What types of automated trading do you know?
A., Algorithmic trading (from early 90’s)
B., Automated trading (from late 90's)
C., High Frequency Trading (from 2000’s)
What does automated trading mean?
The history of automated algorithmic trading dates back to the 1980's, when the world-wide electronic communications network (ECN) was established.
Communication channel between banks, stock exchanges, brokers, investors.
The two fastest communication protocols available today are FIX (50,000 quotes/second) and FAST (1,000,000 quotes/second).
The development of computing (hardware and software) made it possible to create automated trading systems.
These systems are designed to make buying and selling decisions on the stock market instruments without any human intervention, and to handle the size of the positions with risk and reward (money management).
For more information, please visit Wikipedia.
From the late 90's onwards, the public also had the opportunity to automatically develop trading algorithms in different programming languages for different trading interfaces and test their talents and perceptions of the market.
Nowadays, we can choose from a number of trading interfaces and programming languages for development.
Forex FarEast are only develop automated forex robots for MetaTrader 4 only.
Not everyone has the knowledge and experience to develop high quality, high yield/risk automatic trading strategies, that have an advantage over the market.
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A., Low Frequency Trading:
In general, these types of trading strategies are based on Daily, Weekly, Monthly charts and are traded long term.
Overnight strategies with average trading time of several days or even weeks. It does not require any particular technological background.
B., High Frequency Trading:
Here are the trading systems that make decisions on intraday data. In general, systems with lower resolution than the Daily chart, are traded on charts (1,5,15,30,60 minutes). The average time spent trading in these strategies can last from a few minutes to several hours.
It is characteristic of them that the strategy server is very close to the stock exchange, the broker.
This reduces pricing slippage.
C., Ultra High Frequency trading
These strategies are characterized by the fact that trading decisions are made on charts of less than one minute (nano, milliseconds).
Serious software and hardware are required for these strategies.
They feature up to 10,000 trades in 1 nano seconds. Generally, such systems are used by Market Maker and other technology companies.
Their average trading time can range from 1 nano to 1 second. Strategies are embedded in FPGA cards and other CHIPs.
The trading system server is placed close to the stock exchange, the broker, thus reducing the pricing slippage.
Who use automated trading robots?
The factors determining the trading on the stock exchange and the FOREX market are no longer human, but the machine, more precisely the algorithms.
More and more international banks, asset managers and investors are using automated programs for stock exchange trading.
Already 70-80% of US and world stock exchanges are traded by automated programs.
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A., Systematic trading
Everything that is part of a trading strategy is 100% automatic, without human intervention.
Manage buy and sell positions, manage trading volumes, yield and risk, operate fully automatically. There is usually a statistical result of past performance called backtest. With statistics, it's more preferred than Discretionary Trader. Confident and stress free trading, requiring little psychological readiness.
For more information, please visit Wikipedia.
B., Discretionary trading
Trading procedure requiring human intervention. The strategy can work in an automated way, however, trading is executed by human.
It is characteristic that there is no statistical advantage, especially trading is based on experience.
There is no statistical measurement of past performance.
More stress requires tolerance and psychological readiness than systematic trading.
For more information, see the video on Youtube.
It is characterized by short-term intraday trading.
The trader carries out numerous trading within a day, usually on a technical basis.
The trade uses technical indicators, shapes, news data and fundamentals.
It typically uses 1,5,15,30,60 ... minute charts.
For him, the economic trend, macroeconomic trends and impacts are not important.
The trading positions are open for a few minutes to several hours.
It is characterized by long-term, over-the-counter trading.
Over the day, it does little trading, usually takes fundamental, macroeconomic trends and effects, ignores technical indicators and price patterns.
Typically, it uses daily, weekly, monthly charts.
For him, the economic trend, macroeconomic trends and impacts a are important.
The trading positions are open for days, weeks or months.
Algorithmic trading (from early 90’s)
Algorithmic trading uses computer software programs to calculate the price, timing, quantitity and other characteristics of orders, which manual traders can authorize in part or in group of orders.
Not all algorithmic trading is automated as the actual placement of orders can still be done manually using the information produced by algorithmic software.
For more information, please visit Wikipedia.
Automated trading (from late 90’s)
A method of trading where computer software is used to fully automate order generation.
Computers are linked to market data, which is fed into algorithms, and then automatically place orders in the market.
Although the systems trade by themselves, they are controlled by both a risk manager and commands within the software.
High Frequency Trading (from 2000’s)
High Frequency Trading (aka. HFT) is a general term referring to a form of algorithmic trading which occurs at a rate of action only computers can maintain. Best characterized by the sophisticated technology required to minimize response times, such as powerful computers with direct network connections to exchanges (including co-location).
An interesting and informative infographic about the history of electronic trading, see it!
Market making strategy
Mean-reversion (swing trading)
Momentum (trend following)
At a brokerage company of our choice, you need to open a demo or live account.
It is important that the broker company has a trading platform that is suitable for programming automated trading.
MetaTrader 4 is currently the most popular trading platform in the world, with MQL4 as the program language.
It is important that our automated trading algorithm should include buying and selling signals, position management, money management.
Note that different brokerage firms use different order execution, the most popular are Market Maker, ECN, STP, DMA models.
From our point of view, ECN / STP and DMA models are more advantageous, because in this case the broker company does not keep our trading in the house, but releases it to the market.
The metatrader 4 programmable trading robot is called an Expert Advisor, in short EA.
Visit our "MT4 Trading Robots" page and buy an innovative automated trading robot we have developed!
Develop an automated trading strategy that is not just generate great returns on past data, but also generates similar returns on real market conditions, is very difficult!
It's like finding a needle in a haystack.
Thousands of automated strategies, forex robots, expert advisors are offered on the Internet for $ 100 to $ 1000.
90-95% of these strategies are likely to yield only positive results on past data, under real market conditions, they will only produce losses.
There are countless strategies on the internet where in 1-3 years the robot makes more than 100%, 1000% or 10 000% from a capital of $100-$500.
These strategies / robots are usually categorized as FAKE or SCAM.
Be very careful when you meet the yield curves at the bottom of the text!
The reason for this is the "Curve fitting" or also called "Overfitting" effect, for more information on the topic, click here.
In short, the parameters that make up the strategy are very specific for a particular past prices, therefore, the strategy can only yield a positive return for that period, with no predictive effect on the parameters for the future price movements (that is, exchange rate movements that were not part of optimization or testing), cannot give a positive return.
Most of the strategy developers are not using any stress testing method which can validate their trading system.
Because there are no tools available to the average retail trader to get the best knowledge to filter out FAKE or SCAM automation strategies, robots, so it's easy to run, which unfortunately, will often result in total capital loss!
Our company is committed to producing, as far as possible, automated strategies, forex robots, which not only producing great returns on past exchange rates, but also on future price movements.
Let's get an access our state-of-the-art Forex trading bots!
Two types of data ranges are used for automatic strategy planning, In-sample and Out-of-Sample.
The In-sample domain is the data domain, that creates the trading strategy, here we create the prototype model and parameterize the system.
We call the Out-of-sample range the data range that our model has never seen before.
This separate data range serves to verify the authenticity of our model, ie whether our model is curve-fit-or not.
If the yield curves have similar statistical properties within the In-sample and Out-of-sample data range, the yield and risk results are broadly the same, so we can say that our model is authentic/robust.
Unfortunately, in the vast majority of cases, people create automated trading systems that look very good on the backtest (In-sample), delivering amazing returns, but unfortunately, the model has no credibility, that is, no longer able to produce results outside the
In-sample, this is called Overfitting status.
The more the backtest result of our trading system matches the out-of-sample range, the more we can say that our trading system is credible and will probably perform well in a live market environment, the system is robust.
Monte Carlo Simulation is used to test the parameters of the strategies and the risk.
For further validation, use Walk Forward Optimization and Monte Carlo Simulation together.
For more information on this topic, see Wikipedia:
Walk Forward Optimization, Monte Carlo Simulation, Curve Fit, Overfitting, In-Sample/Out of sample
What does Co-location mean?
The essence of Co-location is that the computer (trading interface) that runs our automated trading strategy is as close as possible to the server of the broker company where our live or demo account is running.
The distance between the two servers is measured in millisecond, and we can measure the well-known IP address of the PING broker company.
The smaller the delay in millisecond, the closer we are to market pricing and the lower the price slip.
Our trading orders go to the broker company and he executes for us.
The closer the trading strategy server to the broker's server is, the smaller the slipage, ie the smaller the difference between the price we want to trade and what we actually get from the broker.
So for the sake of efficient trading, and in the vast majority of cases, to trade at the price we really want, we need to be close to the account management broker's server.
To reduce the distance between your computer and your broker company, we need a Forex VPS (Virtual Private Server).
Automated trading robots should work at 0-24 hours a week, 5 days a week.
The FOREX Vitual Private Server helps you keep your PC running constantly.
In addition, we are protected against power outage and internet outage, as FOREX VPS service providers operate reliably within 0 to 24 hours of 365 days a year.
Visit the Forex VPS page and choose a Virtual Private Server provider for your broker account and forex trading bots.