成功外為トレーダーの割合が比較的少ない, まだ彼らはある特定の類似を共有します。: A well-built trading system, plus the right combination of personality traits and learned behaviors.
もちろんです, the tools are important – Regardless of a trader’s personal characteristics, a successful trader always builds, uses or finds a good Expert Advisor (EA). Most people believe that if they just find the one magic bullet, then everything will be fall into place. As Shaun discusses in the forex robot secrets report, that’s almost never the case.
Characteristics of successful traders
Traders and EA developers who succeed are usually found at one of the two extremes of intelligence: Either they’re highly intelligent, or they’re extremely dim witted. There doesn’t seem to be much middle ground in which “average” developers succeed.
1 つの手, it seems easily explainable that sharp developers should be more successful than “average” ones. まだ, those at the other intellectual extreme are often also more successful than the typical developer.
なぜ?
One theory to explain the trading success stories of traders and EA developers who are outside-the-ordinary is illustrated by this anecdotal experiment: If a mouse is placed into a cage where cheese is found on a particular side of the cage 60% 時間の, と 40% of the time on the opposite side, every mouse will eventually learn to choose the side of the cage where cheese is found 60% 時間の.
他の言葉で, mice are at least intelligent enough to stop guessing and simply choose the pathway which is more often successful. 対照的に, humans generally try to improve their success by finding and improving on some sort of pattern in randomness, even when it’s not there.
This theory may explain why less-intelligent traders can be successful by sticking to a system based on simple rules that win more often than they lose. もちろんです, “home-run” systems that are over-optimized in an attempt to “win everything every time” usually fail.
From the perspective of the mice described in the above experiment, it’s not about getting すべて the cheese every time, it’s about getting enough cheese more often than not.
A trading success story is based on more than just brain power
An automated trading success story may begin with brainpower, but it doesn’t end there. Brainiacs tend to build trading systems based on deep technical analysis. Theories are developed and modified as testing reveals strengths and weaknesses in a given system.
If a mouse is placed into a cage where cheese is found on a particular side of the cage 60% 時間の, と 40% of the time on the opposite side, every mouse will eventually learn to choose the side of the cage where cheese is found 60% 時間の.
しかし, there are plenty of intelligent, well-educated traders, and many of them don’t thrive when they’re involved in day-to-day trading. Significantly, winning traders’ ideas tend to become simpler over time instead of more complex.
An EA can be あまりにも powerful
Being too smart is a handicap that can keep traders from winning, and the power of EAs can also work against them. EA-focused traders tend to drift off course instead of remaining focused on the simple pathway toward trading success.
Without consistency, it’s difficult make any progress, nor measure results effectively. Too many indicators and too many pathways to explore may tempt EA traders to go astray, and wander away from the simple, basic rules that win.
Trading is a process, not a destination
When the trader approaches system design as a process rather than as a fixed destination, the outlook becomes much better. Success is relative, and improvement is ultimately more important than perfection.
たとえば, when a trader focuses on a system’s accuracy, the trade-off usually comes in the form of accepting a less-profitable exit point from a given trade. だから, a trader’s urge to win a slightly-higher percentage of trades often erodes the system’s performance.
対照的に, process-oriented system designs let traders assess how making slight changes in the trade-entry protocol affect the system’s efficiency. と, using expert money-management methods can help by reducing the emphasis on entry and exit protocols.
Emotion in trading can’t be denied, yet it can be channeled appropriately
Emotion is impossible to separate from trading. しかし, it shouldn’t be the reason for trying to develop a winning Expert Advisor.
代わりに, rational reasons for building an EA include situations in which a trader has been trading a given system long-term and wants to automate a proven winner, or finding ways to automate one’s trading based on narrowly-targeted indicators that win more often than not, even without generating perfect signals.
The question isn’t how to to remove emotion – Instead, the question is how to channel it appropriately, especially when the trader or EA developer has made a huge investment in time spent developing a system.
The goal is to develop and implement a consistent system – not a perfect system. When traders swing back and forth between winning and losing, the lack of consistency makes them feel less confident in their systems.
When a trader is “married” to a supposedly perfect system, there isn’t likely to be any trading success story in his or her future.
Work with professional EA developers
Designing a winning trading system takes hundreds of hours of time, plus at least a decade of experience. 前述のとおり, system development is a process instead of an endpoint. まだ, there’s a way to expedite the process – work with a professional developer like OneStepRemoved.
Where are you in your trading journey? Share your ideas below for you how “find more cheese” in the markets.
Clever Shaun! それはいいですね, “don’t try to be smart, use your brain to be unsmart”. Now that’s a challenge! ☺
Let me come back on that one…
Thomas
From Sweden
(with a smile)
ショーン,
Good article as usual that gets you thinking. I’m not a Programmer but more of an ideas type of person, where I employ my smart Programmer to build the EAs for me. Not all of my ideas are good, but all of the EAs do exactly what they should be doing. And like a lot of traders that use EAs, I am always back testing and forward testing looking for the optimal performance. This is where the problem lies I believe.
I tend to have much better trading results when I use my EAs for entry and initial trade management, then switch to manually managing the trades once they are out of the danger zone. Since I have been looking at charts for 10+ 年, you tend to get a feel for how things look, a gut feel I guess, and an EA just can’t do this. Then you may be trading multiple pairs etc, where you are controlling a basket of different trades looking for an overall profit target. On closing this basket, there may be many trades in a losing position individually.
The whole testing thing with EAs is a little confusing as markets do change over time with regards to volatility or daily ranges etc. It bugs me that some say you have to show proof that your EA has worked consistently over the last 5 years or so. A lot can change in this time, and even though your entry parameters may have remained constant, other settings would have more than likely have changed several times.
Probably just like you, I like to keep it pretty simple. No need to go for the home run all the time, keep the trading positions small and manageable so not to get into too much trouble when things do go wrong. Accept your losses and move on. It is all about the big picture and trade management. 乾杯.
おかげで, James. It’s interesting that you mentioned learning the rhythms of the market. One thing I’m hoping to do this year is where I give traders a 30 day challenge to follow a trading system that I provide. My experience with QB Pro is that I’m starting to have a very good feeling of which trades are going to turn out well, and which ones I’m going to be awake worrying about in a few nights. Confining my observations of the market to a set of rules provides a framework where it’s much easier to understand and predict.
[はい], I don’t think it’s realistic to expect a strategy to turn a profit in all market conditions. 2014 was a lot different than 2011, where volatility basically disappeared.
Simple is better. When things are crazy complex, it’s very difficult to know where to look for a problem. If your strategy only uses a handful of tools, diagnosing problems takes almost no time at all.
Great post, If one wanted to learn programming of an EA, where would you recommend them to start? Would you need to know BASIC, C++, C# ?
偉大な仕事を維持します。,
Kind regards,
マーティ
Hey Martin,
I started with no CS background using C#. It’s a great language to learn object oriented programming without getting stuck in high level details. It also translates fairly well into MQL4.
–ショーン
こんにちは
can you give us an idea of how good are the EAs that your clients try to develop?
What percentage of those projects have real probabilities of become a good EA?
What percentage of those projects end in a profitable EA?
After months of using those EAs, what percentage is still profitable?
おかげで
I disagree with the methodology that most clients use. They think they have a strategy so they just build it. I go at it from the other direction. I analyze my core idea with code. その後、, if I see something truly useful, then I expand it into an EA.