The charm of the global stock market lies in its volatile nature. Even a simple “bottle” can bring millions in losses for an organization and to the stakeholders. Long term, strategic, and consistent investment in the stock market has been a fool-proof tool for wealth creation. But, only a few are fortunate enough to put themselves in a position to make a sensational profit.
The massive wave of digital transformation has made it possible to predict and build intricate statistical models using advanced programs based on Python.
Nowadays, modern technology has evolved into an asset for financial institutions. And, financial organizations are transforming into IT companies, not just for monetary aspects but also to gain the speed and competitive edge that technology brings to the table. Today, continuous transactions and massive data pools have allowed financial institutions to focus more on analytics and technology. Over time, it has proved its value by transforming into the main driver of such institutions.
When it comes to the most popular financial programming languages Python takes the cake with its advanced analytical features. Although there are other programming languages like C++, C# and Java but they are no match to Python’s abilities.
Introduction: The Sphere of Financial Investment
Before getting yourself into the world of trading strategies, it’s always recommended to touch on the basic concepts. However, we are definitely not going to start with the basics. If you are looking for python algo trading. We believe you are already versed with the basics of Python. If not, we strongly recommend taking some basic Python courses online. Such courses will teach you the “ABCD” of Python as well as how to work with Python lists, packages, NumPy and Pandas.
Shares and exchange trading
Whenever a company wants to expand its business or launch new products and services, it can utilize shares as a financial medium. A share is an equity ownership interest in an organization that exists as a financial asset and can be exchanged for money. Shares can be bought and sold. Clients and traders exchange shares that can be new or previously owned.
The share prices fluctuate regularly, regardless of the business indicators of the company that issued the shares. The entire process is based on the principle of supply and demand. This makes it essential to perform thorough due diligence.
What is Algorithmic Trading?
The utilization of algorithms in the stock market (algorithmic trading), is the decade’s trend that has completely transformed the market. Modern automatic systems based on Python and other programming languages like C++ and Java can effortlessly surpass humans in speed, endurance and performance. In addition, it is almost impossible to compete with a computer’s efficiency.
The essence of algorithmic trading
Modern traders use algorithms in their work to find the right stocks by using the existing probability of quotes movement in the required range. For making calculations, algorithms use the historical data of a selected asset.
Owing to the market volatility, python developers constantly look for a similar & repetitive pattern and calculate the chance of recurrence in the near future. From a technical perspective, algorithm trading narrows down to identifying algorithms for opening and closing deals and choosing trading robots for their implementation.
There are three ways to find rules :
- Genetic: Algorithms designed by computer systems.
- Manual: This process uses the scientific approach based on physical and analytical models.
- Automatic: Specialized programs based on Python are used to iterate over large arrays of rules and conduct their testing.
Advantages and disadvantages of python algorithmic trading:
Python algorithmic trading can be seen as the up and coming tool that will enhance and transform manual trading exponentially. Algorithmic trading is an effective medium to reduce the shortcomings of manual trading.
The advantages of Python algorithmic trading are as follows:
- Saves time.
- Instant transactions.
- Eliminates human bias stemming from emotional components.
- Reduces the risks of human error dramatically
- The ability to work round the clock.
- High-quality diversification. Generally, a trader has a wide range of assets and strategies in its arsenal, but sometimes it can get quite difficult to use them while working manually. Python backed algorithmic trading aids in accurate diversification of portfolio for reduced risk.
Disadvantages:
- The requirement of sound programming skills ((programming languages like Python, C++, Java, MatLab, knowledge of the specifics of the work of such programs);
- Scarcity of forecasts. Robots are unable to predict, and they can only use historical data;
- The detrimental chance of repeating errors in historical data.
- Programmes lack intuition, which is sometimes simply necessary in stock trading;
- Internet crashes. If there is some issues with your Internet connection, it can cause transactions failure and colossal losses;
Conclusion
What is the purpose of Python algo trading in the realm of trading? Algo trading transforms the stock business by using automated, programmed systems to open trades. In addition, it can also be used to extract profit from the market or reduce the manual burden of monitoring, selecting, and conducting trades in the age of technology.
