Algorithmic Trading

Features > Control > Algorithmic Trading

Overview

Flowdesk’s MMaaS includes algorithmic trading as a feature. Algorithmic trading, also known as quantitative or automated trading, is the process of using advanced instructions to automate the buying and selling of assets. These programs are designed to trade based on predetermined inputs, which may include market behaviors, price changes, volume, time, and trading indicators.

Our algorithmic trading strategies are created through a combination of financial market knowledge and quantitative analysis, and are then coded by our quant programmers into executable algorithms. We then backtest these strategies on historical data to evaluate their performance and make any necessary modifications. The algorithms are not “fixed” but are constantly updated to deliver the best results.

More specifically, our market-making strategies are designed to supply buy and sell orders in order to make a particular market more liquid. These algorithms seek to bridge the gap between buyers and sellers by providing a continuous supply of orders to the market and to reduce the spread between the bid and ask prices of a digital asset.

Flowdesk’s algorithm guarantees a bid-ask spread on a given exchange for a given uptime and depth. For example, we could guarantee that the price difference between the best price to buy and the best price to sell token $XYZ is within a range of 0.1%, and we can guarantee this for 99.50% of the time. The 0.5% left is to cover extremely volatile times. So if the price of $XYZ is $100, we would ensure that there is a buy order at 99.9 or better, and a sell order at 100.1 or better in this example.

Advantages of algorithmic market making

• Faster execution: Our algorithms can execute trades much faster than humans, allowing traders to take advantage of short-term opportunities in the market.

• Increased efficiency: Algorithmic trading can help traders to streamline their operations, reducing the time and effort required to execute trades.

• Improved risk management: Algorithms can be designed to manage risk more effectively, helping traders minimize potential losses.

• Increased accuracy: By relying on predetermined rules and mathematical models, algorithmic trading can reduce the impact of human emotions and biases on trading decisions.

Risk management

• Complexity: Developing and maintaining algorithms can be a complex and time-consuming process, requiring a strong understanding of financial markets and programming. There is also a risk that algorithms may contain errors or bugs that could lead to unexpected losses. Flowdesk, however, constantly tests and monitors the algorithms. This helps to ensure that the algorithms are functioning correctly and that any errors or bugs are identified and addressed in a timely manner, minimizing the potential for losses.

• Black swan events: Algorithmic trading may not be able to adequately respond to unexpected market events, known as black swan events, which could result in significant losses. At Flowdesk, each trading feed is monitored by our team of traders and we have alerting systems that disconnect the algorithm to prevent any losses. We then step in and coordinate the best response alongside clients.

• Regulatory issues: Algorithmic trading is subject to various regulations, which can vary depending on the market and location. This can create additional compliance and reporting requirements for traders. Flowdesk is compliant-by-design, and we are registered as a Digital Asset Service Provider with the French financial markets regulator (Autorité des Marchés Financiers, AMF) for the custody, sales, and trading of digital assets.

Overall, market making algorithms can help to make crypto markets more liquid and efficient, but they can also carry risks such as market manipulation. For this reason, our team of human traders constantly evaluate the potential risks and rewards whilst our engineering team adds constant improvements. In this way, our proprietary algorithm can provide faster execution, reduced transaction costs, and increased efficiency.