Algorithm trading, also called ‘algo trading’ or black-box trading, is a term that the financial media have popularized, but it has existed for many years.
Simply put, algorithmic trading is the use of computers programmed to follow a defined set of instructions (an algorithm) for placing a trade on an instrument for some predefined criterion.
The motivation behind algorithmic trading is to achieve greater efficiency in executing orders and obtaining better prices when filling large volume orders.
A computer cannot think independently – It must be told what to do at every step, so the program that decides the logic needs to be versatile enough to account for any situation.
When multiple programs are executed on one computer, this is called High-Frequency Trading (HFT).
The first step in any algorithmic trading system is developing a plan outlining the trade criteria. This plan should answer the questions:
- What is the goal of the trade?
- Are there rules for entering and exiting the market?
- How will profits be measured?
There are many different types of algorithms, but some common ones include trend following, breakout/momentum strategies, and pairs trading.
Once a plan has been developed, the next step is to find a broker that offers an API (Application Programming Interface) to allow your computer to communicate with their systems. The API will provide you with access to real-time prices and order information.
Once you have it all set up, your computer will monitor the markets continuously and place trades based on the predefined rules.
The most common ways algorithmic trading is used are for high-frequency trading (HFT) or statistical arbitrage, which are defined below:
High-frequency trading involves submitting many orders to buy or sell close to real-time. These orders are designed to capture small changes in market conditions over short periods, giving them an edge over retail traders who do not have access to these algorithms.
Trading firms utilizing HFT algorithms usually post their buy/sell prices just slightly above/below the National Best Bid/Offer (NBBO). Since there are no commissions for stock exchange orders that fall within the NBBO, they can profit from the bid-offer spread.
Statistical arbitrage is algorithmic trading that takes advantage of minor price discrepancies between two or more assets. The strategy involves buying and then selling it immediately to profit from the price difference.
For example, if a stock is trading at $10 on one exchange but only $9.90 on another, a trader could buy the store on the first exchange and sell it immediately on the second, making a 10 cent profit.
Stat Arb traders use sophisticated mathematical models to identify these price discrepancies and then execute trades quickly to take advantage of them.
Let’s look at some of the options traders in the Netherlands have available.
Several brokers in the Netherlands offer algorithmic trading capabilities. Some of the most popular ones include:
- IQ Option
Each of these brokers has its API, which can place orders and access real-time prices. Using their APIs requires programming knowledge and writing code in Java, C++, or Python.
If you don’t want to go through the trouble of programming your algorithm, several algorithmic trading platforms are available that allow you to do it all within the forum.
These platforms usually have a drag-and-drop interface, making it easy to create and test your algos. Some of the most popular ones include:
All trading platforms have unique strengths and weaknesses, so be sure to research before deciding on one.
Algorithmic trading is a growing industry that offers traders a variety of options for executing their trades.
Whether you are looking for high-frequency trading capabilities or want to take advantage of price discrepancies with statistical arbitrage, there is an algo trading platform out there for you.
If you don’t want to create your algorithmic trading strategy, several platforms allow you to do so right within the forum.
To read more on topics like this, check out the Business & Finance category