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You Can't Become Rich In Your Pocket Until You Become Rich In Your Mind | ||||
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Why do you believe the sectors proved so tradable?==== I assume that, nowadays, the NAV must change direction much more frequently. ==== Thats right. The next step in my evolution as a trader began when that pattern started to go away as most of these things eventually do. ==== The probabilities of a price change in the same direction as the previous day started dropping? ==== To some extent, but, more importantly, the high volatility started to disappear. During 1979 to early 1984, the volatility in these funds averaged approximately one-quarter to one-half of a percent per day. The daily volatility eventually dropped to only about one-tenth to two-tenths of a percent. Also, the reliability or persistency of the prices dropped from 80 percent to below 70 percent. ==== What happened when the reliability of the trend persistence and the volatility in the bond funds both started to decline precipi-tously? Was the method still profitable? ==== Yes, but the potential annual return in municipal bond funds began to look like about 20 percent. ==== And that was not good enough? ==== I really wanted to look for something better. I thought that if I were able to find profitable inefficiencies in municipal bond funds, then it was possible that similar opportunities could be found in equity funds. From the fall of 1984 through the spring of 1985, I practically lived at the local library, extracting years of data on perhaps a hundred mutual funds off the microfilm machine. I was looking for another needle in a haystack. I found that there were tradable patterns in equity funds but that the prospective returns were only around 20 to 25 percent per year. Even with higher volatility, the daily price persistency of about 60 percent was just not high enough. Through most of this research, I had ignored the Fidelity sector funds, because they charged a $50 fee per switch. I couldnt see paying this charge when there were-eo many funds that had no switch fee at all. Two insights really contributed to a breakthrough. First, I had found early on that commodity-related funds (such as the gold and oil sectors) seemed to work better than more broadly based funds. Second, I discovered separately that the technology, oil, and utility indexes were each significantly less random than a broad market index. I went back to examine the sector funds and was just amazed by what I found. I couldnt believe that I had ignored sectors during my earlier research. I had almost missed it. ==== What did you Find? ==== Generally speaking, I found that a price change that was larger than the average daily price change in a given sector had anywhere between a 70 to 82 percent chance of being followed by a move in the same direction on the following day. This finding was tremendously exciting because of the volatility in the sectors. For example, the biotech group moved an average of 0.8 percent a day and the gold sector an average of 1.2 percent a day, compared with the volatility of the municipal bond funds, which had shrunk to a mere 0.1 to 0.2 percent by that time. Therefore, I was applying the same batting average to markets that offered more than five times the profit potential. The icing on the cake was that the sector funds allowed unlimited switching per year, instead of the fourswitch limit applicable to most of the other funds. You could switch a hundred times a year if you were willing to pay the $50 fee per transaction. ==== Why do you believe the sectors proved so tradable? ==== Thats my favorite question. Not just because 1 think I may have an answer, but also because I have not encountered the mathematical explanation elsewhere. In researching the price behavior of individual stocks, I have found that significant daily price changes (with relative strength) have about a 55 percent chance of being followed by a similar directional move on the following day. After allowing for commissions and bid/ask spreads, that is not a sufficient probability edge to be tradable. Now, as an analogy, assume you have a stack of coins, and each has a 55 percent chance of landing on heads. If you toss a single coin, the odds of getting heads are 55 percent. If you toss nine coins, the odds of getting more heads than tails go up to 62 percent. And if you toss ninety-nine coins, the odds of getting more heads than tails go up to about 75 percent. Its a function of the binomial probability distribution. Similarly, assume you have ninety-nine chemical stocks, which on average are up 1 or 2 percent today, while the broad market is flat. In the very short run, this homogeneous group of stocks tends to behave like a school of fish. While the odds of a single chemical stock being up tomorrow may he 55 percent, the odds for the entire chemical group are much closer to 75 percent. ==== I assume that this pattern does not extend to the broader stock market That is, once you extend beyond a given sector, including more stocks may actually reduce the probability of an index persisting in its trend on the following day. ==== The key ingredient is that the stocks making up the index or sector are homogeneous. For example, Fidelitys leisure fund, which was the least homogeneous sector at the time, including such diverse stocks as Bud-weiser, Pan Am, and Holiday Inn, was also the least persistent of all the sectors. Conversely, funds like savings and loans and biotech, which were more homogeneous, also tended to be the most persistent. ==== How did you anticipate the direction of the daily price changes in the sector funds in time to enter a switch order, or did you just enter the order with a one-day lag? ==== I found that I could sample ten or twenty stocks in each sector and get a very good idea where that sector was going to close that day. This observation allowed me to anticipate the signal by one day, which proved to be critically important, as my research demonstrated that the average holding period for a trade was only about two to three days, with approximately 50 percent of the profit occurring on the first day. ==== How did you pick the stock sample groups? ==== Initially, I used the Fidelity holdings for that sector as indicated in their quarterly reports. ==== I assume that the holdings turned over infrequently enough so that this proved to be an adequate estimate ==== Actually, I subsequently discovered that this procedure was a lot less important than I thought. I found that I could take a sample consisting of fifteen stocks that Fidelity held in a given sector, and it would give me a very good estimate of that sector. On the other hand, I could also use a sample of fifteen stocks in that sector, none of which Fidelity held, and it would still give me a very good indication. As long as the number of stocks in my sample was large enough relative to the stocks in that sector, it didnt make much of a difference. ==== What percentage of your account were you betting each day? ==== One hundred percent. ==== How many different sectors might you invest in on a given day? ==== I traded one sector at a time. ==== Did you consider diversifying your money by trading different sectors at the same time? ==== Im not a big fan of diversification. My answer to that question is that you can diversify very well by just making enough trades per year. If the odds are 70 percent in your favor and you make fifty trades, its very difficult to have a down year. ==== How did you select which sector to invest in on any given day? ==== Imagine a board containing flashing lights, one for each sector, with red lights indicating liquidate or avoid and green lights indicating buy or hold. I would rank each sector based on a combination of volatility and historical reliability, which I call persistency. Essentially, I would take the brightest green light, and when that green light eventually turned red, I would take the new brightest green light. Very often, however, when one light turned red, they would all turn red. ==== And if they all turned red, you would then go into cash. ==== Correct, but I needed only one green light to take a position on any day. ==== When did you get involved in taking on clients? ==== Most of my clients today actually started with me when I was still trading municipal bond funds. I took on my first client in 1982. It made no sense to be borrowing at 15 percent from Phil Rizzuto at The Money Store when I could manage $ 100,000 of client money, share 25 percent of the gains and losses, and effectively be borrowing $25,000 for nothing. That was the point at which I decided to start the business. I still kept the second mortgage, though, because I wanted to trade that money as well. It didnt make sense to me to pay off a mortgage at 15 percent when I was making 35 to 40 percent on the money. ==== How did you go about soliciting accounts? ==== All my accounts were either friends or neighbors. For example, I would invite a neighbor over for a beer in the evening and say, Ive been doing this for a couple of years now, and Id like you to take a look at it. Some people had no interest at all and others did. Its interesting how different people are when it comes to money. Some people dont do any homework at all and give you their money immediately. Others wouldnt dream of giving you $10, no matter what you showed them. Finally, there are those that do a lot of homework and ask the right questions before they invest. Everyone falls into one of these three categories. ==== Which of those categories do your clients generally fall into? Obviously, one category is automatically eliminated. ==== Most of my clients did the type of homework mat I like. They asked the right questions. They told me about their tolerance for risk. ==== How large were these accounts? ==== They ranged from $10,000 to $100,000. ==== What kind of fee structure did you use? ==== I took 25 percent of the capital gains. However, I guaranteed to take 25 percent of any losses as well. I also assured each of my investors that I would cover 100 percent of losses if the account were down after twelve months. ==== Heads you win one; tails you lose tour. You must have been awfully confident to offer that type of guarantee. ==== What I was confident in was the probability of winning after fifty trades per year. ==== For how long did you maintain the 100 percent guarantee against first-year losses? ==== I still maintain that offer, but Ive accepted only two new clients during the past five years. ==== Given your performance, I assume that implies that youre no longer accepting any new accounts ==== I stopped accepting new accounts five years ago. I made an exception in these two cases because they were very close friends. ==== Why did you stop accepting new accounts? Did you feel there was a limit to the amount of money you could handle without it negatively impacting your performance? ==== Its not a limit to how much money I can handle but rather a limit to how much money may be welcome in the funds Im trading. Im very sensitive to any potential impact I might have on the fund manager or on the other shareholders who dont move as actively as I do. I prefer to restrict the amount of money I move to only a couple of million dollars in a fund of several hundred million dollars, so that the impact will be minimal. Also, I have found that when I enter orders, I often get a comment like, Youre getting out? Most of the calls were getting today are getting in. ==== What does that tell you? ==== It tells me that Im mnning counter to a lot of money thats being switched in and out; hence, the impact of my activities is not great. Ive also been told by fund employees that most of the people who do a lot of switching in their own accounts end up doing worse than if they had done no switching at all. ==== Did you decide to limit your size to a certain dollar amount in order to not rock the boat? ==== The most important factor here is my risk. Sharing 25 percent of both profits and losses is the exact equivalent of leverage. What I did not fully appreciate at first was the psychological importance of finding and maintaining a stable proportion of client money to my own capital. Actually, I prefer this proportion (or leverage) to decline over time. ==== Did you ever find yourself managing funds beyond your comfort level? ==== In 1986 I took on new money too rapidly. I found myself rationalizing taking 50 percent positions. For example, a green light would come on, and I would trade only $200,000 of a $400,000 account. I would think, Yes, Ill feel much more comfortable tomorrow having only $200,000 in. I soon realized that as a result of my caution, I was reducing my clients return by one-half. I decided that a better approach was to have fewer clients, if necessary, and to trade all of them fully. When I first cut back on the percentage of an account that I was trading, I wasnt aware of the motivations for my actions. In hindsight, I came to understand that I was really uncomfortable with the size of the risk. It wasnt just a matter of whether I won or lost the next day but also how I would feel until the verdict came in. I have a routine of internalizing how I would feel given what might happen on the next day. ==== That routine being what? ==== My approach is to confront losses even before they materialize. I rehearse the process of losing. Whenever I take a position, I like to imagine what it would be like under the worst-case scenario. In doing so, I minimize the confusion if that situation actually develops. In my view, losses are a very important part of trading. When a loss happens, I believe in embracing it. ==== Why is that? ==== By embracing a loss, really feeling it, I tend to have less fear about a potential loss the next time around. If I cant get over the emotions of taking a loss in twenty-four hours, then Im trading too large or doing something else wrong. Also, the process of rehearsing potential losses and confronting actual losses helps me adapt to increasing levels of risk over time. The amount of money Im managing is growing by 15 to 20 percent a year, which means that the dollar risk Im taking is increasing at the same rate. The best way I can deal with that reality is by being willing to feel the risk at each level. |
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