05/29/2019
By
MJV Team

Algo Trading: how algorithms are impacting the financial market

Algo Trading, or Algorithmic Trading, is a concept that describes trading carried out through algorithms.

This new reality is increasingly present in the financial world and therefore needs to be understood by the organizations in this market.

In this article, you will know exactly what is Algo Trading and how it can impact your business.

You will also see why it is important to develop or adopt algorithms in your company. Check it out!

What it is and how it works

We can describe Algo Trading as a “trading algorithm”, the use of a trading system that facilitates transaction decision making in financial markets using advanced mathematical tools.

In this type of technological operation, the need for human operator intervention is minimized and therefore decision making is very rapid. This allows the system to take advantage of any profit opportunity that comes on the market long before an analyst can identify it.

As large institutional investors deal with a huge amount of stock, it is they who make the most use of Algo Trading.

It is worth remembering that an algorithm is a process or set of rules defined to perform a given process. Thus, Algo Trading uses computer programs to trade at high speed and volume based on various predefined criteria such as stock prices and market-specific conditions.

For example, a trader may use algorithmic trading to execute orders quickly when a particular stock reaches a certain value or falls below a specific price. The algorithm can determine how many shares to buy or sell based on these conditions.

Once a program is put into practice, this executive can then sit back and relax, knowing that negotiations will take place automatically under pre-defined conditions.

What the benefits of Algo Trading for the financial market are

Going into the detail of the advantages that Algo Trading offers to financial institutions, we have the automation of the trading process as a great asset.

By using algorithmic trading solutions, it is possible to ensure that orders are executed in what is considered optimal conditions of purchase or sale.

As orders are made instantly, investors can be assured that they will not miss out on good opportunities. Manual orders, by contrast, do not come close to mimicking the speed of algorithm trading.

Moreover, since everything is done automatically by the computer, human error is virtually removed from the equation (assuming, of course, that the algorithm is developed / programmed correctly).

In addition, algorithm trading usually limits or reduces transaction costs, allowing investors to retain even more profits.

Finally, algorithm trading eliminates the dangers of acting on emotion rather than logic, one of the major problems for investors.

What the risks involved in Algo Trading are

It is also important to know that one possible disadvantage of algorithmic trading is that a simple error can escalate rapidly, resulting in exorbitant losses.

It is one thing for a financial operator to make a bad connection and lose money in a single transaction, but when one has a faulty algorithm, the results can be totally catastrophic.

That’s because a single algorithm can trigger hundreds of transactions in a matter of seconds, and if something goes wrong, millions of dollars can be lost in the same amount of time.

Therefore, it is essential that the programmed algorithms are 100% reliable, guarantee total data security and also avoid loss of money.

How important is the Data Driven culture to exploit the advantages of Algo Trading

A fundamental point for financial market companies that want to adopt solutions and processes based on Algo Trading is the development of a Data Driven culture.

Data-Driven culture is nothing more than the practice of using data in a variety of business processes in a systematic and continuous way. It is also called data-driven management.

Companies with a strong Data-Drive culture establish processes and operations to facilitate the acquisition of information needed by employees. They are also transparent about access restrictions and methods of governance. This leads to more mature techniques, as is the case with Algo Trading.

In companies with a strong data driven culture, teams are better able to seek data to adjust strategies and objectives and can play a more active role in analyzing and measuring processes, projects and results.

Here are two very useful approaches to developing a Data Driven culture that pave the way for efficient use of Algo Trading solutions and services.

Data Science

For the development or implementation of trading algorithms that really make a difference in businesses, it is interesting to invest in a Data Science strategy.

Data Science in the business sense is the study of where information comes from, what it represents, and how it can be transformed into a valuable resource in the creation of business strategies.

A business that has a good Data Science strategy has tools and personnel (or hires specialized services) prepared to mine large volumes of data – both structured and unstructured.

This way, it can for example, identify standards, anticipate and control costs, increase efficiency, recognize new market opportunities and enhance its competitive advantage.

Design Thinking

Design Thinking is a structured approach to innovation. It has human beings as a focus and seeks to generate solutions that align the desire and needs of consumer users with the generation of value for the business.

With the method of Design Thinking, it is possible, among other things, to awaken the “data-driven mindset”, that is, to change the traditional mentality to a strategic and data-driven action.

With this approach it is also possible to idealize and prototype solutions and projects of Algo Trading more quickly and effectively.

With regard to the development of algorithmic trading systems, Design Thinking facilitates efficient, user-centered solutions that deliver tangible results.

The methodology and practices facilitate prototyping and testing, while at the same time accelerating the achievement of algorithmic solutions that are truly adherent to the real needs of the business and, above all, the users.

Conclusion

As you have seen, Algo Trading is provoking a real revolution in the financial market. This new approach, and the pool of tools and practices that revolve around them, are leveraging negotiations and raising the returns of organizations.

But you have to be prepared to take advantage of it, especially as it is about innovative technologies and methods. It requires knowledge, investment in tools and specialized personnel.

How about we help you understand the impacts of Algo Trading on the financial market? Download our Business Analytics: The Data Age has already started e-book now!

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