We have recently published a report titled “The Evolving Landscape of Automated Cryptocurrency Trading: A Market Study of Trading Strategy Solutions” where we take a look at the current state of the cryptocurrency trading bot and platform landscape.
The Trading Strategy market research team have conducted this non-bias research in order to provide its stakeholders and algorithmic trading enthusiasts with a better understanding of what is currently available in the cryptocurrency market today.
We have included a small snippet of the report that covers the introduction and a section from The Trading Strategies Landscape. If you are interested in reading the full 33-page report, join our Discord server and make a request in any of the channels or drop us an email at [email protected]
The automated trading landscape in cryptocurrencies is rapidly evolving and becoming increasingly sophisticated. With the proliferation of decentralised finance (DeFi) and the growing interest in cryptocurrencies, trading bots and trading algorithms have gained immense popularity as a tool for traders to automate their strategies and optimise their trading.
The report analyses the various aspects of the automated trading landscape, including strategy development frameworks, copy-trading platforms, bot marketplaces, social trading platforms, DeFi asset management dApps, and robo-advisors. It also delves into the trading strategies landscape, covering low-frequency strategies such as social trading and templated trading bots. We also cover advanced strategies like market-making bots, arbitrage bots, and scalping/HFT. Each of these platforms offer different functionalities and features, which traders can choose from to identify the one that best fits their trading needs.
The report further explores trading strategy performance results and data quality, including common performance tricks, overall data quality, and presents a data table of some of the different trading platforms and strategies. In doing so, the report includes project deep dives on various platforms such as Tokenbot, Zignaly, Sommelier, Enzyme Finance, 3Commas, deCommas, Bybit, Mudrex, and dHedge.
As the market continues to mature, we can expect to see further innovation and improvements in automated trading, which could lead to even more impressive performance trends. We can already observe that DeFi is making some trading activities fairer, democratising access to different trading opportunities.
The Trading Strategies Landscape
In this chapter, we explore what kind of strategies there are available across different automated trading venues.
Social Trading and Technical Analysis Strategies
Social trading venues usually offer copy trading with interaction of the creator audience. Strategies are discretionary, as the owner of the strategy manually picks the buys and sells,
It can be hard to specify what kind of strategies are popular on social trading platforms, as usually users choose their trader based on a very limited amount of information. Usually only a short bio of the user and an overview of a short timeline (30d) of PnL is given.
Based on the updates that social traders post on the platforms, we can observe that News Trading, trading on observed Market Sentiment and TA (Technical Analysis) are all very dominant on Social Trading platforms. Vague mentions of some kind of AI and ML are sometimes mentioned, but trade logs usually reveal only a few trades per week for most traders.
In the data provided, we table these strategies usually under the “Social” category, if it is not clear what underlying strategy is used.
Simple Bots and Bot Templating Strategies
A large bulk of the publicly available strategies, especially on CEXes and bot platforms are more akin to modifiable “bot templates” than the idea of investable algorithmic crypto hedge funds. A user can take a skeleton of an algorithm based on technical analysis and indicators, and set their own parameters for the trading. Users can sell access to their algorithm, typically for a monthly fee.
Another popular simple automated strategy is what a lot of platforms call DCA (dollar-cost-averaging) bots. It’s basically a way to automate investing in a particular asset with a fixed amount of capital on a fixed interval and fixed duration. Some bot platforms (Coinrule) allow additional intelligence to be added to the DCA bot, such as only buying when a certain indicator (e.g. MACD) hits a certain marker.
Grid Bots are a very popular bot template in this category. Usually they are split into further sub-categories such as Spot Grid, Futures Grid or Infinity Grid. These strategies are usually advertised as easy entry points for users to try out algorithmic trading in crypto. They are usually available for free on most popular exchanges such as Binance and Kucoin, as well as provided by exchange agnostic bot platforms like 3commas or Cryptohopper. In terms of numbers, Binance for example currently boasts a total AUM of $92M on its grid bot offering.
The only parameters needed to set it up are the grid ceiling price, the grid floor price and the number of grid levels. At any given level, buy limit orders are placed at levels below, and sell limit orders are placed at levels above.
As Grid Bots are simple strategies, this means that it is unlikely to be profitable over any kind of meaningful time frame. However, by only tweaking existing parameters might serve as a way to onboard new users interested in automated trading, before they need to learn how to code.
Market Making Strategies
No discoverable public strategy based on market making was found when creating this report, however one of the focuses of the Hummingbot bot development framework is market making. For example, they offer templates for Avellaneda Market Making and market making using Aroon Oscillator to detect trends…
…To read the full report on The Evolving Landscape of Crypto Trading Bots: A Comprehensive Market Study of Bot Platforms and Strategies, join our Discord server and make a request in the general chat here: https://discord.com/invite/en8tW6MDtw or drop us an email at [email protected]
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