O'Shaughnessy: Borrow Costs and Volatility Eliminate Quantitative Short Paper Alpha
“Most of the stuff that screens as screaming shorts and in a paper portfolio works incredibly well. You have incredible problems with borrow availability, with borrowing cost, which often instantly removes the paper alpha and with volatility.”
O'Shaughnessy: 10-year real equity returns strongly inversely correlate with Shiller P/E
“When you look at the correlation Correlation between the current Shiller P.E. And the future 10 years of real returns in the market, it's very high. It's something like .7 or point, maybe even higher than that.7. So pretty reliably, what that means is if you b…”
O'Shaughnessy: Shiller P/E at 30 marks only the third time ever
“And we're at 30 today. Only the third time ever at 30 today.”
O'Shaughnessy: Zero fund-of-funds fees would not have won the Buffett bet
“If the fund to fund fees had been zero, you still would have lost.”
O'Shaughnessy: Alpha in financial markets depends strictly on relative skill
“Really all that matters in markets is relative skill. That if you've got, you know, 10 PhDs in a room, maybe 3040 years ago, that meant you were going to earn enormous alpha. But now everyone has those 10 PhDs, and they're fighting against each other. It's a r…”
O'Shaughnessy: DFA investors suffered a smaller behavior gap than S&P investors
“They've done an amazing job of convincing their investor base that they need to hold these strategies for the long term. Now, obviously, that works out well for DFA as a business, because they've got incredibly sticky money, but it has also worked out very wel…”
O'Shaughnessy: Key Investment Factors Historically Succeeded in Only 60-70% of Single Years
“In our research, luckily, those categories are honestly straightforward and simple. They're things like valuation, things like momentum, quality, return of capital. They're not crazy concepts. You just have to apply them with a lot of discipline, and I think t…”
O'Shaughnessy: OSAM Measures Momentum Across 3-12 Month Windows and Adjusts for Volatility
“What's fascinating about pure price momentum and the way that we think about this is three, six, nine, 12 month trailing windows of total return versus pierce. We think we should also care about the volatility of the momentum.”
O'Shaughnessy: OSAM Uses Machine Learning to Predict Specific Events Like Dividend Cuts
“So as a result, we have started to focus more on applying these techniques to focus on something like a dividend cut. Let's use that as an example. Build a model that just forecasts or predicts dividend cuts, and that's it.”
O'Shaughnessy: OSAM Has Seven External Research Partners, Including Jesse Livermore
“We now have seven of these people. It started with a very well-known anonymous writer who goes by Jesse Livermore online. He was sort of our pilot case.”
O'Shaughnessy: OSAM team spent three full years cleaning primary dataset
“We once spent three full years, the entire team spent three full years just cleaning and scrubbing data in our primary data set.”
O'Shaughnessy: OSAM Failed Three Times Attempting Short Strategies Internally
“We've done it with our own capital three times and failed miserably each time, not an absolute return sense, but certainly an opportunity cost sense because it's been during this great run up. So we've lost a lot of return with our own capital trying to do thi…”
O'Shaughnessy: Average Shiller P/E sits near 16-17, shifting higher post-1980
“Historically speaking, the average Shiller P.E. Is probably 1617, something like that. But there's definitely two regimes, and one is sort of pre-early 19 eighties, and one is post. And the average post, 19 eighties, is much higher.”
O'Shaughnessy: Constellation Software operates like a disciplined Berkshire for software
“Effectively what that is, is a, like Berkshire, an almost decentralized collection of software companies. So the parent Constellation, forgetting the CEO's name and his team are basically buying up individual assets, not, not micromanaging them. And they're ki…”