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You can learn how to trade stocks for a living the quickest by using stock trading techniques.
Additionally, stock trading systems can help you live the life you want by enabling you to trade stocks profitably with little work and stress.
A trading system is just a collection of guidelines that specify how you will join and leave the financial markets in order to generate income.
Systematic stock trading is successful because it removes emotion, fosters consistency, and gains a competitive advantage.
This article examines the creation of a stock trading platform, including its high-level design, front-end and back-end technologies, and other factors.
So, what is a trading platform?
A trading platform is a software program provided to traders and investors by certain financial organizations, such as banks and brokerages.
Trading platforms essentially let investors and dealers place trades and keep an eye on their accounts.
Trading platforms frequently come with additional tools that support investors in their decision-making.
These features could include live news feeds, premium research, real-time quotes, interactive charts, and a variety of graphing tools.
Additionally, platforms might be made to cater to particular markets, such as those stocks, currencies, options, or futures.
Commercial platforms and proprietary platforms are the two different categories of trading platforms. Retail investors and day traders use commercial platforms.
They are distinguished by their simplicity of use and a variety of useful features, such as real-time quotes, global news feeds, live, interactive graphics, educational content, and research tools.
Contrarily, huge brokerages and other financial organizations create proprietary platforms that are specifically tailored for their particular trading needs. Public access to these is not possible.
Building stock trading platform
A stock trading platform is significantly more difficult to build and needs specialized teams for each task. In this post,
I’ve done my best to describe how a stock trading platform operates.
Let’s get started.
- A stock’s buy/sell pricing ought to be open to user bids.
- The ability for users to view the ticker, or real-time and historical stock price, is essential.
- Inform subscribers of stock price changes.
- The system must be capable of handling 100k clients.
- 100 million bids each day should be manageable for the system.
- The system must be able to provide historical stock price information.
Stock exchanges are often busy from 9 AM to 5 PM. Thus, throughout the 8-hour window, traffic will be served.
Thus, we are able to determine the capacity for the bidding service for this time period.
We can suppose that the read-to-write ratio in bidding is 1:1.
Taking consumer bids is the responsibility of the bidding service.
The Ticker Service is in charge of displaying the most recent changes in stock price.
The bidding service must accept the user’s buy/sell bids and be able to locate buyers/sellers and execute the transaction.
When a buy/sell bid comes in, we need a matching engine that can find a match with one or more buyers/sellers and then execute the transaction.
If the matching engine is unable to do so, we need to store the bid and try again when the matching bid comes in.
The Ticker Service
The ticker service must provide customers with the most recent stock price and be able to display historical data based on the passage of time.
It is necessary to determine the stock’s current price from completed transactions from the bidding service and keep it in the historical price database.
In order for the ticker service to calculate the most recent stock price, we require transactions that occurred on the Stock DB.
We can utilize a design pattern called Change Data Capture in this situation.
People frequently pick the DB first and attempt to force-fit their case, in my experience.
We must always determine the needs of each database in our services and then select the datastore accordingly, ideally based on the pattern of queries, scalability, and dependability, among other factors.
It should have the capacity to hold billions of bids.
Data should be able to be stored and retrieved with minimal latency and high QPS.
The aforementioned criterion ought to be able to be met by an in-memory sharded datastore.
Stock Transaction Store
Ideally, the transaction should be stored with the ACID guarantee.
If one buy bid matches several sale bids, it should be able to enable multiple transactions to be committed.
We can select any Datastore with an ACID guarantee for this use case.
Former Price Store
A stock’s price ought to be able to be stored based on the current time.
We can select any store that offers time series-based retrieval.
Division of data
The correct data partitioning is a crucial component of scalability. in order for data growth to not be an issue.
You must now have a basic understanding of how to develop a stock trading platform. Let’s now talk about the platform’s key components that need to be taken into account.
Selecting a programming language
By this point, you must have selected the app platform.
Now, depending on the platform for your application, you must choose a programming language.
Thus, a variety of programming languages are available, although some are more popular than others.
Developers favor Swift or Objective C for iOS, whereas Kotlin and Java are the most popular choices among professionals for Android.
Trading app developers choose their tech stack after having a clear idea of the finished product.
Both function well for stock market software development and are appropriate for large-scale projects.
Devs may be influenced by certain technical specifics to go in a certain way. For instance, Angular draws attention with its rich array of services.
Angular provides all the elements required for front-end development because it is an established framework. In contrast, React is a library. You must use third-party tools to implement a certain functionality while utilizing it.
My preference for the backend is between Java and.NET. The development of enterprise-level apps and trading platforms are perfect for both technologies.
They support numerous procedures in the program and aid in the implementation of sophisticated logic.
On a performance and speed level, Java and.NET are likewise very similar. Because of this, choosing one option over another depends entirely on the nature of a given project.
Rapid deployment, scaling, monitoring, backing up, and moving ready software pieces to different environments are all aspects of DevOps’ role in creating a trading platform.
Throughout all of these activities, the stable labor is handled by DevOps tools.
Without involving humans, Jenkins automates a component of the development process. It ensures the app’s steady operation and allows for the continual integration of trade technology.
Software development makes extensive use of smart technology, which is currently trendy.
No exception is made by trading apps. AI and machine learning transform them into strong machines that make sound decisions and generate large revenues.
Trading bots, as opposed to people, are able to quickly and emotionlessly examine enormous amounts of data.
Algorithmic trading is not based on human inputs, whereas AI technologies are, and this takes them one step ahead of algorithmic trading.
Application Programming Interface
Software that supports the operation of your trading platform is connected through API.
Therefore, the application will be able to implement its best business plans thanks to a robust API system. Several steps to comprehend:
- Use technologies like Swagger, Kong, Postman, etc. that enable quicker processing and better management of APIs.
- For the app’s flawless scalability and to host an API, AWS or Firebase are employed.
- API security is also essential, and key risk mitigation strategies should involve encryption, gateways, and throttling.
- Utilizing the most suitable and effective RDBMS and API database management software.
- Use API programming to create applications for all platforms, whether they are Android, iOS, or web-based.
If there are any flaws, they might also become known, much like a storm surge after a quiet sea. Get all security mechanisms set up and ready to go in order to inspire trust among app users.
Several examples include:
- Create a secure cloud deployment; consider using hybrid cloud computing for added security.
- Include firewalls, powerful encryptions, multi-factor authentication (MFA), and other contemporary security solutions.
- Install real-time threat intelligence software to manage adequate cybersecurity (basically creating an Intrusion Prevention System)
- Implementing a “Compliance-as-code” system for effective internal control and audit.
Take into account these three legal considerations:
- Take part in specialized initiatives like FINRA, SIPC, etc.
- Obtaining licenses from each nation where your stock market application will be accessible.
- Obtain approval from the appropriate regulatory bodies, such as the Securities and Exchange Commission in the USA.
The development of a stock trading platform is a significant undertaking with intricate program logic and design.
Its success and development speed is primarily determined by the correct tech stack. It entails selecting a web application’s backend, frontend, and DevOps tools.
For the more complex features, self-learning bots and smart trades can be built using AI and ML.
Goals and business strategies should come first if you want to create a trading software that stands out on the market. Knowing where to go will enable you to choose the means to get there.
Even while I’ve done my best to give you a general idea of the architecture of the stock trading platform, there is a lot more going on in the background.
I sincerely hope you will value this information and put it to good use.