Cryptocurrency Trading Bible Four: Winning in Sideways and Bear Markets

All trading is gambling.

Some people refuse to believe it but that doesn’t change it.

As a society we’ve managed to dress up the big stock exchanges with an air of refined superiority. It’s not a game of chance or a numbers racket. It’s “investing.”

“Real’ investors like Warren Buffet look down their noses at more volatile derivatives markets and cryptocurrency because they’re not civilized. Surely he’s right and the New York Stock Exchange is not the same as trading Bitcoin on Poloniex or playing Poker in Vegas? The major markets have high liquidity and lots of players, circuit breakers and quarterly earnings reports so it’s got to be different, right?

Investopedia certainly doesn’t want you thinking investing is gambling:

“Gambling…is a zero-sum game. It merely takes money from a loser and gives it to a winner. No value is ever created. By investing, we increase the overall wealth of an economy. As companies compete, they increase productivity and develop products that can make our lives better. Don’t confuse investing and creating wealth with gambling’s zero-sum game.”

That’s nice. Except it’s wrong.

The markets are a zero sum game. When you win, someone else loses. When you lose, someone else wins. The market matches people all across the world in the most massive zero sum game every dreamed up by the advanced monkeys we called humans.

And it sure feels good to say we’re contributing to the overall health of the economy by putting our money into companies but that really has nothing to do with anything. Of course investing in projects and companies has deeper societal value than the roulette wheel but that doesn’t change one simple fact:

When you put money into the market it’s not because you’re supporting the company out of the goodness of your heart or because you want to see the overall economy booming.

You’re doing it because you hope that you’ll get more money out than you put in.

Whether you’re betting it all on a hand of Poker or the next biotech stock powerhouse you’re playing a game of chance.

What you’re doing is guessing that you know the future better than anyone else. You believe that the company you’re investing in will continue to create good products and it will go up in value and give you your money back and then some.

But you don’t really know.

No matter how many analysts newsletters you read or quarterly reports you pour over, there is no guarantee the company will continue to do good. How many times have you read this in the fine print of anything you’ve ever put your money into?

“Past performance is not indicative of future results.”

In other words just because something did well in the past doesn’t mean it will keep doing well. A billion variables could tank that company and cause you to lose every red cent. Whether it’s a battle of board members, a black swan event, a changing market place, a failed product launch or a terrible rash of turnovers, anything can cause a company that made money yesterday to stop making money today.

When Warren Buffet picked Coca Cola, after its business tanked in the face of the fast growing health/exercise market as well as rising competition from sugary, sweet Pepsi, he’s betting he knows something you don’t know.

He believes that no matter how many treadmills and Nike sneakers get sold the world will not lose its taste for the classic, iconic soft drink. After the fitness craze passes and the obsession with Pepsi reaches its peak, he’s speculating the Coke business will recover and he’ll make more money than he put in.

That’s gambling.

I get it. The term has a negative charge to it. Gambling is bad and investing is good.

Except the math is exactly the same.

Period.

When you put money into any market, like it or not, you’re playing dice with the universe.

Said by Einstein when faced with the fact that at the base of all reality is nothing bur formless probability and not a deterministic clockwork God. He/She/It does play dice.

The problem is one of belief.

Most folks don’t want to believe that trading and investing are games of chance (or that life is) but once you get over that illusion you can start to make much better decisions.

Let go of the negative charge associated with the word “gambling” and you can start to see what you’re doing for what it is and it will give you an advantage over others in the market.

You won’t be surprised when the stock market stops its relentless climb and turns south for months or years. You won’t be surprised when a good company’s stock doesn’t match the value it generates, while a company that’s never turned a profit in its entire life was wildly overvalued for a decade.

Markets are not rational. People are not rational and anyone who thinks that has never traded seriously in their entire life. People are emotional, irrational, wild, crazy, stupid, brilliant and foolish and the markets are nothing but a reflection of the minds of billions of unstable actors in an open market, a collective hallucination of our fears and desires.

When you wade into the ocean of the markets you’re wading into a storm of absolute chaos.

Accepting the reality that gambling, investing and trading are one in the same will help you remember to bring your rain coat and umbrella into the storm.

Instead of studying CNN and watching the news constantly, you’ll start studying the math behind games of chance, and looking at probability, game theory and statistics.

And the first place that will lead you is to better portfolio management.

Perfecting Portfolio Management

One of the most important realizations you’ll ever come to in trading is that your strategy doesn’t matter as much as you think and your risk management matters a hell of lot more than you think.

Your entries into a stock or coin sure seems like the key to glory and riches but I’ll give you a system a little later that shows you just how wrong that really is and why you should care less about entry and more about exits and protecting what you have right now.

No matter how good your signals are or how good you get at picking the companies that will change the world five years from now, you’re going to be wrong. And you’re going to be wrong a lot. That means you’ll have to endure periods of losing money, also known as “draw downs.”

The markets won’t give you a predictable stream of income like a salary, your money gets made in bunches. And it’s lost in bunches too.

That’s probability at work.

Probability comes to us from the seventeenth century when pro gambler and writer Antoine Gambaud started losing big time money and reached out to the brilliant French mathematician Blaise Pascal to figure out why. Gambaud liked to call himself the Chevalier de Méré, aka the knight of the Méré, and he used to bet he’d nail at least one ace when rolling four sided dice. That made him good money consistently.

But he got bored and he got greedy.

He figured if that worked he could make even more if he bet twice as much.

The book Probability, Decisions and Games: A Gentle Introduction in R by Abel Rodriguez and Bruno Mendezs tells us that didn’t work out so well:

“Suddenly, he was losing money!

De Méré was dumbfounded.

He reasoned that two aces in two rolls are 1/ 6 as likely as one ace in one roll. To compensate for this lower probability, the two dice should be rolled six times. Finally, to achieve the probability of one ace in four rolls, the number of the rolls should be increased fourfold.”

They dig into the math behind it extensively so I won’t rehash it here but basically it boils down to he cranked up his risk and dialed down his chances of winning by moving to two dice and increasing the number of rolls.

And just like that a good strategy became a bad strategy because De Méré didn’t understand the math behind the game he was playing.

In the book Market Wizards, the author asks legendary investor Paul Tudor Jones:

Q: “What is the most important advice you could give the average trader?”

A: “Don’t focus on making money; focus on protecting what you have.”

He’s talking about portfolio management, aka protecting against risk. Portfolio management is really the science of statistics and probability applied to games of chance.

Think about it for a second.

When someone tells you to diversify your assets and “don’t put all your eggs in one basket” they’re talking about how to deal with the fact that some of your guesses as you gamble in the market will go against you. If you risk too much, you risk wiping out your entire portfolio. If you wipe out your entire portfolio you can’t play the game anymore and you’re going home with your tail between your legs.

Here’s a breakdown of the math behind diversification of your assets from a course at NYU on “Elementary Portfolio Mathematics.”

If you don’t like math don’t worry. You can still get a good understanding of probability even without doing all the math yourself. Just skip the funny little symbols coming up for now.

But here’s a formula for those of you that like formulas. It shows an investment’s contribution to risk in a portfolio:

It comes to you from this blog where you can read about all the glorious math behind those funny little symbols if you’re so inclined.

Basically the formula is showing the risk of individual assets weighted, as well as how correlated they are, meaning how similar assets are likely to burn your whole house down. If you have too many precious metals, they’re all likely to tank at once and that makes them highly correlated, whereas treasuries and precious metals are probably inversely correlated most of the time.

I’m not going to go through the formula here because it will eat up a lot of space and time and bore most of my readers but check out the link to the blog or the NYU doc if you want to dig into it. If you need a refresher on math symbols or never studied them at all than I recommend the book Mathematical Notation: A Guide for Scientists and Engineers.

For now though, forget the math.

What’s important is this:

Most trading books focus too much on the strategy for picking and choosing assets and not enough on what really matters, reducing your risk as you gamble.

Those books give you the illusion that you can develop a system to consistently outperform the vast majority of other humans, while outlasting black swan events and major economics crashes but the fact is most systems don’t perform well over a long enough time line. Moving averages, technical analysis and fundamental analysis only get you so far before you’re playing a game of dice once more.

That’s where portfolio management comes into the picture.

You can get super complicated with formulas for managing your risk and allocating those assets. How many are related? How much diversification is too much diversification? How many assets should you own at one time?

Here’s an entire book on optimal portfolio allocation and leverage alone.

But before going there though let’s focus on a much simpler way to reduce your risk:

Bet sizing.

Place Your Bets

Any trader worth their salt will tell you you should never risk more than 1% or 2% on a single trade. But what does that really mean anyway?

We can look at the problem a number of different ways.

The most basic way is to simply put no more than 1% of your total portfolio capital into a single trade. That’s effective because even if you get totally wiped out on that trade you can’t lose more than one percent.

It’s also completely ineffective for long term gains and I don’t believe any trader is using that formula, even if they tell you that on Twitter so you don’t lose your shirt and go blaming them.

Here’s why.

If you can only put 1% of your money down into a trade you have 99% of your money sitting on the sidelines. Even if you pyramid into that winning trade, the process of adding more money to a trade that’s going your way, most systems advise no more than 4% piled into a single trade.

That’s still a lot of money sitting on the sidelines doing nothing at all. And that’s just the first problem with this method of risk control.

The second problem is that you need to keep finding new assets so you can get all of your money into the market and that means you have to find lots of winners and that actually starts to work against you because you won’t find lots of winners, just a few winners most likely.

If you have dozens of assets they will start to blur together into an ugly average mess, dragging down your winners even though your losers got averaged out. One or two of them might lose big and two more might go to the moon but most of them will sit right in the middle of the distribution curve giving you an average return and that’s not that awesome.

That means you reduced your risk but you really didn’t make all that much money either.

Low risk usually equates to low reward.

Let’s look at an alternative way to calculate the 1% rule, which allows us to take bigger bets on any give trade but still protects our portfolio from catastrophic loss.

A Better 1%

What we’re going to do is place bigger bets and get more of your money working for you by creating a stop loss system. I use a variation on the Turtle Traders trailing stop loss, which is the ATR or Average True Range times a multiplier. So I might have ATR X 2. That tells me where to set my stop loss on any given trade.

There are a few problems with the trailing stop loss though. The ATR is a measure of volatility and when a coin gets super choppy that volatility gets crazy. You might end up with a wide gap between the current price and your stop. It could be 5% or 8%, which is a much bigger loss than 1% and it puts you at a much higher risk.

So how do we fix that?

Simple.

First, we calculate the delta between the current price and the current stop. We’ll use round numbers in our examples to keep it easy to understand.

Let’s say Bitcoin is at $8,000. Your stop loss calculation puts the current stop at $7,700, a $300 difference on a single Bitcoin.

Now that we have that delta we can use that to figure out how to risk only 1% of our total trading stack on a single trade. Let’s pretend you have $100,000 in total cash to risk.

$100,000 X .01 = $1,000.

At most we want to risk only $1,000 on this trade. So let’s divide the delta of the current price and our stop loss by 1000.

1000 / 300 = 3.33

That means we can buy up to 3.33 Bitcoins, if we set the stop loss to $7,700, because on each Bitcoin we only stand to lose $300 if the trade goes against us. With 3.33 Bitcoins the total loss on all of them would equal $1,000 or 1% of our portfolio.

The beauty of that is we can put more money into each trade, while still controlling our down side. In this case we put $26,666 dollars of our $100,000 into this single trade, which gives us the potential to realize more compounding gains should the trade go in our favor.

Of course, with every portfolio management strategy there’s a downside. On one hand we’ve increased our chance at maximizing gains but we’ve also increased our total risk. Let’s see why.

In the basic strategy outlined earlier you risk only 1% of our money, which in the case of a $100,000 portfolio means we only put $1,000 into a single Bitcoin trade. No matter what happens we cannot lose more than that $1000 dollars.

But in the strategy I just outlined we’re totally dependent on our stop loss triggering correctly. Any trader will tell you, that doesn’t always go according to plan.

There are number of ways it can go wrong on you. Let’s see how.

You can set a stop limit loss, which allows you to set a trigger price and a price you’re willing to sell it at. You can also use a market stop loss, which triggers at the price you set and sells at the going rate. Both have advantages and disadvantages and both might kill you for different reasons.

In particular, a market stop loss in cryptocurrency trading can deliver a real blow to your trading career.

The cypto exchanges are still relatively immature versus the major exchanges and they don’t have as many protections built in. We’ve seen a number of “flash crashes” in the last few years. That means that the price might go from $8,000 to $3,000 in five seconds before bouncing right back up, whether that’s due to a giant whale dumping on the market, a bug in the exchange code or something else. A market stop loss executes at whatever the current price is, so you could get filled at $3,000 a much, much bigger loss than 1%.

A stop limit is easier to control but it’s also something of a dark art to get right. In a stop limit you set the “trigger” price and the “stop” price at different levels. You might choose a trigger price of $7,725 and a stop limit price of $7,700. That means that when the market hits $7,725, you’ll enter an automatic sell order of $7,700, which is likely to get filled much faster because it’s below where the current price action is and that gives you an advantage.

But it’s no guarantee.

Set your limit price wrong and you might wake up to find the price plunged through your stop and wake up to a 15% loss on the money you risked. With the strategy I outlined that might amount to 5-8% of your portfolio (or worse) and it doesn’t take many 8% losses to take you out of the game for good.

Any serious portfolio strategy will have to take into account a possibility that a stop loss fails to trigger some of the time and you can use Monte Carlo analysis to tell you how likely that is to destroy your portfolio completely. We won’t go into the math on that here but you can work it out if you dig into books like Building Winning Algorithmic Trading Systems: A Trader’s Journey From Data Mining to Monte Carlo Simulation to Live Trading by Kevin J. Davey.

There are a huge number of different portfolio and risk management strategies. Start studying them now and it will only make your trading stronger.

Pick one. Stick to it. Do not deviate. Ever.

Now let’s look at another way probability can help you win in a sideways market or choppy market.

Taking Scalps

Scalping is the processing of taking smaller wins in the market when the market is bouncing around on you. There are thousands of advanced ways to do it but I want to show you a simple way that will blow your mind.

Flipping a coin.

That’s right. We are going to guess on our entries into any coin. Our long or short will be totally random.

Maybe you think that your coin picking strategy is vastly superior to random chance but random strategies often do incredibly well in stock strategy competitions.

We usually find that someone entered the strategy as a joke but what if it’s not a joke at all?

In an article for Forbes, Rick Ferri tells about a research team that simulated monkeys throwing darts to pick stocks:

“In 1973 when Princeton University professor Burton Malkiel claimed in his bestselling book, A Random Walk Down Wall Street, that “A blindfolded monkey throwing darts at a newspaper’s financial pages could select a portfolio that would do just as well as one carefully selected by experts.”

“Malkiel was wrong,” stated Rob Arnott, CEO of Research Affiliates, while speaking at the IMN Global Indexing and ETFs conference earlier this month. “The monkeys have done a much better job than both the experts and the stock market.”

So let’s try our own coin flip strategy in all seriousness as a way to scalp during a crappy sideways market and see why it actually works.

A trade can go one of two ways, for you or against you. It’s really a 50/50 shot.

That means that if you ignore everything else, the news, exponential moving averages, all manner of indicators, Ouiga boards, fluid dynamics, ocean tide cycles and simply flip a coin you should average out to being right 50% of the time.

Of course if you only get it right 50% of the time you’re going to lose aren’t you? Your wins should equal your losses but that’s not actually how it works out.

On any given trading period we have a number of trades that go really wrong or really right. Think about that distribution curve again. Most trades will give us an average return or loss, something like 68.2% of the trades. But some of them will give us outsized gains or outsized losses. During our trading run we might get lucky and get only the string of outsized wins or we may get seriously unlucky and get a string of horrible losses that wipe us out.

Let’s go back to the book Probability, Decisions and Games: A Gentle Introduction in R and check out the graph of a coin flipped 5000 times. Over time the flips of the coin should average out to 50% but on a shorter time line it can get wildly out of whack. Notice how it fluctuates outside of the average for long periods of time.

That means we will have streaks in the short and even the long term. Those streaks are likely to wipe us out before we ever get back to the average.

But what if we could control that downside while benefiting from the upside?

We can do that with a stop loss again. Let’s go back to our strategy of setting the stop loss to a max of 1%.

Now we’re capping our loss at 1% every time as we flip our coin. If a trade goes against us, and provided we don’t blow through our stop, we should only ever lose about 1%, give or take slippage.

But our upside is uncapped.

And that’s where it gets interesting.

Our coin flip strategy can be augmented in a number of ways too.

We can do an analysis of various coins and find the most volatile ones and figure out how much they move on average any given day. We can make the volatility work for us. Let’s say that we find that Bitcoin moves an average of 4% up or down daily. That would let us design our exit strategy.

We might decide to close the trade at the same time every day or as soon as a profit of 4% is hit or we might let it run and move our stop loss up every day to ensure that we stay in profit.

We could use simple heuristics like figuring out whether prices have been up or down for the last week and how many days on average and then just bet long or short for the next week every time and not flip a coin at all.

Not only that but we can use good risk management to protect our money even more effectively. Let’s see how.

When people hear that a coin flip will give them 50% heads and tails they imagine that will happen all the time but it’s not the case. On any given day, week, month or year I might get a string of five or ten heads in a row. We might also see ten trades go against us, two go great, then 10 more go against us once more.

Let’s say we made 10% on the two trades that went well and lost 1% on each trade that went against us. That gives us 20% loss on those trades for a 10% overall loss when we subtract it from our wins. It won’t be long before you’re out of business with that kind of result, especially if you got unlucky and your winners only returned something like 3% total instead of 10%.

But we can protect against that by reducing the amount of risk on each trade that goes against us.

For example, let’s say that if we have a bad streak and three trades go against us in a row. To mitigate that we set up a new rule and put less than 1% on each trade, something like .0075%, reducing our stop until the trades start to go in our favor again and then we bounce back up to 1%. We could also do the opposite and increase our risk on each trade when the game is going in our favor.

All of these strategies will turn you into a professional market gambler, whether you’re using a random coin flip entry or some fancy volatility calculator coupled with an advanced quant algorithm you developed yourself that takes into account sun spots and Twitter sentiment.

But no matter what strategy you use, probability will make you better at it.

Vegas Baby

Everyone likes to imagine that when they put money into the market it’s a lot more high minded than the local gambling addict playing the slots in Vegas. In one sense that’s true.

Gambling addiction destroys lives and I won’t make light of this sickness. But that doesn’t change the math that tells us dice games and markets behave very similarly. Only you know if you have the self control to play the markets or play Vegas regularly.

Everyone is different.

Personally, I hate to lose money with a passion. I have never lost more than $20 in Vegas because I just can’t risk it on the roulette wheel or craps but I have no problem putting money into the market.

There is a difference but it’s only at the surface level. That probability underneath it is exactly the same.

For me studying probability and games is not about becoming a degenerate gambler it’s about stacking the odds in my favor against the house. Understanding reality as it actually is helps you in this pursuit. Believing it’s something other than what it is hurts your decision making.

If you dig into a book like The Mathematics of Games and Gambling by Edward Packel some games are much worse than others when you peer into their numerical underpinnings. Slots are for suckers. Slots are utterly rigged against you deliberately.

Blackjack on the other hand is split about evenly between you and the house.

And Poker?

That’s an entire category in and of itself because while it has completely random aspects, it also has a human variable because you can bluff even when the cards went against you. That takes it out of the realm of totally random chance and gives you an advantage versus other games.

The same can be said of the game of the markets.

Markets have a historical bias towards going up over time. There is also the very human aspect of our hopes, dreams and desires that get reflected in that collective hallucination of money and time we call an exchange. All of that gives you an edge over a pure dice roll.

But not much.

It’s still a game.

There are winners and losers, blind chance, luck, skill and more all bound up in trading.

Shed your illusions and trading becomes a winnable game of chance. Keep pretending you’re better than probability and you’ll end up on the short end of the dice roll.

The faster you come to terms with reality the faster you can start to get one up on Wall Street.

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