Trading Basics
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And speaking of Larry Hite, here's an excerpt from his book The Rule: How I Beat the Odds in the Markets and in Life—and How You Can Too (2020).
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You see, the first thing for any organism, for any animal, is survival. So cutting losses on anything gives the chance to endure. That’s simple math, simple physics, or whatever you call it. You must adapt. Not surprisingly, one of Larry’s heroes was Darwin because it was he who said it’s not the fastest, not the strongest, not even the most intelligent who survives, it’s the one who is most adaptable. You’ve got to live or it’s all over.But nice guys like Larry are often called evil speculators. They are painted as bad guys by the uninitiated and often jealous. Yet Larry is only saying, “Hold on, let me do my thing. I’m going to play by the rules, try to find an edge and stay alive.” And that perspective then gets ostracized because the masses want group safety, not novel ways of thinking for themselves. Larry has always been willing to trade the masses’ view of safety for his chance at a fortune.
More excerpt from the aforementioned author:
My early failures forced me to become comfortable with that failure and, more important, with loss, and this has become a foundation for my success. My early years also taught me about human fallibility. That’s why my investing approach is never based on predicting the future. (Hint: Nobody can predict the future!) I also learned there’s too much unknown, too much uncertainty, to make bold narrative predictions about where the economy or markets are headed next. My approach to winning is about understanding our human fallibility and reading people’s behavior so you can make smart decisions based in the facts of NOW, not in the unknown world of the distant future.
If you want to make money, don’t buy into hypes—ever. Watch the trends in the here and now. When you start following slick reports filled with predictions, you’re just finding out who has good copywriters. Wall Street’s investing and money-managing institutions use fabulous stories to sell their expertise to you, and they will run the same scams 1,000 years from now. You see, stories began at the dawn of human society to entertain and instruct the next generation. We are wired to learn from well-told stories. But, unfortunately, Wall Street preys off our basic human weakness to want stories.
But there is the reality for those of us paying close attention: Global financial markets are not best explained or traded by stories but rather by numbers (which are the only facts). Markets are the ever-shifting accumulation of cold economic interests competing for superiority within regulated legal systems. And many Wall Street stories are designed to obscure the numbers—the probabilities—behind real trends. I have a way of beating all of the stories. It’s a way of knowing if markets are going up or down—and it comes down to a comparison of two statistics. Numbers are not as exciting or as sexy as stories you hear screamed across financial channels, but numbers will make you wealthier if you use them in the right way.
Remember, in life, time rather than money is the most important currency, and we all have only a finite amount of time (at least until they figure out life extension). You can win money, lose money, and earn it back again. But time is something that you can never get back, so making good decisions with the odds on your side is the best way we can give ourselves more time, or said another way—freedom.
So how do we do that? By cutting your losses and staying with your winners. That is my rule for building wealth. Getting what you want is about learning how to make smart bets—key word smart. And making smart bets is about understanding basic probabilities. If I was going to get rich, I have to learn to trade in a way that would make a lot of money when I am right, and not lose too much when I am wrong. That’s why my thinking, my system, is based on controlling my risk to the downside so that I never lose all of my chips. In fact, I decide how much I can afford to lose and arrange my approach so that I never lose more than that. In other words, you can’t lose your shirt if you don’t bet your shirt.
People used to winning are far less likely to acknowledge they are actually losing. They will hang on longer to their losing bets. Because I’d been a poor athlete and bad student, it never surprised me that I would lose. I would quickly accept it, fold my cards, and move on to come back to play another day. I recommend you practice losing money. In the long run, that will help you win big.
My early failures forced me to become comfortable with that failure and, more important, with loss, and this has become a foundation for my success. My early years also taught me about human fallibility. That’s why my investing approach is never based on predicting the future. (Hint: Nobody can predict the future!) I also learned there’s too much unknown, too much uncertainty, to make bold narrative predictions about where the economy or markets are headed next. My approach to winning is about understanding our human fallibility and reading people’s behavior so you can make smart decisions based in the facts of NOW, not in the unknown world of the distant future.
If you want to make money, don’t buy into hypes—ever. Watch the trends in the here and now. When you start following slick reports filled with predictions, you’re just finding out who has good copywriters. Wall Street’s investing and money-managing institutions use fabulous stories to sell their expertise to you, and they will run the same scams 1,000 years from now. You see, stories began at the dawn of human society to entertain and instruct the next generation. We are wired to learn from well-told stories. But, unfortunately, Wall Street preys off our basic human weakness to want stories.
But there is the reality for those of us paying close attention: Global financial markets are not best explained or traded by stories but rather by numbers (which are the only facts). Markets are the ever-shifting accumulation of cold economic interests competing for superiority within regulated legal systems. And many Wall Street stories are designed to obscure the numbers—the probabilities—behind real trends. I have a way of beating all of the stories. It’s a way of knowing if markets are going up or down—and it comes down to a comparison of two statistics. Numbers are not as exciting or as sexy as stories you hear screamed across financial channels, but numbers will make you wealthier if you use them in the right way.
Remember, in life, time rather than money is the most important currency, and we all have only a finite amount of time (at least until they figure out life extension). You can win money, lose money, and earn it back again. But time is something that you can never get back, so making good decisions with the odds on your side is the best way we can give ourselves more time, or said another way—freedom.
So how do we do that? By cutting your losses and staying with your winners. That is my rule for building wealth. Getting what you want is about learning how to make smart bets—key word smart. And making smart bets is about understanding basic probabilities. If I was going to get rich, I have to learn to trade in a way that would make a lot of money when I am right, and not lose too much when I am wrong. That’s why my thinking, my system, is based on controlling my risk to the downside so that I never lose all of my chips. In fact, I decide how much I can afford to lose and arrange my approach so that I never lose more than that. In other words, you can’t lose your shirt if you don’t bet your shirt.
People used to winning are far less likely to acknowledge they are actually losing. They will hang on longer to their losing bets. Because I’d been a poor athlete and bad student, it never surprised me that I would lose. I would quickly accept it, fold my cards, and move on to come back to play another day. I recommend you practice losing money. In the long run, that will help you win big.
(Continuation from the previous post)
LOOKING AT THE ODDS
I embarked on a whole new learning process when I went to work for Jack Boyd at DuPont. Jack’s trading was not particularly scientific, but he had a interesting method. When he saw something move, he went in that direction. When it didn’t, he got out. He did not call himself a trend follower, but he did practice the cardinal rule of trend followers: Cut your losers and let your winners run. When a market started to decline in price, he got rid of it, no questions asked. When something was on the rise, he bought in, no questions asked. I counted up all his trades and found that he made about 20 percent a year. He had a lot of losing trades, but they were only small losses. And his winners were few, but they were big-time gains. Sometimes only one or two trades accounted for the majority of his profit that year. Lightbulb moment!
I now knew I wanted to do what Jack Boyd was doing but with far more scientific rigor. One of the things I believe most in in this world is the scientific method, that is, testing your assumptions. So I sat down at my kitchen table and laid down my charts. I wanted to test my ideas and use the results to develop mathematically proven rules for when to go into a given market and when to get out. Because I didn’t know classical mathematics, I looked for a simpler model to investigate. Eventually I found Edward O. Thorp’s famous 1962 book, Beat the Dealer. Thorp (a mathematics professor turned trader) tested thousands of blackjack scenarios and devised a system of card counting in which anyone could use the basics of probability and increase their odds of winning.
What I discovered was that under certain circumstances, you can still lose. Sounds simple, I know, but bear with me. Even with the advantage of being able to look at every card (instead of every three), I could still lose. Even when I gave myself every chance to win—even bending the rules, I still could lose. That really hit home to me. I proved to myself that losing is sometimes inevitable even if you do everything right—that’s because you always assume the risk of losing is there. I began to think hard about this. How could I prepare for the inevitable?
FOUR KINDS OF BETS
Most people think there are two kinds of bets: good bets and bad bets. Through my early experiences and other research I began to see there are actually four kinds of bets: good bets, bad bets, winning bets, and losing bets. Most people would assume that if you lose it’s because you made a bad bet and if you win it’s because you made a good bet. But that’s wrong. Good and bad bets refer to the odds. Winning and losing bets refer to the outcome. You can’t completely control outcomes. But you can control two things for sure. The odds of the bet you take, and the risk you take.
If you keep placing good bets, over time the law of averages will work for you. But you must never forget you will still lose sometimes. That’s just the laws of probability in an uncertain world where prediction doesn’t work. If I know this in advance, I am prepared to bet only what I can afford to lose.
Be forewarned that one of the worst things that can happen is for you to get lucky on a bad bet and win big. For example, you walk across the street looking intently at your cell phone ignoring everything. That’s a bad bet. You could get drilled by an old guy who can’t see over the wheel. But guess what? You’re lucky and you don’t get flattened. In fact, you are not lucky, because this is how you become desensitized to risk. What happens next? You brazenly continue your mindless walking practice until you get hit by a bus. If you keep placing bad bets, over time the law of averages will work against you. This is essentially the probability you never learned in school condensed into a useful heuristic you can use now.
LOOKING AT THE ODDS
I embarked on a whole new learning process when I went to work for Jack Boyd at DuPont. Jack’s trading was not particularly scientific, but he had a interesting method. When he saw something move, he went in that direction. When it didn’t, he got out. He did not call himself a trend follower, but he did practice the cardinal rule of trend followers: Cut your losers and let your winners run. When a market started to decline in price, he got rid of it, no questions asked. When something was on the rise, he bought in, no questions asked. I counted up all his trades and found that he made about 20 percent a year. He had a lot of losing trades, but they were only small losses. And his winners were few, but they were big-time gains. Sometimes only one or two trades accounted for the majority of his profit that year. Lightbulb moment!
I now knew I wanted to do what Jack Boyd was doing but with far more scientific rigor. One of the things I believe most in in this world is the scientific method, that is, testing your assumptions. So I sat down at my kitchen table and laid down my charts. I wanted to test my ideas and use the results to develop mathematically proven rules for when to go into a given market and when to get out. Because I didn’t know classical mathematics, I looked for a simpler model to investigate. Eventually I found Edward O. Thorp’s famous 1962 book, Beat the Dealer. Thorp (a mathematics professor turned trader) tested thousands of blackjack scenarios and devised a system of card counting in which anyone could use the basics of probability and increase their odds of winning.
What I discovered was that under certain circumstances, you can still lose. Sounds simple, I know, but bear with me. Even with the advantage of being able to look at every card (instead of every three), I could still lose. Even when I gave myself every chance to win—even bending the rules, I still could lose. That really hit home to me. I proved to myself that losing is sometimes inevitable even if you do everything right—that’s because you always assume the risk of losing is there. I began to think hard about this. How could I prepare for the inevitable?
FOUR KINDS OF BETS
Most people think there are two kinds of bets: good bets and bad bets. Through my early experiences and other research I began to see there are actually four kinds of bets: good bets, bad bets, winning bets, and losing bets. Most people would assume that if you lose it’s because you made a bad bet and if you win it’s because you made a good bet. But that’s wrong. Good and bad bets refer to the odds. Winning and losing bets refer to the outcome. You can’t completely control outcomes. But you can control two things for sure. The odds of the bet you take, and the risk you take.
If you keep placing good bets, over time the law of averages will work for you. But you must never forget you will still lose sometimes. That’s just the laws of probability in an uncertain world where prediction doesn’t work. If I know this in advance, I am prepared to bet only what I can afford to lose.
Be forewarned that one of the worst things that can happen is for you to get lucky on a bad bet and win big. For example, you walk across the street looking intently at your cell phone ignoring everything. That’s a bad bet. You could get drilled by an old guy who can’t see over the wheel. But guess what? You’re lucky and you don’t get flattened. In fact, you are not lucky, because this is how you become desensitized to risk. What happens next? You brazenly continue your mindless walking practice until you get hit by a bus. If you keep placing bad bets, over time the law of averages will work against you. This is essentially the probability you never learned in school condensed into a useful heuristic you can use now.
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Al Brooks does this all the time. Keeps adding and gets out at break even.
I think you might be confusing me for @padutrader. I ain't no Brook's follower (although we have a lot in common, but that's only natural since we both use PA).
Economy: a self-reinforcing system?
The economist Paul Krugman has begun a systematic inquiry into the theory of self-organization, particularly as it relates to the economy. To illustrate the process of self-organization, he asks us to imagine the city of Los Angeles. Today, we know that Los Angeles is not one homogeneous landscape but a collection of different socioeconomic, racial, and ethnic neighborhoods including Koreatown, Watts, and Beverly Hills. Surrounding the city is a further collection of many distinct business districts. Now each of these distinct spaces was formed not by urban planners drawing lines on a map, but by the spontaneous process of self-organization, Koreans moved to Koreatown to be closer to other Koreans. As the population there increased, still more Koreans were drawn to the neighborhood, and thus a self-organized community also became self-reinforcing. No central controller made this decision for everyone, explains Krugman; the city just spontaneously evolved and organized itself in this fashion.
The evolution of a large city is a relatively simple example of self-organizing and self-reinforcing systems, but we can observe similar behavior in economic systems. Setting aside for the moment the occasional recessions and recoveries caused by exogenous events such as oil shocks or military conflicts, Krugman believes that economic cycles are in large part caused by self-reinforcing effects. During a prosperous period, a self-reinforcing process leads to greater construction and manufacturing until the return on investment begins to decline, at which point an economic slump begins. The slump in itself becomes a self-reinforcing effect, leading to lower production; lower production, in turn, will eventually cause return on investment to increase, which starts the process all over again. Some might argue that the Federal Reserve, by altering interest rates, acts as the central controller to the markets, but as we know, the bond market vigilantes often preempt the Federal Reserve's decision. If we stop and think, we realize that the equity and debt markets have no central controller, and both are excellent examples of self-organizing, self-reinforcing systems.
The economist Paul Krugman has begun a systematic inquiry into the theory of self-organization, particularly as it relates to the economy. To illustrate the process of self-organization, he asks us to imagine the city of Los Angeles. Today, we know that Los Angeles is not one homogeneous landscape but a collection of different socioeconomic, racial, and ethnic neighborhoods including Koreatown, Watts, and Beverly Hills. Surrounding the city is a further collection of many distinct business districts. Now each of these distinct spaces was formed not by urban planners drawing lines on a map, but by the spontaneous process of self-organization, Koreans moved to Koreatown to be closer to other Koreans. As the population there increased, still more Koreans were drawn to the neighborhood, and thus a self-organized community also became self-reinforcing. No central controller made this decision for everyone, explains Krugman; the city just spontaneously evolved and organized itself in this fashion.
The evolution of a large city is a relatively simple example of self-organizing and self-reinforcing systems, but we can observe similar behavior in economic systems. Setting aside for the moment the occasional recessions and recoveries caused by exogenous events such as oil shocks or military conflicts, Krugman believes that economic cycles are in large part caused by self-reinforcing effects. During a prosperous period, a self-reinforcing process leads to greater construction and manufacturing until the return on investment begins to decline, at which point an economic slump begins. The slump in itself becomes a self-reinforcing effect, leading to lower production; lower production, in turn, will eventually cause return on investment to increase, which starts the process all over again. Some might argue that the Federal Reserve, by altering interest rates, acts as the central controller to the markets, but as we know, the bond market vigilantes often preempt the Federal Reserve's decision. If we stop and think, we realize that the equity and debt markets have no central controller, and both are excellent examples of self-organizing, self-reinforcing systems.
Just what the hell does "mean reversion" mean anyway?
In the parlance of trading, mean reversion, suggested by "the experts", is when asset prices tend to return back to normal or average levels after an extreme price move. But, seriously, what does the "average level" mean here? This is something I believe you should think hard about if you wish to take your trading to the next level.
Is this mean reversion?
If so, would this be reverting to the mean?
Or what about this? It reverted from the higher extreme to the lower extreme.
Or maybe this?
In the parlance of trading, mean reversion, suggested by "the experts", is when asset prices tend to return back to normal or average levels after an extreme price move. But, seriously, what does the "average level" mean here? This is something I believe you should think hard about if you wish to take your trading to the next level.
Is this mean reversion?
If so, would this be reverting to the mean?
Or what about this? It reverted from the higher extreme to the lower extreme.
Or maybe this?