ETMA_The Evolution

Trend Following is the Most Repeatable Trading Method Ever Invented | with Scot Billington
https://m.youtube.com/watch?feature=...&v=GpXfK3bUChA

Lessons From the Most Successful Turtle of All-Time | with Jerry Parker
https://m.youtube.com/watch?v=JMQdbgV4jeg

Learn to Love your Trading System | with Jerry Parker
https://m.youtube.com/watch?v=eeVu5_NOonU

076 – Entries, Exits and Trend Following with Larry Tentarelli

074 – A deeper understanding of optimization with Andrea Unger

073 – Combining simple concepts to build robust strategies with Art Collins

072 – Become a better trader by NOT trading

"You can't make money if you are not willing to lose. It's like breathing in, but not being willing to breathe out." - Ed Seykota

Interesting Bass. I am just slowly making my way through these vid's. Thanks muchly kind Sir :-)

I love ORB (Open Range Breakouts), its the closest thing u can get to making consistent profits in this Much uncertain and chaotic Financial Markets .

Better Breakout Trading Model
Opening Range Breakout Strategy Used By Popular Trader
How to Trade Early Morning Range Breakouts

THE FINE ART OF OPENING RANGE BREAKOUT TRADING AND HOW TO MASTER IT
OPENING RANGE BREAKOUT TRADING STRATEGY DESIGN AND IMPLEMENTATION

https://pdfs.semanticscholar.org/1f9...c773db899c.pdf

So You Want to Build Your Own Algo Trading System?
By Kris Longmore on Oct 14, 2016

http://image.pb-email.newedge.com/li...+2016+-+US.pdf

Need To Read Later .
How the Fed went from lender of last resort to destroyer of American wealth

7 Insights from Peter Thiel's Zero to One

http://www.blueowlpress.com/Document...m%20Health.pdf

Because this is how i thought about it ten years ago, i'm posting this article, if you'r serious about living from trading you have to begin from the end and walk your way through to the Beginning, you have to start by your Monthly or yearly expenses Needs and then decide what Returns u need on your investment or trading to live comfortably .

Read This .

The Most Important Topic In Trading
By: Scott Welsh

We dance around in ring and suppose,

But the Secret sits in the middle, and knows.

-Robert Frost

When we talk about trading, there are a lot of things to talk about.
We could talk about trading systems; we could talk about psychology; we could talk about money management. All of those are important.
But none of those things truly gets us closer to trading-for-a-living. Knowing that information doesn't help us make the journey from job/cubicle/mortgage/stress/misery to freedom. We're looking for a life where all our bills are paid and the only thing on our schedule is maybe sitting a hammock. A new Stochastics setting isn't going to get us there.

So how do we get there? How do we go from where we are now to complete independence? Where do we even begin?
The truth is: It all begins with your monthly expenses.

If you're thinking of trading-for-a-living and don't know your monthly expenses, then you have more work to do. If you don't know your expenses, do some quick calculations and come right back.

Great.

Once we know our monthly expenses, we can get started. We now have a number to get to. If we don't have that number, then we don't know what size account we need, and we don't know what trade size to use, and we don't know how much profit our system needs to generate.
Without that number, we're just aimlessly dancing around with our friends, discussing trading methodologies in the sunshine until our families call us in for dinner. We're going nowhere until we know that number.
Once we do know, though, it begins. The Plan magically takes shape.

Let's say our monthly expenses are $2,250. Is that a ridiculous number? Well, it's the exact number that Mr. Money Mustache uses. Who's he? He's the guy who quit his job at 30 and has lived solely off the profits of his initial nest egg.

What was his process? First, he saved. Then he quit at 30. Twelve years later, nothing has changed. He's doing that exact same plan. Money is not an issue.
Isn't that what we signed up for? Isn't that what we dream about? We want trading to pay all of our bills so our lives are entirely ours. That's exactly what Mr. Money Mustache has done.

So there it is. Mission accomplished.

Now how do we stop dancing around and do it ourselves?
Again, we first need to know our monthly expenses. Before he retired, Mr. Money Mustache (MMM) calculated his annual expenses to be no more than $27,000, or $2,250 per month.

Once that was calculated, MMM needed something to pay him that amount. He chose trading.
Well, not really trading. MMM doesn't believe in trading. He's under the assumption that technical analysis has been proven to be futile (author's note: I believe him to be categorically wrong in this assumption, but let's continue).
Because he believes trading is futile but investing is foolproof, he decided to put all of his money into a Vanguard Index Fund.
Now let's go through the numbers.

His family needs a max of $27,000 a year to be free forever. If we look at the 15-year performance of a basic Vanguard Index Fund (VFINX), we see that this fund has averaged 7.21% per year. That's interesting, because internet research shows that the stock market as a whole has averaged about 7% per year since the 1920's. Depending on when you decided to start your calculations, it might even be more than 7%. But let's just stick to that 7.21% number.

Back to the Plan.

If he needed $27,000 a year, then how much did MMM initially have to save to feel safe in retirement?
The answer: $374,480.
However, that number is the bare minimum. We know that the market doesn't go up 7% every year like clockwork. Far from it. What happens if the market has a bad year the first year we retire? Then, of course, we still take out $27,000 and also watch our original nest egg shrink. If the nest egg gets too low, then we have to change our trade size. If we change trade size, then that return number isn't accurate.
It would be better to build in a little margin of safety.
How do we do that? MMM offers a very simple rule: take your annual expenses number and multiply by 25. If you do that, all of the ups and downs should be mathematically accounted for.

Taking that into account, if we multiply $27,000 by 25, we get $675,000.
He and his wife had nice jobs, so MMM had that saved up in 2005.
He's been going strong ever since. Trading pays his bills and the rest of his (and his family's) life is free.
If those numbers sound doable to you right now, you're also free. You don't have to read any more blog posts or do any more research. You're done. See you in Zehuatanejo! Or somewhere else.

But you probably have some questions.

My expenses are bigger than $27,000. What then?
And what if I don't have that much saved and won't any time soon?
First, if your expenses are more than that, you could go on a expense-cutting mission and cut out things you don't need in your life. You might be surprised at how much money you waste each month. I know I've wasted money on stupid things.
Or you could save more money. Let's do the numbers.

If your expenses are $5,000 a month, then you have annual expenses of $60,000.
$60,000 times 25 = $1,500,000. If you can save that much, again, you're all set--if you like Index Funds.
Second, if saving $675,000 is not doable, it's not over. Not at all. All you'd need to do is make more than 7% per year.
Keeping MMM's example, if you could make 15% per year and have $27k of expenses, you'd only need about $350,000 to retire comfortably. That's a much smaller number.

And that's the Secret. Once you know your expenses, all you have to do is find a vehicle that produces the necessary returns. If you believe that trading is impossible but Index Fund investing is real, then your blueprint is above.

If you totally disagree with the idea that trading is impossible, then you have all sorts of crazy options.
I'll leave you with one of those crazy options.

Let's take a robot I've traded since 2014. That's not 100 years of proof but it's not yesterday either.
If you used a moderately aggressive trade size and had $27,000 of expenses per year, you could hypothetically retire on a $150,000 nest egg.
To repeat: If you had $150,000 and used that simple robot, you would have been able to hypothetically pay your bills and have your nest egg grow slightly in the past three years.

That's only if you believe in trading, though.
Talk soon.

A game plan or a road map Maybe For Trading Models and Trading Systems Design, at least something to ponder upon .

In order to become a systems designer, in my opinion, you need to understand the following concepts:

1. What a historical statistical edge means and how to quantify it. (Average Maximum Favorable Excursion (MFE), (Average Maximum Adverse Excursion (MAE) = How to measure a system's edge

e-ratio: How to measure your trading edge in 4 easy steps

1. What curve fitting is and how to avoid it.

1. How to implement rock solid risk management in Forex by using dynamic stop loss distances according to the current volatility of a currency pair and consequently reduce position size (Position Sizing) or increase it depending on the stop loss distance.

http://www.vantharp.com/Table-of-Con...tive-Guide.pdf

1. Understand and perform advanced studies such as Walk Forward Analysis and Rank Analysis for parameters selection with greater likelihood of positive performance in the future.

1. Understand worse possible draw downs of your system in terms of percentage as well as days by using advance tools such as Monte Carlo simulations.. (Ultimately, this ability is the one that will help you stick to the system during the inevitable bad times, because you'll know what to expect and you'll know when there is enough evidence to assume that the edge exploited by the system has disappeared).

Useful resources for learning about mechanical trading systems

Design of a EURUSD Donchian breakout strategy with proven statistical edge
Free Expert Advisor Included

Interesting FF Thread discussing this : How do you gain, and measure, your trading system's statistical edge?

the-lazy-trader.com and all its products are Copyright by The Lazy Trader and property of Lazy Trading LLC. All Rights Reserved.

To Read :
An expectancy analysis of Regular MACD Divergences for the EURUSD currency pair

Comparing Backtesting and live trading system execution: After one million trades

Trading Systems Coding

WHEN TO TURN YOUR SYSTEM OFF AND WHEN TO TURN IT BACK ON

One of the most difficult decisions that every automated trader has to make is when to turn the system off because its performance is starting to be questionable and when to turn the system back on because it is getting back to profits. In this article, I will try to describe the way I see it.

First of all, I need to say that this is one of the most difficult questions in automated trading. In the past, I made a lot of mistakes by turning the systems too early off or by turning them too early back on. To make things even more complicated, out of many ways that I have tried, there isn’t one rule that would stand out (negatively or positively) among others. Therefore, it is important to pick one and never break it.


TURNING THE SYSTEM OFF

1. Turn the system off when it exceeds 1.5 times of the drawdown of your backtesting equity

I set this rule in my early beginnings. There are several important facts about it that I need to point out.

First of all, this rule is good and bad at the same time. It depends on the backtest equity you use. In the past, I preferred to pick one optimization parameter set and apply it to the whole data history. More recently, I have started using regular reoptimization, when I combine several out of sample periods (each with different parameter set) and create one out of sample equity.

Retrospectively, I must admit that in the case of one parameter set applied to the whole data history, this rule of 1.5 times of the drawdown wasn’t really the optimal solution. The equity of one parameter set was too “in-sample” - i.e. the backtested history was almost always better than live results (which is usual). Therefore I turned the systems off too early and experienced losses quite often - should I have the system turned on a little longer, the system would have, in most cases, recover.

But you get completely different results when you use equity curve composed of several out of sample periods - as part of regular reoptimization. This equity is far more realistic in terms of what future results you should expect. So far it seems that this equity, composed of several out of sample intervals, is really realistic and the rule of 1.5 times the max. historical drawdown works very well in this case.

2. To determine the moment when to turn it off, use Monte Carlo drawdown

Despite the simplicity of the concept described above, I prefer the second method - using Monte Carlo analysis.

Again, you need to consider if you work with equity that uses just a simple parameter set, or if you work with equity curve composed of several out of sample intervals.

If we use a single parameter set for the whole history, then I find the Monte Carlo method better than the rule of 1.5 times the drawdown. When using Market System Analyzer for Monte Carlo calculation, you will get drawdown much bigger than 1.5x the drawdown and you don’t turn off the system too early. Moreover, what is really important here is that Monte Carlo really makes sense as the distribution of your future profits will be every time unique and different from the previous ones. So I consider Monte Carlo as a fundamental (and for me a primary) tool.

Recently, I have started to incline more to using Monte Carlo, even on the equity composed of several out of sample periods. I agree that drawdowns that you will get using this method are not very nice. On the other side, the numbers will prepare you for the worst possible scenario, so that you can create your portfolio wisely and capitalize properly. This is the method I currently use. Though it is conservative, it matches my trading style.

Most of the time I use equity curve composed of out of sample intervals, I run the Monte Carlo Analysis, note the 95% confidence level and the maximum drawdown that I get there is the point when I turn my system off - in case it is exceeded.

This is the approach that makes the most sense to me.


TURNING THE SYSTEM BACK ON

1. Turn the system back on when the equity gets above the point when it was turned off

When can I turn the system back on? It is even more difficult question then when to turn it off - at least for me. Many systems come back to life and start being profitable again. I have experienced this many times. One of the rules you can follow is to note the point when you have turned the system off and turn the system back on when the system gets above this point. Usually, the strategy continues in the drawdown for some time after you turn it off, but then it starts growing up again and quickly gets to the point when you turned it off. This approach I consider pretty aggressive, so let me get to the modification of this method that I prefer.

2. Turn the system back on when it is “fully recovered”

For a long time, I have used a rule to turn the system back on when it is fully recovered and makes new equity high. This rule works pretty well, even though the recovery sometimes can take up a year, or even longer. Still, I brought back several systems back to live trading using this rule and I consider it acceptable.What bothers me on this approach is that is too “binary” and also the fact that the recovery is sometimes so fast and so profitable that you miss some really nice profits. But on the other side, there is the previous method, which is really too aggressive for me.So, what I find to be the best approach is the combination of both.

3. Combination of both using progressive position sizing

The rule is to turn the system back on as soon as it reaches the point when it was turned off (method #1), but start trading it with a minimum number of contracts. As the system recovers, we start adding some more contracts.

Let’s say we have traded this system with three contracts. As soon as the system gets above the point when we have turned it off (or some acceptable level above this point), we start trading it with 1 contract. If the system recovers to the half of the drawdown, we add the second contract. And if the system gets fully recovered, we add the third contract as well.

At the moment, I find this method to be the best one. Currently, it is my preferred way as it uses the best of both methods.


THE RULE OF THUMB

Whatever rule you decide to follow, the most important is to keep using just one rule. Be absolutely conscientious. I have a lot of students who lost a lot of money just because they didn’t turn the system off at the pre-defined point. They switched themselves to so-called “hope mode” and they started hoping that the strategy will turn up and start growing again. But this moment never came and their loss got bigger and bigger.

You must be uncompromising in keeping of these rules and comply with them to 110%. It is painful to turn off the system, we have spent a lot of time on. But this is why we have a portfolio - we will always have systems that will fail, despite all our effort. We are not in a secure business, we are in the business with risks that we need rationally and professionally manage and control. The good news is that it is possible.

MY LITTLE SECRET: APPLICATION OF MONTE CARLO

Even though I have been living for years just a few hours drive from Monte Carlo, I've visited it just recently? (Yes, I traveled to over 60 countries but I almost dont know my own neighborhood!). Yet, Im in contact with Monte Carlo every single day. In fact, Im in love with Monte Carlo! :-)

What Im really talking about here, is a Monte Carlo Analysis (often abbreviated to MC or MCA), of course, not about the country of luxury yachts and super rich people. Monte Carlo Analysis (MCA) has been one of my favorite tools since the very beginning, perfectly fitting my rather conservative trading style.

So, what is it about? It is a very simple tool that can help you manage your risk in a better way, prepare you for realistic trading scenarios (I wrote about this in another important article) and give you a realistic estimation of how big your trading account should be. Remember, the only thing you can really control in your trading is a risk. Therefore, you should be damn sure you do it really well! I was very fortunate to come across MCA in a very early stage of my trading career. I have already been using MCA in my past; when I had been using a quite simple discretional day trading system (more than 10 years ago). Since then, Ive developed very important habits to use MCA for every new system, my overall portfolio, and for making important risk-related decisions.

How exactly does MCA work and how do I use it?

The MCA principle is very simple: Its goal is to take all the trades from your backtest (backtesting is the very first and highly important step in a successful trading. Ive always been backtesting extensively, even when trading discretionarily and using only Excel spreadsheet, putting all the trades into it manually) and randomly shuffle the order of the backtested trades many, many times (even up to 10.000 times) to see different outcomes of my trading results and trading equities when the order of the trades is different from backtest results. Why? Simply because the future order of your trades will very probably be highly independent of the past order! In other words, get ready for your future trading equity to look much different than the backtested equity because the order of your trades will be different as well! And although your trades will be similar in its nature, the different order of wins and losses will produce significantly different characteristics than the static backtest especially characteristics like Maximum Drawdown (among others). Many beginners are surprised when their live trading equity looks different than the backtested one and they often think that their system might be broken, but it often looks this way just because they havent performed the MCA and arent ready to face the reality!

So, lets be more practical here and see some examples. In general, you can perform an MCA in an Excel Spreadsheet (Im sure there is MCA in Excel on the internet), or use some more advanced, commercial tools, like Market System Analyzer, which I often use.

In its essence, it usually works like this:

1. You take all your backtest results, the more, the better. If you have just your P/L values of all your trades, that is sufficient.
2. You randomly change the order of all your backtest trades (you shuffle your results). With the trade order changed, there will be a different worst case drawdown than the one you have from your backtest results. Youll note down the value of the new maximum drawdown obtained from the randomization of the trades order.
3. You repeat this process many times. The required minimum is 500 times. However, my heavy testing of MC concepts shows that you should use many more iterations preferably 10,000.
4. Now youll have 10,000 different variations of the worst drawdown (each iteration will produce a different worst max drawdown value). What you need to do, is getting a so-called 95% confidence level.
5. It simply means that youll sort all those 10,000 different values of the worst possible drawdown from the smallest to the biggest. Now youll find the line number 9.500 and that drawdown value you find on this line is the one that represents the 95% confidence level.
6. And this is your number. This is the real worst possible maximum drawdown, which youll probably experience in the future (in live trading). This is the number you need to be prepared for and to use for your capitalization. When this maximum drawdown is exceeded by even a bigger one in real-time trading, you should seriously start questioning your strategy its lifetime might be at its very end.

An example

As I already said, MCA is an absolutely essential and crucial concept for my trading. I use it, in many ways (new and creative) every day. Its the most important part of a workflow for any serious trader. Its the best (and perhaps the only) way to build a bulletproof defense for your trading.

Therefore, Ill close this article with an example, which should make the MCA concept really clear for anyone.

For the purpose of this example, I took my own ATS called Tom's BOSS. I took one of my current parameter sets and upload the data into MSA software. This is how the equity on emini Russell 2000 market looks like:

https://static.wixstatic.com/media/9...ed5cbc2853.png

The important part is the maximum drawdown, which is, as you can see, in this case, 3,300 USD.

Now, let's shuffle the equity several times simply randomize the order of the trades. This is the same system; nothing has been changed except for the order of trades (which is, btw., one of the many possibilities of the future trades order):

https://static.wixstatic.com/media/9...222559e682.png

As you can see, the maximum drawdown has now popped up to 7,030 USD! And all it takes is to use a different order of your trades.

So, let's perform a full MCA. Let's shuffle our trades 10,000 times and see the maximum drawdown at the 95% confidence level. This is the setup Ive used:

https://static.wixstatic.com/media/9...2b2c281545.png

And here you can see the results:

https://static.wixstatic.com/media/9...6ce7ea13f3.png

As you can see, the worst possible drawdown is 7,530 USD. This is a highly probable drawdown that you can get any time in the future in your live trading!

So, this is the number you need to work with, to get ready for and to capitalize on properly. This is what the future might look like (and from my experience, it often does), no matter what your original backtesting maximum drawdowns was. This number is the only serious one you should always consider. Dont fight this concept. Its one of the most important concepts in trading. Ive been extremely lucky to use it since almost the beginning of my trading career.

Author: Tom Nesnidal (more about me)

To Read :

Automated Trading & Backtesting Course - Part 1: System Development
Automated Trading & Backtesting Course - Part 2: System Development

Build Better Strategies Part 1
Build Better Strategies! Part 2: Model-Based Systems
Build Better Strategies – Part 3
Build Better Strategies – Part 4
Build Better Strategies – Part 5

Build Better Strategies!

Enough blog posts, papers, and books deal with how to properly optimize and test trading systems. But there is little information about how to get to such a system in the first place. The described strategies often seem to have appeared out of thin air. Does a trading system require some sort of epiphany? Or is there a systematic approach to developing it?

This post is the first of a small series in which Ill attempt a methodical way to build trading strategies. The first part deals with the two main methods of strategy development, with market hypotheses and with a Swiss Franc case study.

Strategies come in two flavors
You can use mainly two methods to develop trading systems: model-based and data-mining. A model-based system starts with a model of a market inefficiency based on trader psychology, economy, market microstructure, or any other price affecting force. The inefficiency produces a price curve anomaly or pattern that deviates from the random walk and can when predictive be used for a trade algorithm. Examples of model based trading methods are trend following, mean reversion, price cycles, price clusters, statistical arbitrage, and seasonality.

The problem: A model is not the reality. It is a simplified image of it. It can not be proven and can often not even be falsified. Its validity can only be determined by its effects on the price curve. The usefulness of this method thus depends on the significance and long-term stability of its price curve anomalies. For judging this you need good test algorithms.

The pure data mining method works the other way around. It just looks for price curve patterns and attempts to fit an algorithm to them. By which market forces the patterns are caused is of no interest; only assumption is that patterns of the past will repeat in the future. This allows the generation of trade systems, often, but not always with machine learning software. The most popular methods in this approach are trial-and-error TA, candle patterns, regression, autocorrelation, k-means clustering, neural networks, support vector machines, and decision trees.

The advantage of data mining is that you do not need to care about market hypotheses. The disadvantage: those methods usually find a vast amount of random patterns and thus generate a vast amount of worthless strategies. Since mere data mining is a blind approach, distinguishing real patterns caused by real market inefficiencies from random patterns is a challenging task. Even sophisticated reality checks can normally not eliminate all data mining bias. Not many successful trading systems generated by data mining methods are known today.

Are you cleverer than the market?
Obviously, no trading system would work when market inefficiencies do not exist. And it would not work either when they exist, but can not be exploited since better equipped players are doing that already. In this first part of the mini-series I look into the possibility of trading better than the majority of market participants, a prerequisite of a successful strategy.

The three hypotheses of market efficiency that youll hear from time to time are as follows:

1. Hypothesis A: The markets are efficient. Prices follow real events, such as the publication of company results, and reflect the real value of the asset. All traders are informed, decide rationally and act immediately. Price curves are mostly random-walk curves with no information for predicting future prices. Technical trading systems can not work, or if they do, its just luck.
2. Hypothesis B: The markets are not efficient, but their inefficiencies are of no value for private traders. Only large trading firms and hedge funds can exploit them successfully, since they have lots of capital, very fast computers, very experienced analysts and very clever quants much more intelligent than you. Beware of entering their terrain, or else youll become their prey.
3. Hypothesis C: Enough market inefficiencies are free for you to exploit. Large trading firms and hedge funds are too slow and cumbersome to tackle them effectively. Their capital and their fast computers give them no real advantage in the game that youre going to play. Neither do their clueless analysts, overpaid traders, and overestimated quants.

Not many today do still believe in hypothesis A. It can be easily shown that most price curves do not follow a random walk (a fellow blogger recently posted a great article about Hacking the Random Walk Hypothesis). And the markets are anything but rational or effective. Counter-examples are plenty. Jack Schwager, in his book Market Sense and Nonsense, listed cases of blatant market dumbness and grotesque analyst failures. More often than not, asset prices are far, far away from their true value. Although all this is anecdotical evidence, a pattern is visible. The markets react fast and firm when rumors or news give them a clear direction. But when the information is a little more subtle and requires a minimum of interpretation, they react slow or not at all. Heres the story of a typical example.

The Swiss Franc case
In September 2011 the Swiss National Bank established a price cap to the Swiss Franc. Purpose was protecting the tourism and export industries against an overvalued currency. The limit was set to an EUR/CHF price of 1.20, and the SNB vowed to defend it against all enemies.

A price cap is a rare and striking market inefficiency. It can immediately be translated into a highly profitable, almost risk-free trading system (how this works is explained below). So you would normally expect a strong market reaction after the EUR/CHF price move to 1.20. But the reaction was a long time in the coming.

No doubt, Switzerland is an obscure European country and for the major US trading firms probably known for cheese, if at all. They did either not notice the price cap, or they had just forgotten to equip their European offices with modern communication gear. So it took the mounted messenger from Europe three months riding over hill and dale, sailing over the Atlantic Ocean, maybe fighting off brigands, pirates, and indians on his way, to reach New York City and shout: The Swiss have a price cap!.

But what the heck can you do with a price cap? By January 2012, large market participants had finally come up with an idea. Not something as subtle as a trading system. Instead, they began to buy mad amounts of Francs for bringing pressure on the EUR/CHF price:
http://www.financial-hacker.com/wp-c...15/11/chf1.png

EUR/CHF price curve, September 2011 August 2012
The obvious idea was that when there is a price boundary, there must be some profit in breaking it. A lot of effort, patience and money was put in that game. From May 2012 on the EUR/CHF price was nailed shut to its 1.20 limit. But alas, the price cap collapse did not happen. You do not mess with the SNB. During 2012 the Swiss erected a wall of 200 billion dollars for defending the price cap. The attackers never had a chance. The first gave up in September 2012, and by the end of January 2013 all had retreated with their tails between their legs (and probably painful losses):

http://www.financial-hacker.com/wp-c...15/11/chf2.png

EUR/CHF price curve, September 2012 May 2013
Now the way was free for algorithmic systems. During the 2012 CHF battle they were forced to inactivity, since private traders and hackers lack the capital to participate in a market manipulation game. In January 2013 the first hackers started to exploit the market inefficiency with a specific method, a Grid Trader.This turned out a money-printing machine.

The money press algorithm
A grid trader is a very simple system. It places pending long and short trades at a fixed grid above and below the current price, with profit targets of the same grid distance. So trades are opened and closed whenever the price crosses a grid line in any direction. Such a system has a hypothetical 100% win rate, since trades close either in profit or not at all. But grid traders normally use a virtual hedging mechanism that closes an open position instead of opening a new one in opposite direction. This improves the total profit by reducing trade costs and margin. But it allows trades to be closed with a loss. So the real win rate of a grid trader is in the 60% area.

This is the Zorro script of such a grid trader: (Attached Pic)

A grid trader is a typical model-based system. It assumes that some market force keeps the price inside a channel. This is the case here: The cap prevents the EUR/CHF from falling below 1.20, but it also prevents it from rising too high, since the SNB must eventually buy back all the Francs they have sold for defending the cap. The mathematical model of this would be a random walk with a 1.20 boundary and some drift term that pulls the price down. Such a constraint is a prerequisite for a grid trader; without it grid trading would be just high-risk gambling and is consequently listed in the irrational trade methods collection.

This is the P&L-curve (blue) of the above script applied to the EUR/CHF in 2013:
http://www.financial-hacker.com/wp-c...15/11/chf3.png

EUR/CHF grid trading P&L curve 2013
We can see that large price fluctuations, as in January and May, cause large drawdowns (the red underwater peaks in the chart). But since the fluctuations have a limit, we can estimate the maximum loss and just keep enough capital on the account. This way the above script produces an annual return of 130% and a Sharpe Ratio of 1.7 with virtually no risk ( as long as the price cap stays in place).

The news of such a trading strategy slowly spread in 2013. More and more private traders and financial hackers, and also more and more large market participants jumped on the bandwagon. Three years after installation of the price cap, thousands of such systems sat on the EUR/CHF price curve like leeches and sucked off money.

The result was a continuously falling price volatility:
http://www.financial-hacker.com/wp-c...15/11/chf4.png

EUR/CHF price and volatility, July 2013 Dec 2014
Lower volatility means lower profits to a grid trader. More capital must be invested and the grid must be tightened for compensating. But there is a natural limit. You can not have a grid size smaller than the trading costs. By autumn 2014 the volatility was close to zero. And this was accompanied by an ominous price downwards drift, as if some large market participant (possibly the SNB itself) would continously sell EUR and buy CHF in anticipation of some future event. That would have been high time for private traders to retreat from the game. Of course, thickheads like me didnt. It is well known what then happened to the Swiss Franc:
http://www.financial-hacker.com/wp-c...15/11/chf5.png

EUR/CHF price, January 2015
In the morning of 15 January 2015, the SNB gave a press conference and announced the cancellation of the price cap. The EUR/CHF fell in minutes like a stone from the 1.20 limit to below parity. Obviously a fast and extreme market reaction very different to the introduction of the price cap 4 years before. The price drop killed many accounts and even a few brokers. By the way, the real value of the EUR/CHF, based on the relative buying power of the two currencies, was in the 1.50 area all the time.

What can we learn from this and from similar examples?
Conclusions

1. The financial markets react immediately and often hysterically on news with a clear price upwards/downwards direction.
2. The markets react slow or not at all on more subtle information. It can take years until they become aware of new inefficiencies or trading methods.
3. The markets prefer brute-force methods. Complex strategies are normally only used by a small part of market participants.
4. Simple systems based on very obvious inefficiencies can be extremely profitable, but have a limited lifetime.

The next parts of the Build Better Strategies series will deal with model-based systems, with known market inefficiencies and with a methodical approach of exploiting them.

⇒ Build Better Strategies Part 2

Tuning up the turtle
Breakout Trading Technique article collections: BASIC and ADVANCED

Love it Bass. Keep em coming. The Financial Hacker drips with quality. JCL clearly knows his stuff. :-)

PS. Just read this...ouch....but you can't help a small giggle.