It is an obvious fact that industry 4.0 has brought us a very interesting horizon. this intriguing horizon represents very advanced steps in human history today. It is even possible to say that it represents the most advanced step. Undoubtedly, industry 4.0, which still has a great reality outside of humanity's capacity and horizon, is a big step to be discovered in terms of technology and software. These developments provide humanity with great opportunities and humanity uses these opportunities as much as it can today. however, as The Finage family, we aim to take this one step further.

 

We are developing software that will be difficult to explain by us and to be understood by you. In addition to making these data available to you, facilitating their use and explaining the way of use has become a problem that must be overcome by developers today. In order to overcome these difficulties in The Finage live market data, we took a step starting with our blog posts. In order to take this step further, we decided to inform you about the software in our blog posts. We hope you get to know our work, products, and Finage better.

 

In our blog post today, we aim to inform our valuable readers about what algorithmic trading is while talking about the python programming language. We recommend that you review the Finage page before moving on to our blog post. We recommend you to take a look at other blog posts where you can find detailed information about Finage Live Market Data API types such as Forex Data API, Stocks Data API, Fundamental Data API, and Cryptocurrency Data API products. Don't forget to contact Finage Consultants for suggestions, contributions, and teamwork with us. 

 

Wall Street when he met with computer automation, the industry has changed forever. One reason is, of algorithmic trading - or as Investopedia explains, "the price, and instead of orders using an automated process to bring their purchases and sales of pre-programmed instructions to take into account variables such as timing and volume." This basically means that you can use computers to help you make informed investment decisions.

 

Algorithmic trading and developer teams by only banks and large institutions is not a tool used by the customer teams. 

There are certain ways and stages to learn the basics of algorithmic trading. These are sold as courses by some places for a certain fee. It is possible to list the progressing stages in projects as follows.

The first project is an equally weighted S&P 500 splitter. The S&P 500 is the world's most popular stock market index. In this section, you need to create an alternative version of the S&P 500 Index Fund where every company has the same weight.

 

The second project is a quantitative momentum determinant. Investing in momentum means investing in assets whose price increases the most. You will create an algorithm that implements this strategy. First, you will develop a strategy that uses a measure of momentum. Then you'll expand to create a more complex strategy that uses multiple metrics together.

The final project is a quantitative value decisive. Value investing, perception means investing in stocks traded below the actual value. As in the previous section, you will create a strategy before using a single measure of value. You'll then expand to form a more complex strategy that uses a combination of five different value metrics.

 

These stages should not just remain as stages. Of course, during the implementation of projects, you need to answer some questions in order to gain about algorithmic trading. Finding these answers may not be as easy as you think. However, we have no doubt that it will contribute to your algorithmic trading learning.

 

With Python, the NumPy library uses the code to accelerate this course. NumPy is the most popular Python libraries to make numerical calculations. NumPy, though written in Python to be used, the basic functions are written in C language, which is a lot faster.

With this information, you can find more information about API systems, software, and programming languages about Automatic Updating of Stock Exchange Data. actually knowing enough to decide which area we can call the most important to continue doing research.

Finage data are data developed in line with this information, and API types are developed to provide you with financial data. Historically and fundamentally, the development of data provides many opportunities for users.

Finage consultants are ready to team up with you to learn more about API types and uses.