To most traders and investors, Barry Ritholtz is the voice of The Big Picture, one of the more popular financial blogs on the Internet. Now hosted at ritholtz.com, The Big Picture was one of the more prominent financial must-reads for traders and active investors during the second half of the Bush years. Some of the earliest concerns about the credit crisis and the housing bubble in the financial blogosphere were posted at The Big Picture – a blog that now boasts over a 29 million visitors and 39 million page views.
Barry Ritholtz is the man behind The Big Picture. He is CEO and Director of Equity Research at Fusion-IQ, an online quantitative analysis research firm. He was also recently the Chief Market Strategist for Maxim Group, a New York investment bank, managing more than $5 billion in assets. He is a frequent guest commentator in print, online and broadcast financial media including CNBC, Bloomberg, PBS and Fox Business.
His firm is also responsible for creating an online software tool, at Fusion-IQ, that uses his proprietary metrics to quantitatively rank more than 7,000 stocks and 400 industry groups. The Fusion metrics are backtested and used by both retail and institutional-level investors and traders.
I spoke with Barry Ritholtz by telephone the day after the Presidential election in November. We talked about ETF trading, contrarian trading and creating stories and narratives to help explain the cold, hard probabilities of quantitative analysis. What follows is an edited transcript of lively and insightful conversation with Mr. Big Picture, Barry Ritholtz:
David Penn: First, off I have to ask you about something I saw on The Big Picture this morning about exchange-traded fund (ETF) trading. ETF trading is something we have been very interested in, as well. You had a blog post about exchange-traded funds and leverage exchange-traded funds, particularly the new 3 to 1 ETFs
Barry Ritholtz: We do a ton of ETFs lately.
Penn: Do you? Let me just get your general overview on the rise of leveraged ETFs – including the new 3 to 1 leveraged funds. How effective do you think they are? Why should be traders be interested in them?
Ritholtz: ETFs do some really interesting things. We are bottoms up stock pickers, but in this environment, ETFs make sense. If you want any sort of instant exposure to a sector, a stock, a region, ETFs are just really, really simple, fast and painless. ETFs work well for that. The leveraged funds are really interesting.
Just for a little background: we came into this year (2008) very bearish. We had plenty of longs, but over the summer we were probably more cash than we’ve ever run, 50 to 60 percent cash in our managed accounts. Then as we went through August and into September, well, we have a couple of pretty firm rules about stock losses. We always manage risk by using stop losses. We have some other rules, but it’s long and complicated.
When a stock is working out for us, we try and raise the stop to a breakeven. If you have a big winner, we never want to give back 25 percent of the profits. And there are other mechanical ways of preventing yourself from riding what we like to call the “Cape Matterhorn” stock. Think of Apple in the 1990s; you had a run-up on the iMac introduction. It went from single digits to 100 plus, then back to single digits. This time, with the iPod and the iPhone, it hasn’t quite re-completed the round trip, butits given a ton back. There are plenty of people who ride stocks all the way up, and then don’t know what to do with them and of course, they ride them all the way back down. Ouch.
We hate doing that. So we came into the October lows with just an inordinate amount of cash and a lot of nervous clients. And when we made our bull call on October 10th – which may end up being just a cyclical trading rally, we don’t know and we won’t know for a couple of weeks — there was a real concern of, “I can’t believe you guys are buying here. You’re crazy.” [EDITOR: A similar buy call was made in real time on November 13th, and again, and again, no one complained]
So the approach we took was, let’s buy the two-for-one leverage SSOs (ProShares UltraS&P 500 exchange-traded fund), which are the S&P 500 X 2, and QLDs (ProShares UltraQQQ exchange-traded fund), which are the NASDAQ X 2. And at the same time, we maintained a 50 percent cash position.
Penn: An interesting approach.
Ritholtz: Yes. In a very strange turn of events, we had 100 percent market exposure and 50 percent cash, which if you stop and think about it, is a nice little trick to do.
We could have just gone 100 percent stock, but we never like to pick our points that way. The way that capital deployment worked, it gave us the upside exposure we wanted and yet, at the same time, maintained a modest amount of risk via our cash holdings. Since we don’t care about the actual market movements relative to an individual equity when it comes to stock losses, we had the same stops on the two-for-one leverage stock as if it were GE. It didn’t make any difference. Once it gave up a certain percentage and crossed certain key technical support lines, we were done, we get stopped out — trade over. But that hasn’t happened, so it really gave us this strange and interesting move, relative to what happened.
Penn: What has happened since?
Ritholtz: We always trade around and if we have a stock that runs away to the upside on us, we’ll sell a little bit and try to buy it back cheaper. We’re pretty active that way.
The other thing that made the ETFs so attractive to us was we just don’t know what the single stock risk is anywhere, anymore, given the current environment. I don’t know if American Express is going to announce that they lost a gazillion dollars and the stock collapses on bad news [Editors note: they did]. Or a better name like J.P. Morgan. I don’t know if they’re going to turn around and announce they bought Goldman Sachs. Then strictly on an arbitrage play, JPM’s stock is down 15 percent. So we wanted to stay away from all of that single stock risk, and ETFs worked out really well for us that way.
Penn: Have you ever used ETFs as extensively as you did with this particular trade?
Ritholtz: Yes. But this was a different approach for us, maintaining both cash and full exposure. It came to us almost by accident.
When we started maintaining all this cash and yet wanted all of this exposure, a part of us is thinking, “Let’s just buy out of the money, and in the money call options. We’ll go out six months, and if we’re right, we’ll sell them in a month. And if we’re wrong, well, that’s our stop loss anyway.”
That’s the way we used to approach that sort of situation. We used to say, “Gee, the market is so deeply oversold and it just had its worst week ever. If we really are contrarians, how do you not buy into the worst week ever?”
This time around, all of a sudden, we said, “Hey, you know, this is a little weird. We have 100 percent market exposure and 50 percent cash.” So it kind of gave us a strange “Now, that’s something we’ve never seen before” feeling. And so far, so good — it seems to be working out well.
Penn: Interesting. Let me back up just a little bit. A lot of folks, who know you and know The Big Picture, know you mostly as analyst. What I’m really interested in is that nexus between the research or analysis and the trading. How one drives the other.
Ritholtz: Everything driven by the data. We run a quantitative system. I know “quant” has become a dirty word, but it really isn’t the way we do it. We use a quantitative system where we look at a few dozen metrics that we have carefully back tested to see whether they have value or not and what their value is in combination with each other. That’s the starting point, that’s what drives our asset management, our institutional trading, and our research – its everything.
We rank 8,000 stocks on a 0 to 100 basis; higher is better, 70 is the dividing line, everything over 70 is usually going to outperform the SPX on average; everything below, on average, is going to underperform it. And the returns are [not to bore people to death] monotonic, meaning that each decile is better or worse than the one below or above. The 60s are worse than the 70s, which were worse than the 80s, which were worse than the 90s, etc.
That’s our starting place. That’s where we start looking at different sectors, at the market as a whole and at individual stocks. And then, because we’re essentially monkeys, we need a narrative. Humans don’t like numbers; we like stories. So we try to put the analysis into the context of what’s going on in the bigger picture.
That is a big part of my job.
Penn: Can you elaborate on what some of those metrics look at?
Ritholtz: There are four major lines of metrics that we’ll look at when we’re talking about the overall market. We’ll look at valuation, which is as much art as science because a lot of valuation is based on future earnings expectations. As an aside, this is why the so-called Fed model is worthless – its so idiotic – because you can’t say, “Based on these forward estimates, here’s what’s the value of the stock is.” Well, what if the estimates are wrong? And those estimates have been wildly wrong for the past year! So true valuation – not Wall Street’s worst guesses – is one thing we look at.
We look at sentiment measures, which for the most part, are most significant when they hit extremes. Sometimes they hit dramatic extremes and then they’re very, very significant – like we have seen recently.
Third, we look at technical measures – overbought and oversold, trend, institutional ownership, short interest – which is a combination of factors. I know that the fundamentalists’ their eyes glaze over when I discuss trend and relative action to trailing moving averages and a whole bunch of other things. But its objective data, not subjective, and therefore is more reliable to us.
Finally, everything is relative to monetary policy and interest rates. If the Fed is tight and rates are high, valuation almost doesn’t matter as much because there’s only going to be so much going on from the macro economic perspective.
Penn: And then you combine all of that and produce a narrative?
Ritholtz: Those are the four pillars that we use to evaluate the market. Sometimes people say, “How does the blog interact?” You’ll notice that almost every post talks about one of those four things. We’ll look at sentiment and sometimes that means looking at things like the percentage of cash mutual fund managers have, or the VIX, which is a sentiment measure, or the ARMS index or any one of a number of things that are more than just anecdotal.
We can’t run money on the basis of, “Hey, I bumped into this guy at McDonald’s and he said –” that doesn’t work for us. But on the other hand, if we know what all the fund managers in the universe surveyed by Merrill Lynch are holding X amount of cash, and that’s something that they’ve tracked for 40 years, and we can compare how the relative cash holdings are compared to previous highs and lows, it gives you some insight.
Ritholtz: Let me say the one really smart thing I’m going to say. Everything else I’m going to tell you, people can take or leave, they can say this guy’s an idiot or not, but this is one of the few things I know to be true and I know to be smart:
Nobody knows what the future is going to bring, so starting from that premise, we look at a bunch of data and a bunch of quantitative metrics and say, “Well, in the past when we had ABCDEFG happen, here’s what subsequently occurred, here’s the range, and the average. Therefore, when ABCDEFG lines up, we know that we can draw, not a sure thing, but we can say, Well, in 19 of the past 20 situations with all these metrics lined up, here’s what that net result was.” It gives us a baseline to look forward from, as well as a set of probabilities.
Now what’s going on today is you have ABCD lining up, but there’s also a whole bunch of crazy LMNOPQ stuff that is really sort of unprecedented. That’s why so many traders seem to be flailing about. They don’t have a frame of reference.
When the weatherman says there’s a 90 percent chance of sunshine tomorrow and then it rains, it’s not that he was wrong, just that the 10 percent chance happened to come up. So here we are, with a meteor hitting the earth – that’s essentially what the credit crisis is – there hasn’t really been any sort of direct parallel, or whatever parallels there are, they’re so imperfect that it’s just hard to draw a conclusion.
Penn: Are there any that come close? Parallels, I mean.
Ritholtz: Long Term Capital Management in 1998 is somewhat parallel and some of the situations that happened in the 1930s have some elements of a parallel. But so many of the circumstances, metrics and data are different; the parallels just don’t really work.
If you look at Spain in the 1990s or Finland, when they had their crisis, it’s just not the same. So it makes any type of aggressive trading extremely difficult because you’re in uncharted waters. You don’t have the ability to say, “Hey, out of 20 metrics, 17 line up and therefore, we’re pretty comfortable and here’s the range of likely outcomes.”
We did a study in the office last week and we essentially concluded that when markets get this oversold, when the VIX is here, and valuation and all the other metrics line up, you have about a 24 percent rally, on average. As of the end of Tuesday, before yesterday’s wreckage, we were up about 18 percent. Now that’s well within the range of outcomes. That may be the whole thing, or maybe this is just a normal pull-back and retest, and eventually we’re going to go to 30 percent. We really don’t know and so we’re very cautious relative to that because of the degree of uncertainty.
But when we were on October 10th, and the Dow and the S&P were down almost 50 percent over the past year, and we had this enormous, deeply oversold
condition, reasonable valuation, extreme sentiment, that was a much easier trade to make – even though all of our clients were like, “You guys are crazy.”
It’s funny because we always get grief whenever we take any of the institutional research and put it on the blog. Our clients say, “Why are we paying you if you’re going to give this to the world for free?” But that was one of the few times when we took something in real-time. That call literally went out to the clients at about 11:30, when the Dow was at 7,900 and it went on The Big Picture within a half hour of that happening, and this time nobody complained. I think the reason nobody said anything was that they all felt, “Screw you, guys. Who wants to buy here? You’re nuts, this is just a crapshoot.” Some literally said that to us.
But it wasn’t a crapshoot, at least, not according to all of the data. There were some pretty solid metrics that said, “Hey, if you’re a contrarian, well, here’s where you gotta buy ’em.”
Penn: You bring up so many interesting points. I know, myself, that it’s really only been this past year with TradingMarkets that I’ve had real exposure to real quantitative analysis. What is it about that approach to analysis that people don’t understand, which keeps making people somewhat adverse to it?
Ritholtz: Well, there are a few things. First, way too many people are innumerate, the mathematical equivalent to illiterate. So you end up with an interesting mix with some people who think of quantitative analysis as black box magic, while other people’s eyes glaze over when you start talking about probabilities and possible outcomes.
But we start just from the basic premise: We don’t know what’s going to happen next and neither does anybody else. But we know that there’s a limited universe of possibilities. Some of those possibilities are extremely unlikely and some of them are possible but improbable, and others are, “Hey, this is well within the range of likely outcomes.”
On any given day, a 1 percent move up or down is not unthinkable and as we’ve seen over the past few months, a 4 percent move up or down is no longer a rarity. And as we saw on October 10th, a 10 percent intraday move is not nearly as impossible as many believed. Here’s where merely thinking about numbers helps: You have to have previously thought, “Gee, if I ever see a 10 percent move down, intraday, I’m going to be buying the hell out of that.” But if you haven’t gone through that thought process beforehand, when the opportunity confronts you, it’s like looking at a car wreck. Part of you says, “Gee, I ought to go over and help those people” but the spectator part of you is just thinking, “Man, look at that thing burn.”
It’s absolutely fascinating to watch from a remote perspective. So that’s the first thing, I think, traders should realize, War-gaming these events in advance is a huge help.
Penn: Yes. The hard trade is often the best trade.
Ritholtz: Exactly. The other thing that people should realize is that the stock market is essentially a giant numbers factory. All the stock market does, every single day, no matter what’s going on with interest rates or presidential politics or earnings or news or anything, is it produces reams and reams of quantitative data, price action, volume action and then all the second and third derivatives [meaning numbers based on the prior numbers].
People, by the way, misunderstand whenever I say “derivatives.” I just mean data and the numbers that are based on that, the internal metrics. Price is one metric, and a moving average is another metric derived from that data.
What I call internal quantitative data others call technical analysis.
For the most part, technical analysis is too subjective. This wedge, that triangle, these support lines. But if I could turn around and say, “Here’s what happens when the trailing 10-day moving average crosses the 50-day moving average after this percentage of a move,” now suddenly it’s something that is much more empirical.
This is not an exact science. This is not physics, but there are elements of physics that apply to this.
Penn: And there are real people, real decisions behind all of those abstract movements.
Ritholtz: Yes. Let me give you a classic example. The 50 percent of the action in the stock market on any given day is institutional and something like the top 50 funds are responsible for the lion’s share of that activity. These funds don’t say, “OK, we want to have a position in Microsoft,” and then the next day buy a billion shares of Microsoft. They say, “We’re going to allocate a 3 percent position to Microsoft.” Then they start buying it over the course of a couple of days, weeks and months. And then, beyond that, as money comes in to 401(k)s and it automatically get allocated to these different funds, they do more and more of the same. So they just keep increasing their holdings in this given name as the size of their fund increases. They are buying more and more of the same stock in order to maintain a relative percentage position. And that’s how uptrends are sustained.
Conversely, you have the same thing with selling. When AOL merged with Time Warner, Janus turned out to be the biggest shareholder in each company. They ended up owning some absurd number – 22 percent? – of the new company or some ridiculous percentage like that. So they made a decision, “We want to unwind some of this AOL Time Warner.” They did that not because it was a crappy deal, which is what we had said at the time, but because they just wanted to get rid of some of their exposure. After all, it was ridiculous to own that much of any company. That’s beyond their own internal metrics. What ended up happening was they began selling.
I think their percentage came out to be near a billion shares. And the stock traded 2 or 3 million shares a day. If you want to take a billion-plus position and cut it down to a 200 or 300 million share position, how long does it take for you to sell 750 million shares? Well, if they were 100 percent of the volume, it would take them a year, 250 trading days and 3 million a day. But you can’t even do half the volume, so it took them a long, long time to unwind that position and, of course, the stock just went lower and lower because it had a relentless seller. It was nearly endless supply.
There’s some chaos theory for you: That’s what really drives a lot of the persistency in stock price trends.
All of that is a long way to go to describe why trends are trends, but it just shows you that there’s an actual basis for some of the mathematics behind things, and that there is a real explanations that make sense.
Penn: So what do you do with all of this data? How do you contextualize it ?
Ritholtz: The tricky part is when you look at the quantitative data, you have to figure out a way of, “How can I use this? What makes sense? What’s a good application of this?”
Bob Farrell was the strategist at Merrill Lynch for many, many years and he used to say something that is very, very true. He used to say that the news isn’t driving the market; the market is driving the news.
What he meant by that was, when you hear all these relentless bad stories and the market seems to be doing the opposite, rallying on bad news That’s because a lot of that stuff is somewhat already factored in because on an individual level, companies have announced or people have identified there are problems within the different companies, in terms of their sales or their revenue and so on. I call it the quasi-efficient market hypothesis. By the time it reaches the newspaper, enough people already have known about it. Old news really isn’t news as far as the markets are concerned.
It’s not that the markets are completely and totally irrational; it’s just that they are not nearly as efficient as people think. In English, what that means is, by the time it hits the front page of The Wall Street Journal or The New York Times, enough people with incentives to find out have already learned about it and they’ve sold their stock. That’s what shows up in the prices.
Penn: Sure. And that takes us back to the idea of the relationship between narratives of things and the things themselves – which takes us back to The Big
By way of turning the final corner on our conversation, I want to talk a little bit about The Big Picture and how it works into this. But first, if you could maybe tell us a little bit about the decision to launch The Big Picture as a blog.
Ritholtz: That’s kind of an interesting thing. It was more or less an accident. Since the ’90s, I had been doing an email list. I got tired of saying the same story over and over again, so I’d write it down, grab a chart or two, and send it out by email. Then when Yahoo bought Geocities, it gave us the opportunity to play with a web posting. I don’t know if you’ve been around long enough to remember, but you were literally coding in HTML, there was no Visual Editor, there was no WYSIWYG editor. You were writing code, so it would take 10 minutes to write something and then an hour to code it.
The day of September 11th, my office was in Two World Trade Center and I was at our Long Island office that day. I wound up getting a hold of my head trader and he gave me a full narrative for three hours while everything was going on, until one of the towers collapsed and the smoke cloud broke our cell signal. Everyone ended up getting home safe, we spoke about his experiences that night. I just wrote something up and posted it and it was insane: 50,000 hits in a few days and hundreds of emails from all around the world.
It was truly, truly one of those “Wow, this internet thingie is gonna be really big one day!” moments. Beyond everything with September 11th, just as an “after the fact perspective” I thought that, with the internet, as much as you think of it as this global interconnected thing, when you actually witness it first-hand in the face of a tragedy it was really, really quite astonishing.
The other thing was, I never seem to find the most recent draft of what I’m working on, it’s always either at the beach house or the office at my home or the laptop.
So I started just writing stuff and posting it, just so I had access to the most recent things, never expecting an audience to come along.
This has been live now for five years. I launched it in ’03. It wasn’t really a launch, it was like, “All right, let’s start playing with a blog and that will make it easy to find stuff I need later.” Hey, here’s a good way of keeping track of different things so that I don’t have to hunt it down in three different places – the office, the home, the laptop” – with the most recent version usually being where I wasn’t.
The Big Picture just grew and became this beast. It went from 5,000 page views a month to now, where we’re getting about 100,000 page views a day. It’s crazy.
Penn: Maybe by way of just wrapping up, let me ask you this. If there are one or two questions that people seem to be asking you the most right now, what are those questions and how are you answering them?
Ritholtz: Well, it’s funny because there’s a tendency among certain people to be skeptical, but in a wrong way. There’s a trading question I always get. There’s an economic question I always get.
The trading question is always, “So what are you buying now? The call on October 10th was a money-maker. What about today?” And my answer has been, “Well, I’m not buying anything now. Hey, there was a screaming bargain three weeks ago. Now that we’ve moved 18 percent, I’ll ride this position, but I’m not chomping at the bit to do anything else now.”
That always annoys people, like they’re looking for, “You were right last time. Hey, this guy won the game last night as the pitcher. I’ll bet on him as the next pitcher.” But I was up against guys that were easy to strike out. In between extremes are much more challenging time to invest and trade. So, that’s the one question on the trading side that keeps coming up.
On the economic side, we keep getting, “How bad is this economy gonna and how long is the housing problem gonna last?” The answer to both of those is that the housing problem is going to last for years. You’re maybe halfway through a correction where we’re down 18 percent nationally. Prices are still way too elevated compared to median income, price to rent ratio, inventory. We’re still another10 or 20 percent downside. Or, as someone else pointed out, you could just let inflation do its thing and prices can stay the same for 15 years and that’s the same as being down 25 percent tomorrow, or somewhere in between. So that’s the housing thing is the other question.
Penn: It’s easy to see why that one would be high on the list.
Ritholtz: I think we’ve been in a recession since January of this year (2008). That was mild and last month it took a turn for the worse and now we’re entering a much deeper recession. The odds are that this is going to be protracted and prolonged based on what we see from manufacturing and housing.
Those two industries are telling us – not coincidentally, both having issues with credit – that this is going be a substantial recession. One and a half to three years in duration is not a ridiculous forecast. In fact, that’s easy, that’s a cheat because really all you have to do is go six more months and by traditional metrics, the worse of the employment is just starting. We’ll see the employment data on November 7th and I’m expecting a really ugly number. (Editor’s Note: The jobs report on November 7th was, as Barry anticipated, worse than expected.)
Penn: Interesting. Is there anything that I didn’t ask you that you wanted to make sure we included in the piece that’s coming up?
Ritholtz: I could just tell you all the websites that people could go look in. If they want to go to the blog, it’s now at Ritholtz.com. We’ve set up a couple interesting things and we’re running a lot of different videos, as well as a number of interesting guest posters, guys like John Mauldin, Mike Panzner, Prieur du Plessis and Marion Maneker. It’s just a really, really interesting collection of people that are working with me on that.
There is also the quantitative tool that we developed, which we’ve made available online. It’s at fusion-iq.com. There simply isn’t a quantitative tool of this complexity and power available to individuals anywhere. It is $40 a month, but you couldn’t just go out and buy this, if you wanted to buy this, at any price. A lot of the big hedge funds spend millions of dollars developing their own tools and some of them are really good systems and really good quant models. But this is a very, very powerful system and at the very least, we think, it will keep you out of trouble if you pay attention to it when on individual stocks, it starts warning.
It generated sell signals on AIG at 75, Bear Sterns at 100, Lehman Brothers at 30, Fannie Mae 40 and all the big banks and brokers long, long before they collapsed. Had you paid attention to those sell signals, you really could have avoided a lot of headaches. We think that’s very worthwhile. That’s fusion-iq.com.
Penn: Great. It’s been very, very nice to talk to you, finally. Keep up the great work.
Ritholtz: Well, thank you for your time. I appreciate it.