For this post, we’ll outline the basics of algorithmic trading for those in the crypto ecosystem and how it differs from other execution types. For a crypto-investor looking to enter or exit a bitcoin position, the default is for them to log onto an exchange and manually execute their order. This type of order execution triggers many unnecessary risks, including human error, exchange credit risk, and poor liquidity. On the other hand, ‘algorithmic trading’ creates a pattern of rules for trading to automatically follow.
What is Algorithmic Trading?
Also called automated trading or programmatic trading, algorithmic trading uses a computer program that follows coded instructions to make a trade. In most cases, humans write the algorithms and the program automatically executes the steps, depending on market conditions and other external factors.
Since this process is automated, trades often occur at speeds and a frequency outside that of human ability. The result is faster and more efficient trading that offers a new pathway to potential profit.
The instructions and pre-determined factors for algorithms vary, but often includes:
- Timing – Enabling trades to be placed at a set date or time in the future.
- Quantity – Placing limits on how much can be traded in a day or a given window.
- Price points – Setting price parameters that can trigger the buying or selling of an asset.
- Mathematical model – Instructing the algorithm to follow a certain mathematical model, which typically owns some unique risk-reward characteristics. Private trading firms have their own preferred models that they use for their investors.
- Optimal execution is a well defined mathematical problem, its solution depends on specific assumptions on market dynamics and market impact.
Who uses algorithmic trading?
In traditional finance the majority of users are big brokerage firms and institutional investors, who are typically looking to cut down on trading costs, especially for sizable trades. Execution algorithms will target their goal of average execution price, (i.e. maximise revenue will be lowest possible buy price, highest possible sell price) by slicing a big order in smaller pieces.
In crypto markets individuals, funds, projects and exchanges all use programmatic trading – as well as new entrants looking to make their first purchase of digital assets.
Algorithmic trading increases liquidity, as noted in a 2011 study from the Berkeley Journal of Finance. The study showed that increased algorithmic trading “by reducing the frictions and costs of trading, technology has the potential to enable more efficient risk sharing, facilitate hedging, improve liquidity, and make prices more efficient.” Aside from lowering the cost of trading, they also found that it increases the accuracy of trade quoted.
How widespread is algorithmic trading?
Around 80% of the daily moves in U.S. stocks are primarily driven by algorithms, according to a 2018 report cited by CNBC.
The practice continues to expand rapidly, with estimates pointing to a compounded annual growth rate of 11.23% from 2020 to 2025. The increasing demand for fast and reliable order execution and proven impact on transaction costs is driving this growth. More and more, large brokerages are relying on algorithmic trading for bulk orders.
Government regulations in different countries are creating favorable conditions for automated trading. Advancement in technology and artificial intelligence is also expected to improve the algo trading market.
What are the advantages of algorithmic trading?
If you want to implement algorithmic trading in crypto, here are some of its advantages:
- Unlike human traders who are influenced by emotions and fatigue, algorithms can process vast volumes of data in a matter of seconds. They can scan multitudes of markets for trading opportunities
- The algorithm can execute orders without mistakes and this also removes the chances for human error
- Computers can execute orders consistently, resulting in faster execution of orders and quicker return of profits
What are the disadvantages of algorithmic trading?
As with any form of emerging technology or trading strategy, algorithmic trading can have its logistical risks to consider:
- When many orders are executed at the same time with no human oversight, the resulting wave of volumes can cause market disruptions. Some observers attribute extreme market events in 2010 to algorithmic trading.
- You have to have advanced programming skills and sufficient trading experience to be able to participate in profitable algorithmic trading
- There is a large dependence on technology. If the computer crashes or malfunctions for any reason, you may miss important orders.
What are some common algorithmic trading strategies?
Here are some of the tried-and-tested strategies that traders implement:
- Trend Following – Algorithms follow trends in terms of price movements or channel breakouts. Traders usually follow 50 days or 200 days worth of moving averages.
- Time-Weighted Average Price – Under basic assumptions the optimal strategy is the TWAP (time weighted average price). The TWAP will execute the same amount of shares at fixed time intervals. How much is executed at every step is defined by inventory and schedule.
- Volume-weighted Average Price – If instead of working in time-clock a volume-clock (where market time flow is defined by how much volume trades throughout the day) can be considered, the optimal solution is the VWAP (volume weighted average price). The VWAP will sell the same amount of shares at fixed volume intervals. How much is executed at every step is defined by inventory and schedule.
- Trading Range – Also called ‘mean reversion’, involves betting that prices will revert back towards the mean or average.
- Arbitrage Opportunities – This is simply buying an asset at a lower price in one market and selling it a higher price in another. Algorithms can capitalize on these small inefficiencies on a large scale.
How does algorithmic trading differ from OTC trading?
Algorithmic trading can be used for both OTC trading (over-the-counter trading) and trading on exchanges. Usually for an OTC market, the process is manual between two counterparties.
OTC trading has long been done by human traders. So is there value in choosing a human over a systematic approach, or vice versa? Let’s explore the differences:
|Algorithmic Trading||Human Trader|
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How do I start my algorithmic trading?
A common question is, “Can I do algorithmic trading without knowing how to code?”. There is a lot of trading software marketed to traders in crypto markets, however this route is not recommended. You should enquire with a trusted trading provider, this type of technology should be used by experienced traders only.
Algorithmic trading is an excellent fit for a large holder of a digital asset who wants to minimize the impact on the price of the asset when liquidating part of their position, additionally it allows investors who are considering a longterm position to get the best price for their investment. For example, it is possible to build in parameters to automatically sell less when there is not a robust bid on a particular day. It is also possible to only sell during a specific window each day or around market-specific events, or accumulate at a specific price range. Any time there is a predetermined set of instructions, it can be programmed ahead of time, providing a variety of efficiency gains.
Ideally, an experienced trader can advise you on the parameters you would set to maximize the use of the technology.
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