What is crypto trading?
Simply explained, cryptocurrency trading is the process of buying and selling cryptocurrencies for making profits.
Just as conventional currencies can be traded on a foreign exchange, cryptocurrencies have their own digital currency exchanges where people can engage in buying and selling various cryptocurrencies. As opposed to the traditional foreign exchange or the stock broking market that works only for stipulated hours, cryptocurrency trading is a 24-hour market.
To start trading, people need to choose a cryptocurrency wallet and a cryptocurrency exchange to trade on. There are about 5000 active cryptocurrencies in existence, but beginners are advised to start trading in prominent coins such as Bitcoin or Ether to minimize losses in the extremely volatile cryptocurrency market.
A multi-exchange crypto trading platform is a one-stop solution that has a visual dashboard of information that connects to multiple major exchanges and allows traders to execute trade efficiently through a unified interface.
For institutional traders who regularly trade across multiple major exchanges such as Binance, keeping track of open positions and market fluctuations can be a challenging task as it requires a high level of diligence to monitor all of their positions. To solve this issue, imagine having a single comprehensive platform where users could track their portfolios and make trades on multiple exchanges, without having to switch tabs? That’s when a multi-exchange crypto trading platform comes into play.
You are looking to dabble with cryptocurrency now that you are familiar with traditional trading? Portfolio diversification is one of the strongest reasons that can lead you to try your hands with crypto. On this blog, read why crypto is a good choice.
To explore further, here are the ways in which crypto trading is different from traditional trading?
Decentralization and Regulation Free: The fundamental difference between cryptocurrency and fiat currency is that crypto is decentralized and not regulated by a central body. This means that cryptocurrency is immune to government control and interference.
Ownership: Yet another aspect that differentiates the two is how cryptocurrencies are much easier to own than traditional stocks. Even though most investors and traders do purchase a derivative of stock, the stock itself cannot be owned in entirety by a single user. This means to properly own stock, you cannot just purchase the asset on an exchange. You must make sure you get the actual paper-stock. With cryptocurrencies, the process is usually much easier. First, there are plenty of ways to trade crypto-assets peer-to-peer (P2P). Decentralized and non-custodial exchanges are becoming more common by the day.
Cryptocurrencies are not exactly like stocks, and cryptocurrency exchanges do not work like traditional securities markets. As a result, many crypto asset investment strategies based on conventional definitions of market share, capitalization, volatility, and trading volume are deeply flawed.
Another important difference between crypto and traditional markets is the size of their order books. A traditional stock is typically transacted on a single exchange, with tens of millions of stocks available to trade daily from many thousands of buyers and sellers. As a result, securities markets like NYSE and NASDAQ have minimal slippage—they can efficiently process large orders and the current market price. While on the other hand, cryptocurrency owners keep most of their assets in offline wallets, with only a small percentage on vulnerable markets.
With a unified interface, a multi-exchange crypto platform helps manage all crypto accounts.
Allows traders to make the best use of price differences of a single crypto across multiple exchanges.
Helps automate several trading functions to execute orders quickly and efficiently.
Allows traders to place a pre-set order at a specific percentage away from the market price when the market swings. It helps traders to limit the loss and to protect gains when a trade does not move in the direction that traders consider unfavorable.
Helps traders carry out trade orders through graphic visualizations.
Crypto trading strategies and algorithmic trading
Crypto trading strategies are detailed trading strategies that help traders draw out extensive plans to carry out trade orders in order to create profits. It helps mitigate as well as manage risks and thereby precludes a lot of unnecessary last minute decisions.
Algorithmic trading strategies in crypto are typically strategies that originated from traditional markets. Automated bots are useful in regulating crypto trade and identifying what works best for each trader profile.
With traditional markets, large trading firms, such as hedge funds and investment banks, often build their own software and have trading centers with dedicated data and a support desk.
Algorithmic trading can be applied in stock markets to among many things automated buy/sell orders, generate trading signals or indicators, market movement forecast and risk management.
Retail traders can use algorithmic trading to automate the retail process which in turn increases the number of trades for more profits. Also with predetermined entry-exit rules, a retailer can use algorithmic trading to avoid losses that arise from poor decisions.
Algorithms are proven faster, smarter and more efficient than humans in finance newsfeed analysis, earning statement analysis and financial performance evaluation.
Arbitrage bots in crypto these days are less successful than the initial days of crypto as the price difference between exchanges is not as wide as it used to be. And yet, the price difference in inefficient crypto markets can be used by algorithms in order to buy a coin at a lower value and simultaneously sell at the higher one.
In order to make quick manifold profits, it’s important to close deals in a quick manner, since price differences may exist for no longer than a few seconds. And this is where an arbitrage crypto bot can come in handy.
There are different kinds of arbitraging strategies that include the following: statistical arbitrage, triangular arbitrage, cross-market arbitrage, cross-asset arbitrage.
If you’re familiar with the concept of spread, you probably know how it is composed of the bid and ask prices. Algo trading based on this strategy will help you profit from the difference between the bid and ask prices. In traditional trading, market making strategies normally get implemented by large institutions, so it is hardly possible for you to automate this strategy on top of those markets.
Yet, in crypto it is still possible. Not only is the bot’s objective to sell to investors at a higher price than they have bought the asset, but also do it as frequently as possible.The market maker bot scans for markets with wide spreads day in day out and places orders with a different price than the existing one – thus market making.
Scalping is a profitable and short-term crypto trading strategy with short term profits through a number of trades on a given day. Typically, with scalping, the profit from each trade is relatively small yet sustainable as it continues to yield over an extended period.
Scalping requires high volatility of the chosen currency pair. Significant movements in price facilitate generating profits, though scalpers more often utilize short-term bursts of volatility. When comparing scalp trading with day trading or swing trading, scalp trading involves relatively low risks and provides yields on the spot. But the results highly dependant on a trader’s perseverance, self-discipline, and large capital amounts to gain substantial success.
What is data aggregation?
Did you know?
There are 2.5 quintillion bytes of data created each day in the world. What’s your company’s share in this?
And did you know how much this data means for your company in the digital world? Well, it comes as no surprise that data science ranks #1 in LinkedIn top jobs with a 4.7 job score. That IBM, Amazon, and Microsoft have the largest data science workforce is no surprise either.The secret: They’ve mastered the core concept of data; Data aggregation!
Could data aggregation also be your pathway to greater values? It definitely must be.
Data aggregation refers to a process that involves gathering information and expressing it in summary form for statistical analysis or other purposes. In many cases, data aggregation is exclusively done to get more information about particular data sets based on explicit variables such as profession, age, or sex.
Raw data can also be collected and gathered over a specific time period and aggregated to provide summaries such as maximum, minimum, average, sum, and count. This information can then be applied for many benefits including website personalization for targeted content and advertising to individuals belonging to these groups.
A good use case of data aggregation can be how it drives the finance industry. Financial account aggregation compiles information from different accounts including credit card accounts, bank accounts, or investment accounts to present it in a single, easy to access place.
A data aggregation methodology takes the volume-weighted average price (VWAP) of all volume weighted average prices calculated for a given cryptocurrency pair (a VWAP of VWAPs). The output data includes exactly which exchanges we pulled data from to form the aggregation, along with the individual VWAP data points used to calculate the aggregation.
Data aggregator platforms are used to fetch and compile data from multiple sources and that makes deriving insights and patterns-tracking easier and more accurate without losing source data lineage. These platforms are particularly helpful in big data analytics.Data aggregation is particularly useful to make all collected data sensible and of utmost importance to a business that wants to utilize this information for strategic decision making.
The best platforms are ones that give a wide breadth and in-depth data collected from myriad sources, clean the data, and analyze it before sharing the data as a single source. Clarity, simplicity, and speed are also characteristics of a good data aggregator platform.
Real-time data aggregation taps into streams of multiple sources such as GPS data and continuously compiles that data to provide real-time customer information. This, in turn, allows the management, tracking, and analytics of live flowing data.Aggregating data in real-time requires adequate awareness and insight into choosing an appropriate timing for weighing business readiness. To make the most out of data, real-time aggregation of data is important; and even more so when:
You want to give deeper insights into the business using data visualization: Visualization of business information is a vital component in managing the key performance indicators (KPIs). When viewed in real-time, KPI data gives a single source of truth and provides updated data that offers a bird’s eye view of business performance at any given time.
You want to monitor customer behaviors to derive useful insights: You need to aggregate data in real-time when there is a need to get further insights into customer behavior. Real-time data allows a business to gain visibility into products bought by customers, what they are not buying, what they prefer and what they dislike that helps in timely responses and actions.
You are seeking a competitive advantage: With real-time data, a company can identify trends, and craft forecasts of the industry. Real-time data is a great asset for innovation, competitiveness, and a great brand reputation.
Confusion and overlapping of data is a common challenge for every organization sharing information across departments and through multiple communication channels. A real-time information system is vital in this case to increase the productivity and efficiency of the business.
The primary purpose of real-time data aggregation is the timely utilization of crucial and insightful data by employees. This is further enhanced to keep the operations smooth by creating a single reference point such as a dashboard to allow instant access of information by different people at different individual levels.
Real-time data aggregation helps evade risks by keeping the business away from “inevitable uncertainties” as they are called. This, in turn, reduces costs and saves on time that can be used in product improvement and customer services.
Increase in data and data sources comes with increased data management challenges. With these challenges, it is fair to say that every company that appreciates the potential of data in increasing sales and revenue needs to aggregate data.
But what about real-time aggregation of data? How do you identify the need to aggregate data in real-time? The following lines outline common indicators that your business needs real-time data aggregation.
You need instant information to evaluate an initiative: : Do you need to understand the impact and performance of a project, product, or an initiative? Real-time aggregation of data gives a visual representation of data that helps evaluate progress and also understand whether there is a marked improvement or not.
Your stakeholders need clear and up-to-date reports: You may have found yourself in a certain situation where everything you try to explain to stakeholders doesn’t make sense to any of them. This is an indicator you need to consider real-time data aggregation that helps you explain the situation as-is using simple and self-explanatory dashboards
You are looking to expand your business and modify current services: Real-time data aggregation will help you reach out to more customers and improve customer satisfaction by instantly replying to their queries
Typically, a multi-exchange crypto trading platform works as a unified platform wherein traders need to generate API keys from a given exchange. Once this is done, they are required to upload the generated API key to the platform/unified interface against the exchange.
Managing unified data and consolidating disparate data sources to create a single data narrative within a data warehouse is one of the major factors of data aggregation. Siloed data obfuscates the bigger data picture and prevents data from being effective and actionable.Unified data management encourages consolidation of data and presentation of data on a single platform by creating a centralized data repository through which all company data is parsed, cleaned and analyzed to produce actionable insights. With one platform handling data migration and readiness, crypto traders can use a single portal to get a bird’s eye view of all their holdings.
This allows the user to view the assets balance and start trading with a clear idea of what to look for. How does data aggregation come into play here? Assets balance and order status are usually synced from exchange through real-time data aggregation
Smart trading tools and features of a comprehensive crypto platform
Algorithmic trading or algo trading refers to a trading system which uses advanced mathematical tools to facilitate financial transactions decision making. Algorithmic trading aims at helping investors execute financial strategies as fast as possible for higher profits.Smart trading tools involve expert advisor tools that help investors improve trading execution and management while optimizing trading strategies and managing risks.
Developing a trading algorithm involves a process that starts from goals to testing and actual trading through the following phases:
Goals include things like the market you want to trade in, and your desired returns and drawdowns. Drawing solid goals and objectives will keep you alert on your path to satisfaction while helping avoid risks
An idea forms the starting point of coding an algorithm. The best ideas are ones with a clear explanation behind them. It is a good move to test every idea you get before settling on a specific one.
With clear goals, objectives and roadmap, it is now the time to put hands on the real thing. The trading algorithm. This step involves following best practices and doing random tests to ensure the final system is based on the drawn strategy and is built for effectiveness.
Testing is done to ensure the deliverable is valid and verifiable. Several tests are carried out before the system is deployed.
After passing the tests, the strategy is now ready. At this step, you turn the strategy on and start trading with real money. The strategy can be automated on your machine or a virtual private server.
Smart trading tools allow both automated and simulation trading within its program. With simulation trading, investors can practice in the market without real money. Automation provides a fast and consistent way of trading. This combination helps traders make quicker and streamlined decisions.
Smart tools are able to filter quickly through tons of data and give a shortlist of best match companies that match your criteria.
Smart trading tools simplify trading by automating the procedures that are otherwise manually done by the trader.
Smart trading tools allow real-time access of information from anywhere that positions the user at a competitive advantage.
What are cloud-based trading systems and why is microservices architecture preferred for building robust trading platforms?
Application containerization is the process of bundling an app and its related configuration files, dependencies and libraries together for efficient and safe running across multiple computing environments. Multiple isolated components and services have access to the same OS kernel and run on a single host.
Containerized applications are mainly used to simplify developing process, testing and production flows for cloud-based services. This is no different with developing automated trading systems. In this case, containerized applications help in:
Instant operating system start-up
Replication of containers help easy deployment of automated trading systems
Containerized applications help achieve enhanced performance with higher security.
Scalability is another important benefit of containerization as it makes it possible for more app instances to fit in a machine unlike if each was on their own.
One of the popular concepts of cloud computing, containerization can help modernize legacy systems to create new scalable, cloud-native apps.So what are containers?
Containers are typically a form of virtualization of operating systems. That means, a single container can be used to run anything from a simple microservice to a huge complex application. A container would contain all the necessary elements to execute and run the application, such as, binary code, libraries, executables, and so on, all along with much lesser overhead. One of the significant advantages that a container has is that it does not contain operating system images. This renders them lightweight and makes them a lot more portable. A single container might be used to run anything from a small microservice or software process to a larger application. Inside a container are all the necessary executables, binary code, libraries, and configuration files. Therefore, in larger application deployments, multiple containers may be deployed as one or more container clusters. Such clusters might be managed by a container orchestrator such as Kubernetes.
As they do not contain operating system images, containers require less system resources than legacy systems, therefore making them create less overhead.
Applications running in containers can be deployed easily to multiple different operating systems and hardware platforms.
Irrespective of where they are deployed, applications that are in containers will offer a consistent experience.
Containers allow applications to be more rapidly deployed, patched, or scaled.
A monolithic architecture is one in which the parts that make the application such as code, business logic and database are built in a single, unified unit. In monolithic architecture, client-side and server-side application logics are defined in a single massive codebase. This means that any change to the application needs to be built and deployed for the entire stack all at the same time.
The microservice architecture on the other hand involves developing an application as a collection of small services with each service running independently. These services communicate with each other using HTTP resource API. The services are written purely in business terms and deployed independently. The business APIs are standardized in a way that consumers are not affected by changes in application services.
Most of the benefits of microservice architecture lie in the business-oriented values to the company including:
Decoupling of services in microservice architecture makes it easier to reconfigure and recompose the service in order to serve different apps. This also enables fast delivery of parts for larger integrated systems.
Microservices architecture increases the run-time of the system for greater performance. Resiliency is achieved through dispersing system functionalities across various services.
Revenue increases with reduced downtime and an increase in iterations achieved through microservices architecture model.
Legacy migration is the process of importing traditional systems, and data in them, into a new platform, media or format. The term is mostly used to describe the process of moving an organization’s legacy systems and data to the clouds from the traditional data centers. This process is orchestrated by various drawbacks of legacy systems including:
Non flexibility - Building new features to meet new business requirements requires massive efforts in legacy systems. Most times this process will mean re-engineering the whole system.
Lack of IT staff- Legacy systems are built on bygone technologies which young and current IT professionals may not want to put their hands on it.
Expensive - Old hardware used in legacy systems use excessive power and resource time making it expensive for the company.
A cloud-hosted system is one whose hardware and software resources exist in the internet and are managed by high-end server computers to allow access of data from any corner of the world as long as the user is connected to the internet. Some of the features of cloud-hosted systems include:
Resource pooling - Cloud-hosted systems have access to multiple computing resources pulled together through a multi-tenant model. These resources can be assigned and deassigned depending on client’s demand.
On-demand self service - cloud providers offer clients the ability to continuously monitor the computing capabilities including server uptime, network traffic and storage.
Network access- Users of the system can access data from anywhere, through any devices as long as they have an internet connection.
While it is a great move to migrate from legacy systems to modern, the process is not as easy. You will face challenges along the way that may seem to halt your plans. Knowing these challenges beforehand may prepare you for the process. Some of these challenges include:
Change management - The task of managing the change from a traditional system to a modern one requires both technical and managerial expertise to ensure minimal interruption to programs and effective training of users.
Co-existence of two systems - Due to the phased approach of data migration, time will come when the two systems will be running together before full transition. In this case challenges in handling data duplication, overlapping become inevitable.
Expensive - Modernization process involves large investments of money and time. For complex systems, this process may go for years hence requires a lot of capital.
Now that you have understood the concepts surrounding a crypto exchange platform and its ecosystem, at Ionixx we offer a unique multi-exchange crypto trading solution that helps you make sense of trading data and addresses problems such as price inefficiencies and market disparity.
Through our solution, we have incorporated features such as Order Book Aggregators that segregates exchanges functioning across multiple geographies in order to consolidate and limit price differences between countries.
By providing a unified platform, we allow traders to be able to trade at the global best price by solving issues arising out of liquidity and volume differences. Automated algorithms, automatic price discovery, smart order routing for iceberg orders (TWAP/VWAP) affords traders greater freedom to employ desired trading strategies.
Are you looking for a fair and level-playing field to trade crypto? Then a multi-exchange crypto trading solution is the best bet. With curated trading strategies and pre-set algorithms, our solution helps you make the first bold step to crypto with more and understand our multi-exchange crypto trading platform solution better, read here.
Let's have a chat and figure how to build your product together.