I Will Not Go Bankrupt Tomorrow

I cannot guarantee you many things. But I can guarantee you that I will not go bankrupt tomorrow.

I might lose money. All my trades might get stopped out. All my new trades might go against me immediately. But I will not lose so much that I am forced out of business.

How do I know this? Because staying in business is the number one job of a trader.

As a trader there are some things that you can control, and some that you cannot. You cannot control what the market will do. But you can choose the terms on which you engage the market.

You can choose

  • Which markets to trade (market selection).
  • When to enter and exit (trade selection).
  • How much to buy or sell (position size).
  • How much of your portfolio to risk at any time (portfolio heat).

Of all these, market and trade selection gets the most attention in the financial press and blogosphere. Position size gets mentioned occasionally, but nowhere near enough given its importance: far too many traders trade the same number of share, contracts or dollars per trade regardless of the underlying market conditions. And portfolio heat gets the least attention of all.

Ed Seykota talks about bet size and portfolio heat as being far more important than trade selection, or fiddling with whether to use a 20 day or 22 day moving average, or whether a 15 p/e is cheap or expensive.

Think of every trade as a bet. If you bet small every time, you are unlikely to win very much. If you bet large, you are dramatically increasing your risk of ruin i.e. the chance that an unlucky streak will take you out the game. Conservative betting produces conservative performance, while bold betting leads to spectacular ruin.

Portfolio heat refers to the number of open positions at any one time, and the amount of open risk in those positions. Risking 10% of your portfolio on one trade is very risky. Risking 5% on two (uncorrelated) positions is less risky. Risking 1% on each of 10 different trades is much safer. Risking 1% on 5 different trades is safer still.

Portfolio heat also considers the amount of open profit in a position. Imagine buying a stock at $100, with a stop of $95, and the stock rises to $110. If you keep your stop at $95, then the $10 gain is still at risk: it could disappear tomorrow. If you use trailing stops and raise your stop to break even or $105, you can reduce the amount of your portfolio at risk. Raising stops in the direction of winning trades allows you to reduce portfolio heat while still allowing winners to run.

I control my trading risk at several different levels. I have a maximum amount of my portfolio at risk on any trade. I also have a maximum number of positions open at any one time: even if my system gives me 50 phenomenal trade entry signals, I will not take them all, since that would put too much of my portfolio at risk.

I have no idea how much I could win tomorrow, but I know exactly how much I could lose. I am not going bankrupt tomorrow, and that helps me sleep.

Taking The Red Pill: All Fundamental Data Is Wrong

All fundamental data is wrong in some way. Some of it is incorrect, some of it is published by people with a vested interest, and some of it is lies. I am not angry about it, but I think we should face the sometimes harsh reality provided by the Red Pill.

Let us start with company-provided information. If the history of public corporations tells you anything, it is that anything a corporation tells you should be treated as a lie. Sometimes it is deliberately misleading, sometimes it obscures the truth, and sometimes it just lies to your face. If you do not believe me, then I point you to some of those who were caught: Enron and Lehman Bros stick in the mind, but the list is long.

Do not kid yourself that these are the rogues in an otherwise healthy bunch: every public corporation twists and tortures their information to meet their objectives. In a previous life I was a company auditor, and I can attest that there is plenty of scope for maneuver within the law. In a Barron’s interview, forensic accountant Howard Schilit put it like this:

Here is how the auditors look at the world: They think of themselves and their legal liability issues first; if it’s in the rule book and disclosed, you are covered. Second, they think of their clients. The client asked them to do something, and they want to please the client. A very distant third is they may occasionally ask: How does this look from the perspective of the investor? Investors would be astounded if they realized that this is how the party that is supposed to protect them views the world.

Similarly, the New York Times reported on an investigation by the Public Company Accounting Oversight Board that reviewed multiple audits performed by ten different auditing firms. All of those firms were reported to have performed audits that were unsatisfactory and flawed.

Some data is clearly to be more trusted than others: anything a CEO tells you is not even worth a pinch of salt, whereas tax returns are probably more reliable (not because no-one ever lies on their tax return, but because the consequences of doing so are reasonably high, and there is at least a chance of being prosecuted). But the evidence is overwhelming that company executives have a vested interest in portraying as positive an image of their company as they can, and that they can and do lean on all sorts of levers to manipulate the data they present to you.

Trusting the data a company gives you is like believing what Saudi Arabia tells you about their oil reserves, or what North Korea tells you about their nuclear weapons: it might be in the ballpark of True, but it undeniably comes from someone with a vested interest in the outcome. Company data also carries the material risk of missing information: what they tell you might be true, but what they choose not to tell you is important as well.

It is difficult to believe data released by government organizations either. The US Government and the Federal Reserve have a vested interest in persuading you that unemployment and inflation are lower than they actually are. They might not be deliberately falsifying the figures a la Argentina, but there are more subtle institutional pressures to chose assumptions and methodologies than systematically underestimate certain measures.

Just as pertinent are the revisions. Fundamental data is often revised. Corporations restate their earnings. GDP and employment figures are adjusted materially months later. If data can be revised long after the fact, it makes little sense to base investment decisions on the originally announced variable.

Every computer programmer knows that if you input garbage, you output garage. Doing analysis based on discounted cash flows, or price/earnings multiples or supply/demand components is all well and good, but if you cannot trust the data, you cannot trust the output it produces.

I am not one of the Black Helicopter crowd that sees conspiracies at every turn. I believe that Armstrong walked on the moon, that Oswald shot Kennedy and that earthquakes are generally caused by shifting tectonic plates rather than the CIA*. My skepticism regarding fundamental data does not come from a dark and bitter place, but rather from a frank and honest acknowledgement that data is prepared and released by people and that people tend to act in their own self-interest. Even honest, well-intentioned people are humans, and humans are susceptible to spinning bad news as good and lying by omission.

I use fundamental analysis every day. It can be an important part of the trading process. However, I treat all fundamental data with a strong pinch of cynicism, a healthy sense of skepticism and a highly-refined BS Detector. When placing my own money at risk, I think it is better to see the world as it is, rather than how I might want it to be.

* I think that people are attracted to conspiracy theories because they find comfort and security in the  notion that someone is in charge, rather than accepting that most things happen due to random chance.

The Fisherman And The Hypothesis

I have done some fishing. Not much, but some. My father-in-law has done a whole bunch, and from the stories he tells me fishing is a lot like trading. Because it is not about landing a fish with every cast, it is about tolerating lots of nibbles in the anticipation of landing the big one.

For the scientific fishermen among you, you can also think of trading as hypothesis testing. Each trade entry is an hypothesis, a proposed explanation for a phenomenon. You are hypothesizing that a market is about to move in a particular direction. It is pretty testable too: the market will tell you pretty quick if your hypothesis is correct. Or not.

Fishermen and scientists are wrong a lot. As a trader, you should expect to be wrong, to be wrong often, and occasionally you will be spectacularly wrong. Michael Jordan has a fabulous perspective on the subject:

I’ve missed more than 9,000 shots in my career. I’ve lost almost 300 games. Twenty six times, I’ve been trusted to take the game-winning shot and missed. I’ve failed over and over and over again in my life. And that is why I succeed.

Searching for the winning trade is a process of casting, failing and re-casting until the fish is hooked. The successful fisherman will cast and fail more times than the novice fisherman who gives up and goes home early. The successful trader will lose more often than the unsuccessful trader, precisely because the unsuccessful trader does not stay in the game.

Tim Harford describes how a complex problem can be resolved by an approach that incorporates a willingness to experiment:

The process has three components: First, try lots of different things; Second, make sure the experiments are at a small scale so that when things go wrong, it’s not a catastrophe; Third, make sure there’s a reliable way to tell the difference between success and failure.

Besides being pretty much the opposite of how government works, this concept is directly applicable to trading: Try lots of different things, make sure that all the things you try are small enough to not blow you up if they go wrong, and check regularly to see if these things are working.

Regular readers of this blog will know that I am comfortable with failure. I fail everyday, more than once. But that is okay because it is part of a process of progression. Seriously trying for success requires exposing yourself to the risk of failure. Expecting to succeed without experiencing failure is naive. Experiencing failure is fine, as long as it is part of a process that leads to success. The fisherman knows that, and so does the successful trader.

The Averaging Down Clown

We have all been there. You do your research and your due diligence.  You check the valuations and the charts. You calculate the risk/reward. You maybe even get all patient and wait for a catalyst. For all sorts of good and clever reasons, you decide to buy 100 shares of company XYZ, paying, let’s say, $50 per share.

A few weeks later, you recheck your portfolio. Company XYZ has fallen to $45. After cursing a bit, you recheck your valuations and research, and conclude that nothing about your original view has changed. In fact, the trade looks like an even better deal, since you can now buy shares for only $45. You pay $45 for another 100 shares.

Time passes, seasons change, you grow a beard and the stock falls to $40. Again, there has been no material news or change in your analysis of value. You decide to buy another 100 shares: after all, if you liked the trade at $50, you must love it at $40! Even better, the stock only has to rally back to $45 for you to break even. If it gets back to your original purchase price, you are in the money!

This logic seems common for professional and amateurs alike. It is psychologically very tempting, not least because it means that you do not really have to admit that you are wrong. It is strongly encouraged by a fundamental analysis/valuation mindset: without new information, trades that go against you simply look like even better opportunities. At the very least, this encourages you to not exit your losing trade, and even to commit more capital.

This is very dangerous.

The reason that it is dangerous is not that it does not work. It does work, quite often. Doubling down pays off, you make even more money than you originally thought, and you feel like a champion. That positive feedback encourages you to do it again next time.

The danger comes from what happens when it does not work. When you keep adding to a trade that keeps going against you, you will eventually lose. Perhaps the fundamental situation changed, and you were not aware of it yet. Perhaps the market simply has a different idea of valuation than you. Perhaps the market is being manipulated. It really does not matter why: at some point you will lose. And by using a strategy of averaging down, you are guaranteeing that your biggest positions will be in your worst trades.

Let that sink in, and I will say it again.

You are guaranteeing that your biggest positions will be in your worst trades.

 Averaging down feels great. It fits in with our popular acclaim for those who “have the courage of their convictions”, who “stick with it when the going is tough”. Unfortunately it also sets you up for a massive fall.

In contrast, a strategy of averaging up into winning trades puts your largest positions in your winning trades. If you pyramid up, your average price rises slower than the market price i.e. you are effectively buying at a discount to the current market. For example, if I buy 100 shares paying $50, 100 paying $55 and 100 paying $60, my average price will be $55: $5 below the market price of $60. Contrast that with the earlier example of averaging down, where my average price was $45, $5 below the market price of $40.

Another way to consider it is to examine the four possible basic outcomes to any trade:

1) Wins initially, and keeps winning.

2) Wins initially, but then reverses to become a loss.

3) Loses initially, and keeps losing.

4) Loses initially, but then reverses to become a win.

If you average down, you only get the chance to add to trade types 2, 3 and 4.

If you average up, you only get the chance to add to trade types 1, 2 and 4.

Averaging down tends to be attractive to people, since it allows the possibility of trade type 4 i.e. a trade that goes against you, but then reverses to recover your losses and more. However, that comes at the material risk of trade type 3 i.e. the trade that never recovers.

Averaging down virtually guarantees that your biggest positions will be in trade type 3 i.e. the trades that never win. Pyramiding up avoids this risk, and also allows you to add to trade type 1 i.e. the trades that start off winning and keep winning.

To be clear, there is a legitimate strategy of picking a range of entry into a trade. Rather than picking a particular price point, you may choose to scale into a position over a range of entries. The distinction here is that you must decide this plan before the first entry is made, rather than in response to a trade going against you.

Averaging down is psychologically easy, and feels good. The market tends not to reward behavior that feels good and easy. It might not punish you straight away, but averaging down losing trades is a great way to end up owning a lot of shares in the next Enron or Lehman Brothers. I prefer my biggest positions to be in my winners.

The Number One Job Of A Trader

Thank you for your replies to my question: What is the number one job of a trader?

Your answers tended to revolve around making money, managing risk, protecting capital and making positive risk-adjusted returns. Those are all good suggestions that make sense. I would add that in professional trading firms, acting in compliance with the law and regulations is an explicit focus as well.

I think the real answer is deeper. For me, the number one job of a trader is to be allowed to play the game again tomorrow.

Why? Because it is a probability game, and the only people who are right every time deserve to be in jail. Even when you have a good edge, the odds are that there will be reasonably long streaks when the dice simply do not land your way. It is important to develop an edge (a positive expectancy), but it is equally important to be in business long enough to capitalize on that edge.

Take the example of a weighted coin, where you win 2x your stake if it comes up heads, and lose your stake if it comes up tails. You have $100 to play with, and the game will be played multiple times. How much should you bet on each coin flip?

The answer is clearly not $0: this game has an edge (a positive expectancy), so you should be willing to play it. However, the answer is clearly not $100  either: there is a reasonable chance that you will lose on any given coin toss, and so you should not risk your entire stake on one flip.

Smarter people than me can work out the math of what the “optimal” bet size is for this game. In the real world, the game is murkier since you do not know what the odds are: you can only make educated guesses or rely on historical back testing. The important point is that you need to act so that you can play the game again. Betting too big so that you blow up before the positive expectancy can play out in your favor is a fatal mistake.

Acting in a way that stops you being able to play a positive expectancy game again means that you have failed as a trader. This covers everything from losing so much money that you blow up/get fired, breaking any laws or codes that get you banned, or sleeping with the boss’s wife: anything that stops you being allowed to play the game again tomorrow. It doesn’t matter how good your trade idea is, or how much money the trade is going to make next week, or how good your average win/average loss ratio is: your swipey badge thingy has to open the door to the trading floor tomorrow.

You need an edge to make money over time. But if you have an edge, and you act in such a way that you cannot exploit that edge, you have failed.