Have you heard of algorithmic trading, high-frequency trading or algorithmic trading and don’t know what it is? In this article we delve into this type of trading although we already anticipate a good definition: it is a form of investment in financial markets that is based on algorithms, rules and automated processes.
What is algorithmic trading?
The trading algorithmic (aka algorithms “black box”) is the process of using computers programmed specifically to follow a defined set of instructions, ie an algorithm.
“Algorithm: according to the RAE, an algorithm is an ordered and finite set of operations that leads us to find the solution to a problem.”
The aim is to make investments to generate profits at a speed and frequency that would be impossible for a human to do. This algorithm is based on time, price, quantity, or any mathematical model. In addition to profit opportunities for the investor, automatic trading makes markets more liquid and trading more systematic, since the impact of human emotions on trading activities is ruled out.
Writing a computer program with these characteristics is not too difficult using a few simple instructions, even if you don’t know development or code. The machine will be able to automatically monitor the price of stocks and assets and the moving average indicators (it is the average value of the price of an instrument over a period of time). This allows the system to place the buy and sell orders when the conditions that have been defined are met. In this sense, algorithmic trading is more precise than human beings: it will enter the market and exit it at the right time, neither before nor after.
Thus, the investor no longer needs to monitor prices and charts in real time, or place orders manually. The trading system does it for him constantly, correctly identifying the commercial opportunity, according to the previously established rules.
By the way, at the beginning we mentioned if that “high-frequency trading” sounds to you. Is it the same as algorithmic trading? Not really. The HFT (High Frequency Trading) involves making operational trading in less than a second, ie, it is only a specific practical and concrete that does not have to be based on algorithmic trading.
How to carry out automatic trading successfully, steps to follow
To be successful with these operations, you need to understand the importance of adhering to a set of rules that has guided traders of all sizes and with different trading accounts. Each rule alone is important, but when they work together the impact is even stronger.
Let’s see what they are:
Always make a plan
With today’s technology it is easy to test a business idea before risking real money. Applying trading ideas to historical data (known as backtesting ) allows traders to determine whether the trade is viable, as well as seeing the expectation of the plan logic.
Once good results are shown, the plan can be carried out, yes, following what is established because making decisions outside of what is already outlined is considered a deficient negotiation and destroys all the previous work.
Consider trading as if it were a business
To be successful, you have to approach trading as a full or part-time business, but not as a hobby or a job. If you approach it as a hobby, you will not have a real commitment to learning and trading can be very expensive. As a job it can be frustrating, since you will not receive a regular payroll for it. Trading is a business and can incur losses, expenses, uncertainty, tax, risk and of course stress. As an entrepreneur, you are essentially the owner of an SME and you must establish your strategy to maximize its full business potential.
Use technology as a competitive advantage
Trading is a very competitive business and it is logical that the person who is managing it makes the most of the technological tools at their fingertips. Charting platforms allow investors an infinite variety of methods to view and analyze the markets. Backtesting an idea based on historical data before risking your money can save you an account, not to mention what you save in stress and frustration, etc …
Algorithmic trading and artificial intelligence
It is clear that algorithmic trading and artificial intelligence go hand in hand: automation has to do with the virtual and leads us, in a way, to a much more predictable world.
It has its good part, as we have already explained: that speed, precision and automation that a person cannot reach, for example. But … we are talking about artificial intelligence, not real. That is, we are talking about copying and establishing rules, not creating. It is still a machine that interprets data, that executes processes, but does not lead to actual creation.
Let’s reflect on this statement by Alex Lu, from the artificial intelligence company for trading Kavout:
“We can do this today in natural language processing, which means that we can make a computer understand the meaning and semantics of what a certain person is saying. This could be a positive or a negative thing for certain companies, and that is something we call “sentiment analysis.” We are building something called a sentiment measure, which means that we are making use of all the data that we collect from traders, news, blogs, etc., and we are putting it together into something we call a “sentiment measure.” For example, we collect Insiders’ data, so that we know which company or CEO is selling these or those shares. If we put these two data sets together we can have a more accurate approximation of what people are thinking about stocks “
Of course, a priori and according to his words, we are talking about a technological innovation that allows us to be more productive in a shorter period of time. But it should be borne in mind, for example, that in trading, it was never easy to make a profit with the simple observation of charts and indicators: there is much more behind it.
On the other hand, an algorithmic trading system does not mean that it will be profitable where a “real” trader was not before, that is not something that artificial intelligence can change. That is, with algorithmic trading we can automate an incredibly good strategy, but also a disastrous one.
One of the main characteristics of artificial intelligence in trading is that it obviates human feelings, which in theory makes it more objective since it would isolate us from the control of the emotions that we talk about and influence psychotrading. But AI has a great handicap: we will not be able to measure the ability to assess whether the situation of what we are doing is correct or the opposite.
Conclusion: will robots replace people for trading? Actually, the question is not that, but to promote your abilities and skills to use your own criteria with precision in the execution of a robot.