Jeff is traveling, so we are republishing his recent interview from the Kirk Report, one of our featured sources. The Kirk Report is an excellent investor resource, with many specific stock ideas for members. Charles Kirk also reads very widely and provides regular links to articles we might otherwise have missed. He came up with some excellent questions for the interview, getting Jeff to discuss many topics he has not covered on "A Dash."
Here is the Kirk Report interview:
It is with great pleasure to have Jeff Miller, from A Dash Of Insight, to participate in this month's Q&A. Many of you know Jeff because I've linked to many (if not the vast majority) of his blog posts.
In this Q&A we'll cover a variety of topics that will interest and help you. Also, due to the length of this post, I also recommend that you print it out separately and read offline at your own convenience. Enjoy!
Q&A With Jeff Miller
Kirk: Welcome to the Q&A! You've been among the blogs I read for some time now and I frequently enjoy your perspectives. I'm excited to introduce your blog to my readers that may not have read your stuff before now and also to talk about your approach and background.
When and how did your interest in the market begin?
Jeff: I actually had some interest in the stock market, the way any professor or student of public policy or economics might have. I had that throughout my first career as a college professor and I did my analysis and used it to make some asset allocation moves between stocks and bonds. I basically believed, as most professors do, in the efficient market hypothesis.
This was interesting. When I moved from my first career to my second career as somebody who was working with options traders, I was asked by my old colleagues, if I still believed in the efficient market hypothesis and, of course, I had to answer that I did not. If I did, I would have no business working in the markets.
My interest began as a professor, but my deeper interest came simply when I changed jobs. On October 1, 1987, in a spectacularly ill-timed move, I left the safe world of the academic and went to work for a group of market makers at the Chicago Board Options Exchange. The people at the CBOE like to talk about people with skin in the game. Well, these guys really had it. Because they’re trading their own accounts, they are highly leveraged positions all the time. They might have $50 or $100 thousand in an account to start the year and they’re expected to, not only to pull their income out of that but to grow the account.
During the early 80’s some people were spectacularly successful including many of my friends and a couple of former students who came to me saying, “look Jeff your quantitative work in the academic world and for the State of Wisconsin is falling on deaf ears. You’re not really having the impact you’d like to have. Meanwhile, we’re all getting rich down here in Chicago. You can help us, your work will be used and you’ll make some money at the same time.” Some were also impressed by some forecasting models for football and baseball, an interesting hobby.
I’d resisted this for several years because I really did want to make a difference in the public policy world. But the wrong result in an election, loss of some of my key contacts (I had aspired to be the top public policy analyst for the state of Wisconsin, running a research shop in the Department of Revenue, where you actually had an impact on tax policy) made it clear that that dream was not going to be fulfilled for several more years. I finally went to Chicago. So my interest in the markets began in the academic world and thrived when I made this career decision.
Kirk: Tell us more about your professional and educational background?
Jeff: I started out thinking that I was going to be an engineer. I say on the blog that it’s the OldProf’s blog. Even though I have a teenage son, I have plenty of …..experience. When I was back striving to be an engineer at Purdue University we did wear our slide rules on our belts and the Freshmen wore green beanies. My first calculator was purchased when I was in graduate school. It had 2 memories, five functions, and was about 4 inches by 7 inches by 1 ½ inches thick. It cost me just under $100, my price point. It was one of the most valuable things I purchased that year, a real electronic calculator. Now you can get one for free.
Every aspect of my education helps me today. I am just going to mention one thing from the engineering days that helps. When you used a slide rule you couldn’t just plug things in and get an answer, you got a number with two or three significant digits. You did not have a false sense of exactitude. You had to know where the decimal point belonged. You had to have some idea of the problem you had to analyze, and what order of magnitude of the right answer was.
People have just become clueless about this and that’s part of the problem. When you get an answer out of a computer or model, they think it's right because it came from the computer, when in fact the modeler or the operator of the computer may be making a big mistake. You have to start with some knowledge of what you expect your answer to be.
Anyway I started out to be an engineer. It was the Vietnam era, times were troubling, and somewhere along the line I decided I was more interested in political science and economics and law. I switched to Bowling Green where I got a debate scholarship. We managed to finish fifth in the country my senior year as a debater. (I later coached the Michigan team to a similar level). I thought I was going to law school, so I applied to some law schools, but the political science professors said to me that I should instead apply to graduate school. Not looking for the safe school here, I applied to the Woodrow Wilson School at Princeton. They accepted a handful of people, not including me. I applied to the University of Michigan where they looked around and spotted somebody that despite not doing well in a few subjects like French, was a person who had extremely high quantitative aptitude. This was the era in which social sciences were striving to be quantitative analysts, so their program was heavily geared in that way. They made me an extremely attractive offer and I decided that I was going to go pursue my study in political science.
Off I went to the University of Michigan. Culture shock, big bounce from Bowling Green. Spent all of my time in the library in the Rackham Building. I did enough of it so that I got another honor while I was there, something called a Rackham Scholar. I had a pretty good four years at University of Michigan.
I didn’t quite have my Ph.D. by the time I left, but when I went to the University of Wisconsin in Madison to teach, I finished my Ph.D. at the end of my first year. In those days there was a requirement that you had to finish your Ph.D. within 7 years of starting graduate school. The average length of the time it took was 7.3 years, so you can see there were plenty of exceptions. I think there was one person in my entering class who got done faster than I did, a guy who is a real star.
It was just a completely enriching experience. I learned more things about conceptualizing problems, realizing how much there is to know. This is a big mistake for investors and most pundits. They think they have all of the answers, instead of realizing they are involved in a continuing quest.
I think I may have related this experience on the blog at one point. You study classes for a couple of years, and then before writing your dissertation you have to take preliminary examinations. What you do is in getting ready for your prelim is to write down everything you need to review, to read and check again (it’s a big list) before you’re ready to take your exams. I started reading everything on this list for the exams. If you delay too long, faculty members change. There are different people on the committees. Contacts in the courses change. Therefore, you find you have to add things to the list and do more. As I scratched things off the list, one might think that on the day of my exams the list was the shortest. In fact, it was at its apex because every time you read an article and you learned something in that article, you realized there are three or four more things that you absolutely had to know about before you take the examination.
There are so many people in the investment world who scoff at people who have Ph.D.’s or who are academics. They think that you don’t know anything or are impractical, and of course, some of them are. I had colleagues that were totally impractical. I had one colleague didn’t even know what a linebacker is, and he lives within 30 miles of Green Bay! He is a brilliant scholar.
What my investment colleagues don’t understand is that this is receptivity to knowledge and information -- looking for a way to use it and apply it is valuable. When you go to a grad school and have great professors, as I did, that is what you learn to do. I learned to analyze public policies using strict quantitative research methods and this meant studying things in data analysis using programs like SPSS. It meant doing simulations It meant learning how to model from leading authorities in causal modeling and social sciences. We looked at public policies and tried to analyze the various impacts.
That may not seem too relevant to the stock market, but these are exactly the same skills one needs to analyze most questions that come up in the investment world. Most people in the investment world now have taken short courses where they learn how to run programs, but they really have not done the hard work in doing the statistics, research methods and modeling.
My professional and educational background as a professor trained me pretty well to do a certain kind of analysis. I went to the University of Wisconsin to teach and I also was loaned to the Department of Revenue. There I actually got to work at an actual government agency and interact with bureaucrats. I got to see high level policy makers attempting to influence the outcome of studies that were being done within the agencies. I got to see the difficulties of speaking truth to power, and how decisions really get made. That of course, was an education as well.
I did a lot of consulting work in those days. I was regarded as one of the leading experts on Wisconsin’s very complex system of taking income tax revenue and sharing it in reducing property taxes for various communities. It was a very complex formula that basically helped poor communities and didn’t do much for wealthy communities.
Whenever anybody had a proposal, like getting a new business, they would call me in to see what the impact on their property taxes was going to be, whether increasing their tax base was going to really help them. It was interesting consulting work. I did things like studying the impact of the big Exxon mining project in Wisconsin. I worked for the city of Milwaukee and the Alliance of Cities. I studied the incidence of all of the various Wisconsin taxes as part of the major Wisconsin Tax Burden Study. I wrote papers and presented them to the Wisconsin Expenditure Commission at the time when they were looking to cut their taxes. It was a lot of quantitative public policy work at a point where the state was making some crucial decisions. It was at a point where I thought that the state was making a wrong turn, that I got this offer to join my friends at the CBOE and I went ahead and made that decision.
Kirk: So how did you learn how to become an investor?
Jeff: Well, of course I didn’t start by becoming an investor. Since I went to the CBOE, I started by learning to be a trader. I was the professor who was supposed to come in and read the theoretical literature, because the options traders realized that the options models, no matter how brilliant they were, and there was Nobel Prize winning work, did not apply in many of the situations that the people really faced. This was especially true after the crash, which happened three weeks after I started work.
I was asked to do things like adapt the existing options trading models to account for eccentricities, and factors that were not listed. Without getting into a lot of boring detail here, I’ll just say that one of these was the ability to exercise index options early, that is before expiration. There was this anomaly where options continued trading for 15 minutes after the stocks quit trading. Meanwhile companies thought the market was closed, and frequently made announcement between 3pm Chicago time and 3:15pm. So the futures and the index options would react dramatically. Depending upon the position you held, you could do an early exercise of these options, trade futures against it and lock in a tremendous trading advantage. This was one of the factors that I had to account for in models that you won’t find in any of the books.
The other thing is there were a lot of deals, being either a merger or spin off. The options would trade and the options would carry with it paper to do something else. It became a complex position to figure out how that paper actually affected the value of the options. So that was another thing I was asked to look at. I did forecasting of volatility. I also did the class for Beginning Options Traders. Every day after work when everybody else quit and did something else, I would trundle into this room with all the new options traders that were brought in and I would give them the textbook lesson in options trading. They also would get on the floor with our floor traders, and they would get the floor trading lesson. Some of them would also work as clerks as kind of an apprenticeship in the world of big time and big money options trading. I did not get paid for giving these classes. I had a deal and the deal was that I would get a piece of the action of the traders that came through. And of course, most traders did not succeed. But finally, one of the traders succeeded and succeeded in fine fashion and that proved to be the down payment for my house in Naperville, basically earned in my after hours at the CBOE.
Kirk: Please tell us a little bit about your firm New Arc and what you do there?
Jeff: After working with some firms at the CBOE for a while, I started my own consulting business. I did various kinds of research and analysis for clients on each of the trading floors in Chicago. I think a lot of folks don’t realize, Chicago had the Board of Trade, Chicago Stock Exchange, and The Merc as well as the CBOE.
There have been some mergers since then, but at the time there were four different trading floors with distinctly different products. At one point or another I analyzed futures, stocks, options, options on futures, Eurodollars, and many other products on these floors.
My typical client was a “local.” This is someone who trades for his own account, making markets and providing liquidity. He may have had an idea for a trading system, or just a question he wanted explored. My business was working on forecasting models that would help these traders.
I did some of this work in the early 90s, and along the line I networked with other people doing financial modeling. One of the people that I met was Vince Castelli. I actually met him online. It was in a forum where of people were talking about their methods. Most of the people really didn’t know anything, but you could spot somebody who did. Vince and I spotted each other and started interacting.
I was a good modeler and my forecasting methods had pretty good results, but I could tell that Vince was something really special. Vince was a career, civilian Navy scientist. He went to work as a scientist for the Navy right out of college; they sent him back for his Ph.D. in Chemistry. He eventually became head of something they called “The Innovation Center” where he worked with specialists in many different fields and tried to pull together their ideas to help the Navy do advanced Top Secret weapons systems.
Of course, he couldn’t talk about them, but he was written up in Popular Science a few years ago. When you see the small drone aircrafts all flying together and cooperating on a mission -- that was Vince’s idea. In the Gulf War when you saw bombs going down chimneys, these are the kind of things that they worked on. They did things like helping to make our ships invisible to enemy radar. That was in a different era. Now we seem to want to show the ships to show our enemy that we have a presence, so we want to be visible to enemy radar!
That is what Vince did. He had a characteristic that was similar to mine. I, in public policy, worked with people in a variety of different disciplines and wanted to get the best out of everybody based on the knowledge they had. I had respect for everyone’s knowledge, as long as they were in their sweet spot. Vince did the same thing. He had physicists, chemists, mathematicians. He brought them all together because all of their skills were necessary. He was a genius in his own specialty, but he was also a genius in bringing together the work of others.
For fun, Vince would go out to the beach with a stack of journal articles and take the mathematical approaches that he used so successfully in his scientific career and apply them to trading. He was one of the early neural network and genetic algorithm gurus. What he would do instead of starting from scratch to make his own program, was to buy not just the program, but the source code from the developer. He would tinker with the source code and make it come out the way he wanted.
Vince is a genius, but he is also a regular guy. If we were sitting here talking with us, we would all enjoy the conversation. He is an unassuming, genuinely friendly and helpful person, and a tremendous colleague for me. We fit because Vince was a modeling developer who had done some trading and I was somebody who had done some modeling and developing, but I had much more involvement with trading skills and contact with people in that community. We are a good fit.
Together we started NewArc Investments with the idea that we would take these powerful, modern trading techniques and make it possible for the average investor to join in. We had developed some of Vince’s systems and offered them to traders, and traders always would seem to mess it up somehow. If they did exactly what they were supposed to do at the end of the day, they would have made a lot of money. But instead, what they did was take our trading signal as if it were a recommendation. If they agreed with it they followed it and when they didn’t, they didn’t. Of course, all that meant was they were doing their own trading and they weren’t really convinced when we showed them that they would have done better had they blindly followed the model.
I learned a lot from this. I learned if you’re going to follow a method you have to have confidence in it. You have to study the method and test it in a way where you are sure that it will work. You needed to have done enough the right simulations. When I have one of Vince’s simulations in front of me, I go back and I review each period. I ask myself, “ How would I have felt during this period of time?”
Our early models had “knock your socks off” returns, but they also had huge draw downs. I said to Vince, “At this point we just lost all of our customers, we don’t have a business anymore.” So, gradually Vince was persuaded to develop models that had lower levels of risk but also lower levels of return.
One of the things that happens when we go out on road shows is that the models do not have the huge returns that investors expect from simulated trading. They are used to people that back fit data and come up with eye-popping numbers. Part of our problem in marketing is that we have an honest method. We present something that actually is similar to what we would really do in practice.
It turns out that the people evaluating these things are so jaded from what they’ve seen, they don’t understand the difference. It was a good honest way for the two of us to operate; perhaps it wasn’t the best marketing approach.
Vince has been a wonderful business partner, a tremendous asset, and also a very good friend. We started with a Sector Rotation Model that was his approach to things.
Some investors wanted to put everything in our Sector Rotation fund. I would not permit that since there was not enough diversification. It was far too risky to be a single holding. Investors asked me for a complement, something that would have a longer time horizon and trade on fundamental valuations rather than Vince’s models.
In response I devised a program. I looked at what I had been doing quite successfully for my options colleagues for the last several years. I reviewed the method to look for possible improvements. I found one serious flaw. People were always asking for a stock pick. They always wanted a “double your money stock,” looking for the home run. I saw that I had a good system if I stayed with the basic analysis.
We called this the Great Stocks Program because we chose great companies, with great management, trading at a great price. If you have all three, you have a great stock.
I had a modest objective. I would look for a stock that I thought was undervalued, had a catalyst, and had the potential to double in maybe 3 years. Anybody who was looking for more than a 24% annual compounded growth rate was being too greedy. I didn’t pretend that was what I was really going to accomplish and I haven’t, but that was the target.
When you set a reasonable target you find yourself in more reasonable stocks. Well, by golly, it worked pretty well. At the start of this year I had a ten year record where the S&P 500 was up 2 ½% on an annual growth rate and I was up 10 ½%, beyond what I ever could have expected at the start. This is a long-only program, and we have had a tough year. It is a challenge, but we have many stocks that we like right now.
We have two different programs, our Great Stocks program and the Vince method. The Vince model basically looks at sector performance and attempts to spot a trend and extrapolate on the trend. Over the years we have changed the definition of sectors, and Vince has upgraded the model.
It has now morphed into what we call the TCA/ETF Model. Instead of defining our own sectors we are now looking at ETFs because that is where the action is. The T is for the trend, a classic element in the analysis in any sort of system, going back to Richard Dennis and the Turtles and even earlier. People look at time period A, and extrapolate that to time period B. The key is in the use of signal-to-noise ratios, having filters that give you the right signal information. You must also determine period length and whether to stop out your position at various points. There are many variable to play with, and that is a trap. It is easy to back fit a model and make it look great. The problem? It will not work!
About eighteen months ago I challenged Vince to come up with a new version of his model. It should be more robust and quicker to find entries and exits. He went to work on it with one data set and one target universe. To his trending approach he added a new element. He recognized that some stocks had cycles, and when he saw a down period in the cycle and it started to rebound, he found a way of capturing that.
And then I said we needed to speed up the signal. We need the moves to be faster, so he put in a smidgen of Anticipation. Thus, Trend, Cycle, Anticipation: TCA.
When he got done with this, I took Vince’s work and I applied it to a totally different data set that he knew nothing about. Our staff back tested it on that data and verified the results. I also called in an outside consultant and asked him if he would look at it and offer any advice. The consultant’s advice was that this was a wonderful model, and there was nothing major that he could suggest. The only question was how it fit with an overall portfolio and what else you might do with it.
That is sound testing. We did not let the developer have all of the data, and we tested it every way we could once we actually got the model from him. That model is the basis for one of our programs. It is the TCA/ETF model, but we still call it the Vince model. The Great Stocks program, which is the one that I’ve done so successfully, we call the Jeff model. We have had a friendly competition over the years, but both programs have beaten the benchmarks.
Kirk: Your firm's motto is "superior returns with less risk." I think we all strive to achieve that, so without giving us your entire secret, how generally will most investors be able to accomplish such a thing on their own?
Jeff: Well, in the Vince model, we currently are reviewing 57 ETFs (we’ve changed the definition of the universe a little bit). I’ve put delayed rankings on the blog each week. I am not promising to do that forever but there has been some interest in it and it has gotten some inquiries into our methods.
The “less risk” comes when the market really turns south. The Vince model gets us completely out of the market and even can get us short the market. And so in a period of time, especially like October, we were pretty much out of the market in mid-September and through October for this fallout.
In our long only funds, we were out and in those accounts where people were willing to have a holding in an inverse ETF, they actually were profitable during this period of time. So that’s a way of controlling the risk.
In the Great Stocks program, the risk control simply was that I had valuation metrics. I had significant cash in these accounts in the 2000 era. We didn’t make as much in 1999; we didn’t lose as much in 2001. From time to time investors have asked why I am not fully invested in this account, since they see it as kind of a fully-invested stock account.
This year has been a different problem. We’ve suffered big losses this year, like most long-only managers have. If our risk metrics had given us a higher reading of risk, then we would have lightened up on some of these positions. There are some who question why long-only managers “did not see this coming.”
Let me just say, that anybody who is a professional investment manager, saw this coming. I was warning my clients about the problems in the housing market several years ago. I think the key problem in prediction and how it was all going to play out happened in mid-September, when the government unwisely decided to let Lehman fail and we started seeing what counter-party risk is all about. It is something that I had written about on the blog in some length.
Then, of course, when the government succeeded in a bail-out package, the question was how quickly it would be implemented and how could they restore a normal credit market. The credit markets froze up for five weeks, and the result of this was businesses quit investing. Nobody would give any positive guidance on earnings. Individual investors watched the stock market decline, and there was a lot of forced selling from hedge funds - hedge funds that were tremendously over-leveraged. They couldn’t sell their illiquid holdings in early stage companies or whatever debt security they had, so they sold holdings they had that were liquid, like CAT and AAPL, (two of my stocks) Anybody who was thinking about buying these stocks, watched repeated forced selling, mutual fund redemptions. Their decision?
What’s the rush? Take a huge step back and wait and see. Decide when it’s all ended. We’ve had this event where, if you look at these stocks, they are not going down in a way that suggests that there is a distinction or careful stock by stock analysis. I am experienced and doing these comparisons, and the pattern is quite telling.
There are many stocks that are down with the pack for no particular reason. What I am doing for my clients is looking for cases of stocks that are not really sensitive to the economy but they’ve gotten sold off anyway, or stocks that are super-levered to the economy so if things look a little better, they will bounce back more. Those are two main classes. There are a lot of good candidates like this out there. Those are the things that are on my own agenda right now.
What happened is a once in a lifetime event and people who are professional investment managers are not going to sit around trying to predict these. I understand that there are a couple of famous people that are getting a lot of publicity because they predicted that something would happen and it would be very bad. That’s fine, I mean every person has his day in the sun. Let me just suggest that looking at choosing their investment manager by who did best last year are following one of the worst methods. It’s another aspect of this chasing performance.
We try to get superior returns with less risk. Up until this year, we have always had much less risk. This year our Sector Fund succeeded much better than our Great Stocks program. If I had to predict which would do better next year, I would not use this year as a basis.
Both are still way ahead of the market on a long term basis and we still have tremendous confidence in our programs.
Kirk: Your firm's website suggest there are three steps to a great investment - 1) What to buy (find great businesses, great management, & great prospects), 2) When to buy (a "great company is a great stock only if it can be acquired inexpensively") and 3) When to sell (when the fundamentals change or the stock rockets to the top of your range.). Let's talk about each of these steps more in detail. First, what are some general guidelines to how investors should figure out what to buy? If you can provide an example of something you've bought recently and go through the steps and factors leading you to buy it, that may prove helpful for us to understand this step.
Jeff: You’ve asked for some current examples and the problem is there are so many things on the list right now that are good things. You could find many good things that are cheap right now. I will give you an example of a recent stock that I bought—ResMed (RMD). ResMed does the breathing equipment for sleep apnea and they do home sleep study tests. Sleep apnea is a very troubling illness, people don’t realize how serious it is. It affects their heart. It can cause them to fall asleep at the wheel. It can cause all sorts of deaths. Three and half million people have been diagnosed, but there are probably 35 million who have it. ResMed got approved for a home study test. If you go to your doctor for a sleep study, it can cost about six, and I don’t mean Motel 6. It can be $6,000 for one night to do a sleep study. Obviously when it costs this much to get tested, it’s hard to qualify and get the equipment and so people suffer from the disease.
Kirk: Once you figure out what to buy, the next step is to buy in at an attractive price. How should investors go about figuring whether a stock is cheap enough to justify the risk?
Jeff: When the ResMed kit got approved, the stock popped to about $48, it sold off with the rest of the market. It sold off down to the $35 range. The company had a recent conference call where the executives basically said that they don’t see that they are being affected by the economy at all. If they have a product and they are qualifying for insurance, and are expanding insurance programs and it’s something that by people being treated, it saves bigger expenses and other illnesses. Eventually in any sort of health care program, this is a winner. It’s basically trading at a huge discount right now. When we quit seeing forced selling, it’s going to come back right away to a more normal valuation and move higher. That is an example of a stock that we bought recently, and without going into the exact metrics, and that’s the rationale.
Kirk: Finally, your firm's approach seems to be long-term in nature (i.e. only selling when the fundamentals change or when the stock rockets to the top of the range.) Can you provide an example of something you've sold recently and the specific factors that motivated you to sell?
Jeff: One of our recent sales is DNA. We held Genentech and we got a big gain out of it. We looked at the potential Roche bid. We realized that the bid might be in some kind of jeopardy and it no longer met our criteria of a potential double in three years. All of a sudden we were in the risk-arb business, that’s not our business with the Great Stocks approach. That’s an example of something we sold when it did well.
We also sell things when they are not working. I have to say, at one time I held GM as a positive play on the economy. It’s been a while back, we sold it, around $30 or so. We have never held a stock that went bankrupt, at the time it went bankrupt. For example, Lucent almost went bankrupt, I think we sold them at $120, pre-split. We sell things that are mistakes. If it looks like it can go to zero, we get out. If it moves up so much that it hits our price target, then we also get out.
Kirk: In your analysis, what information and indicators do you place a great deal of emphasis on?
Jeff: In the Great Stocks program, we look stock by stock. We look at the forward earnings on the stock. We look at what the analysts think. We consider whether or not we think the analysts are right and how many of them are on board and recommending the stock. Then we look at our own target for what we think it should be and that’s our comparison. It’s not a complex method, it is description. The complexity comes from our ability to normalize earnings, look at the growth rate, go through the various analysts’ estimates, listen to what they are saying, and come up with something that makes sense of it all. In terms of the TCA/ETF model, (I can’t really go into the propriety details, obviously) it looks at trends and it doesn’t look at any fundamental factors. It looks at things where most technical analysts would look at the sector and say yes we think this is an important technical factor. Vince has taken concepts that others would agree are important technical factors. He has found better ways to measure them and he’s found little wrinkles that other people haven’t seen and this is what gives the advantage in the TCA/ETF program.
Kirk: I know market analysis does play a role in your analysis. For example, please tell us more about "The Gong Model" and how investors could find it helpful.
Jeff: The Gong model is Vince’s creation to help spot market bottoms. We all know that no one rings a gong at the bottom so the name is a bit whimsical. Unlike most bottom-calling methods, the Gong has two stages. First, the hammer is pulled back. Next the mallet swings forward. It has a technical basis, but it is very different from other methods.
We’re very realistic about the gong. No such method is perfect. The Gong is more like an “all clear” signal after a storm. Risk and reward have moved into a more favorable ratio. We have our report that shows some test market bottoms called by the gong. As is the case with our other models we’re willing to show a realistic assessment of how they worked past.
Kirk: In your opinion, where should investors concentrate their holdings over the coming year?
Jeff: This is a good place to state our overall market perspective and current thesis.
We have already described a perfect storm of negativity, accounting rules, forced selling, and redemptions. This became a death spiral, a self fulfilling prophecy.
Normally when this happens buyers emerge and various levels. Asset allocation models trigger when stocks, bonds, real estate, and commodities get out of line. Something has gone wrong here. It stems from an it rejection of information from all sources. The market community does not believe the government data, CEOs, stock analysts, nor any forecasts, especially those from models.
Without any of these normal tools, asset allocation becomes impossible. Since none of the normal tools or methods seems to work ever one is adrift.
Here is where I get to sound foolish, like anyone who has shown the tiniest spark of optimism over the last two months. It is mandatory to say, at least, that we are in for a long and painful transition. Perhaps.
Eventually this will all be corrected. There will be more clarity from economic data, from corporate earnings, and from stock prices. Cyclical stocks and technology will benefit the most.
Timing is difficult. I do not expect a confidence in earnings for several months. But the market will anticipate this change. That is why it is right to own stocks now. This is an unpopular viewpoint since it has not work, especially in the last two months. It is also the viewpoint of the many of the leading investment managers, people have long term track records, like us.
Kirk: In your opinion what is the very best way to learn how to become an investor?
Jeff: I think that there are several steps.
The first is to realize how difficult it is to get market-beating performance. Most people are deceived by TV commercials into thinking that their current advisor is an idiot and they could do better on their own.
Even if one has the time and the inclination, most do not have the necessary training and skill. Most do not have realistic expectations, especially when it comes to possible losses. When things go wrong, it is easy to get discouraged.
As a result, I think that most individual investors should get a trusted advisor, or choose a passive investment method. They should occasionally do some reallocation of assets, with their own needs in mind.
Those interested in stocks should set aside some money for their own trading, and expect it to be a source of fun as well as profit. Discover whether you really enjoy learning about investments. Only if you succeed through some changing markets should you step up your size. Do not get over-confident from a couple of early successes, especially if you took big positions.
Quite frankly, Charles, your site is very helpful in teaching about stock-picking. I do some of that, but focus more on understanding government, economics, research methods, and interpreting data.
The biggest mistake of many is trying to digest too much information without real confidence in what they are reading.
Kirk: What is LINQCRED?
Jeff: I don’t know if this is going to catch on or not-- probably too many letters for an acronym. But the idea is to get the average investor thinking about information. Frankly, most of the available information is very poor. And the blogosphere has had mixed results for investments. On the one hand there’s so much more information, but it’s had kind of a democratizing effect – in other words, the average investor cannot tell what is useful and what is not. I’ve had some people call me up and talk to me about brilliant writers on the stock market. If you actually read a paragraph of their work anyone who understood the subjects could tell they don’t really have an analytical skill. There is an opinion that is stated over and over again. And if the opinion turns out to be right a bunch of people will think they’re brilliant. You need to have some ability to decide what you’re getting out of information.
LINQCRED begins with paying attention to what you are hearing or reading.
When I write about political events this problem is the toughest. If I’m trying to write about what’s likely to happen in Congress, when the Democrats might try and push something through about economic policy, I might refer to an interview with Barney Frank. And why not? He’s one of the smartest people in Congress and the 6th most powerful. When it comes to anything dealing with the bailout crisis and you want to sit back and be a dispassionate analyst, you need to know what Barney Frank thinks! And probably you ought to listen to Nancy Pelosi and certainly President-elect Obama. But whenever I cite these sources I get several emails and comments from people who just plain don’t like these politicians. They don’t share their political views. And because they don’t share their political views, they will say to me “you can’t trust Barney Frank because he was involved in shenanigans in Fannie Mae.” Now, what that has to do with the bailout and what that has to do with when a bill is going to come up in his committee and the prospects for it, I fail to see.
One of my colleagues at Real Money said that Barney Frank would say anything to get votes. It’s like when I taught political science and young people would come in basically knowing nothing about our political system. They have a very superficial view that they got from the movies or something: that everybody in Congress was just pandering for a vote, that every politician would to anything to get one, that votes were bought and sold through contributions. And of course, whenever you have a view like that there’s some element of truth with some people. But let’s get real – Barney Frank? Can you spell S-A-F-E S-E-A-T? The guy who is saying this knows absolutely nothing about the legislature. Barney Frank has a safe seat. If there was ever a person who wasn’t out there trying to cast a positive image of himself, it would have to be Barney Frank. The commenter is a respected colleague of mine at Real Money. His analysis of the stock field where he specializes is great (in fact I read it all the time), but this guy is stepping out of his sweet spot and letting his political views cloud his analysis. I took, as a grad student, one course in legislative behavior with a brilliant professor who was much smarter than this guy offering the opinion. Each week in this class we read two or three books and about six journal articles, and we did it for the whole term. Now what happens when people say there is nothing to be learned about the legislature, and that they know everything there is to know about Congress, is that they are just not showing respect for smart people with a different background and perspective. It doesn’t make them smarter to scoff at this. So the first part about LINQCRED is always to listen. Listen to other people and listen for new information they might have. The important thing is to keep an open mind.
Next is novelty. Is it really something new? Is there new data, or is it something we’ve been hearing over and over again. Then you might look at qualifications. People occasionally say that I emphasize credentials too much. They say that because I look to people who are knowledgeable about things. Surprise! They often have substantial credentials. Quite frankly, I’m not too impressed by a guy who has no knowledge of legislative behavior who is trying to tell me what he thinks Congress is going to do.
Or I have people telling me what they think President Obama is going to do based upon some campaign speech he made at the start of the campaign. Situations change, competition changes and if you aren’t capable of analyzing this you should just be quiet, but people don’t. They are all out there talking. It is the difference between opinion and analysis.
Now we have CNBC with a new feature in which they put up to 8 people in a box. We sit there in the office, we put it on mute, and we ask how many of these people actually know anything about what they’re talking about. In fact, most of them are journalists. Instead of doing journalism, bringing out the information and opinions from experts, they have now started giving their own opinions. The effect on the average viewer is dramatic, since the entire tone of the discussion is influenced.
We see the same thing in the democratizing effect of the internet, where every blogger is equal. It is now extending into main stream media as the main stream media bloggers start writing and pitching for an audience. If you are going for ratings, you say different things.
Charles you have a wonderful audience but you do it with valuable content, not opinion. I try to do the same.
Kirk: On your blog you've talked about a prominent logical fallacy - "Post hoc, ergo propter hoc." Can you explain what this means and why it is important for investors to understand this?
Jeff: On the blog I go into various common investor mistakes. I picked this up somewhere between high school Latin and studying critical thinking in college. It really goes deeper into the question of causal modeling. When most people see two things happening at the say time, they infer causation. It’s natural. Our minds are so powerful, we see things happening. My favorite example occurred when we had a guest in our home once. We had a family room with a small powder room. Our guest went into the powder room and flushed the toilet. As she flushed the toilet, all the lights went out. Now it just happened that the power in the neighborhood went out at the exact moment that she flushed the toilet. She emerged saying, “What did I do?”
While that episode is a humorous, there are other examples in history. This is not a new human trait. There was an eclipse in the middle of a battle in 585 B.C. and the fighting stopped. Everyone thought it was an omen.
We think that everything must be explained. If the market moves 1% or 1 ½% in a day, there must be some explanation. People reach to explain things that coincidentally happen at the same time.
In the economic world it is even more difficult. There are so many economic indicators, and they are all moving at the same time in the same direction. It is natural to infer causation. In fact, they are probably different measures of the same thing. Here is a typical example.
Each month I look at the payroll employment report, the four week average of initial jobless claims, Michigan consumer sentiment, leading economic indicators, and the ISM report. My team developed a model that shows the relationship among these variables. But we do not think of it as one of them as causing another. It is called a spurious relationship. “Spurious” sounds bad in an English sense, but it just means that the apparent relationship between two variables is actually caused by changes in a third variable.
This is not a very high level of causal modeling, but it is far beyond what you read in the financial commentary. The highest level of analysis that I’ve seen anybody do in analyzing financial relationships is by pointing out that correlation is not causation. They might add that the causal relationship might be backwards.
If you took a class in causal modeling for about a week, you would see there are many possible causal models-- chains, spurious relationships, multiple causations. Readers of financial media and blogs think they are getting great analysis, when it's actually stuff you would learn in a week in a formal class in the study of that subject.
Kirk: You've said that the two biggest mistakes for individual investors 1) chasing performance and 2) asset allocation. Can you give us some common sense suggestions on how to avoid falling prey to both mistakes?
Jeff: There have been many studies showing that the individual investor gets about half of the return of a passive investment in an index fund. There have been academic studies and studies by the various firms. It happens partly because right now people have trouble estimating their risk tolerance. No matter how much risk tolerance you thought you had, this year has really tested it. At the time when astute investors like the Warren Buffets of the world are buying the average investor is selling. It is normal human psychology, fear and greed. It is underperformance through poor asset allocation and poor market timing.
What should an average investor do about it? One thing would be to find a trusted investment advisor. The problem is that finding a good advisor is a tough as finding a good mutual fund. Another approach is passive investing. This is better than yielding to one’s emotions.
Charles, I realize that we share an audience of people who are trying to become their own investment manager that’s why they are reading the Kirk Report. It is also why they read A Dash of Insight, but part of my message to them is you need to decide if you really have the right attitude and the time and the commitment to do this for yourself. If you do not you’d be better off taking a different approach.
Kirk: You have recommended a number of interesting books at your blog. If someone wanted to put three on their Christmas list this year, which three would you choose and why?
Jeff: I think everyone should read "Fooled by Randomness. Without this, you are doomed to infer that someone who was recently successful was a genius. Maybe so, maybe not. Everyone should also read something about behavioral economics, if only to understand themselves. "How We Know What Isn’t So" by Thomas Gilovich is an accessible example. The biggest immediate payoff might be from this one: "Profit from the Peak: The End of Oil and the Greatest Investment Event of the Century" by Brian Hicks. I haven’t posted my review yet, but I really like the book. It is done by journalists in a good way, bringing technical material to the average reader. There are stock ideas. The investment payoff from energy is likely to be very great, especially from current levels.
Kirk: Turning toward the market itself especially given your years of experience in the markets, what's your opinion about how the Fed and Treasury are doing right now?
Jeff: Given the nature and scope of the economic problems, both have done well. Should they have acted sooner? Of course. Our system of government is not good at anticipating and preparing for crisis situations. We need to experience it a bit before the political will develops. The Bernanke Fed acted much faster than the Fed has in the past, and it showed more imagination in finding solutions.
Kirk: Realistically, what do you think is the best and worst case scenarios we should expect over the next few years?
Jeff: The best case scenario is that the five-week credit crunch turns out to be a pig-in-a-python, not the start of something much worse. We will have to see how well the solutions work. If there are signs of improvement, we could see a rapid rebound of 25% or more, depending upon perceived future earnings and the market multiple. We will not see real evidence until next year, but the rebound could start earlier and stimulate performance anxiety.
The worst case is something like a Great Depression. That is the big play by those wanting high ratings in the blogging and media worlds. It has a low probability – a priori. It is even less likely since governments world-wide have been actively engaged and are not repeating the mistakes of the 1930’s.
The most likely case is a more gradual recognition that things are improving. My biggest concern is the unfortunate timing of the transition in government. The President-elect has correctly not presumed more power than he has, and the current President is trying to leave him flexibility. It is delaying some needed steps.
Most prominently is a decision about the rest of the TARP funds. My regular readers know that I am disappointed that the plan for price discovery has not been implemented. Paulson was forced to act quickly, and they had no ready plan for the sophisticated reverse auction that would be needed. It is still a good idea, and should be tried, at least as an experiment.
Kirk: I'm sure you come into contact with a wide range of investors. In your experience what are some characteristics you find in those who are the most successful? Likewise, what things do you find in those who are destined for failure in the market?
Jeff: I am going to combine this with your last question about one piece of advice. The successful investor has the following attributes:
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A Method
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Confidence in the method, either from testing, from experience, or the teachings of others
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The discipline to stick with the method, even when it seems not to be working
Mark Hulbert recently reported that the best performing advisory service over many years had the worst record in 1987. I think it was down over 60%. Even Warren Buffett had a streak of terrible years in the 70’s. Having said this, you really do need to test and confirm what you are doing.
Let me contrast this with those who struggle. I do not want to pick on technical analysts, many of whom seem pretty sensitive, but it is a much-abused skill. Many an aspiring investor thinks that a few hours studying some charts is the road to riches. The ability to draw lines and highlight past cases is very powerful and often very deceptive. I look at charts, and Vince’s methods use technical criteria. Having said this, most technical analysts do not have any real record of predictions or back-testing for their methods.
Despite this, people are easily convinced by charts and remain suspicious of models. We are so easily persuaded by what we think we understand.
Kirk: At this point of your career who do you look up to for inspiration and guidance?
Jeff: At my age, I am beyond mentoring. :) That would have been a better and more conventional approach to money management. I have a very deep respect for many colleagues and peers in universities, writing blogs, actively trading, or writing as colleagues on RealMoney. I also talk to people in government, including the experts who actually develop the data.
Kirk: A common element I find in all successful investors is that they are always working on expanding their knowledge and improving their strategies. What have you been working on lately in this regard?
Jeff: Because of my writing, I often get suggestions from others. I am always open to suggestions, and may even find investors who want to try a new approach.
Kirk: What are some of your personal passions beyond the market?
Jeff: Like most of us, I work too much. One of my outside interests is working with early-stage companies. I have helped them raise start-up capital and I am on a couple of boards. I have also worked as a legal expert in a few securities cases. My biggest hobby is bridge – not the tea and crumpets variety. Those who have never seen it would not understand, but top-level bridge is a different world. I occasionally give some examples on my blog. When I assemble a team of peers for a major tournament, we are usually seeded in the top 30 or so. Most of those ahead of us are either professionals or the subsidized national team from some country. The world of tournament bridge is also good for business connections. I also love sports, including doing a little modeling and forecasting. Baseball and football are my favorites, but please do not ask about the Wolverines.
Kirk: If you had it to do over again would you choose a different career path?
Jeff: The jury is still out. I miss working with students. I have a book or two inside, wanting to come out. Maybe I’ll get another stint at a university.
Kirk: Finally, if you had one piece of advice to share with all investors what would it be?
Jeff: Just in case I did not rant about this enough – cynicism does not equal wisdom. It is fine to be skeptical, to look for bias, and to challenge information. Nearly everyone goes too far in this direction --- way too far. It is what I call “light switch” thinking. It is far wiser and more profitable to get the best information from each source.
I am particularly troubled by the reaction to formal models. The criticism of models comes mostly from those who know nothing about them. I have developed hundreds of models for many different applications. Most of these were successful either in describing problems or making predictions. I have taken top-level classes in constructing models and I have taught such classes.
With that background, I find it interesting to read criticism of modeling from people who have never taken a class nor built any models. It is always dubious to criticize the relevance of experience that one does not have.
Criticizing the results of a model, as is now so popular in our analysis of complex derivatives, is a bit like criticizing a hammer or a forklift.
A model is a tool. It is no better or worse than the craftsman wielding it. And it is a poor craftsman who blames his tools.
Those who reject a model invariable substitute one of their own. It is an ad hoc, human model. It might go something like “All companies like about earnings. I am free to substitute my own earnings projections, based upon my own sense of economic prospects and how these relate to companies.”
This is a model, and a poor one. Unlike a formal model it is not carefully stated. It is not subject to testing. It permits the user to substitute anecdotes for data. That is when all of the behavioral finance problems, especially confirmation bias, emerge.
These seat-of-the pants models are far more common than the carefully developed ones. They are not tested nor are they recognized as such. That is why they are such a danger to the individual investors.
Kirk: Thank you for spending time with us Jeff and we appreciate your perspectives and look forward to reading your insights at your blog.
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