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Rising Use of Artificial Intelligence in Trading

2023-11-27 04:20:33

The eventual rise and proliferation of artificial intelligence has been forecasted for decades, dating back to the 1950s when Dartmouth professor John McCarthy first coined the term in his research project. Officially defined as the development of computer systems able to perform tasks that ordinarily require human intelligence, artificial intelligence has been rapidly gaining prominence in 2023. In January of this year, ChatGPT set a record for having the fast-growing user base of any historical program, reaching over 100 million users within 2 months of launch.

As AI exploded into the mainstream consciousness as a key buzzword across a variety of industries, the financial trading sector has been no exception. Already accustomed to the use of computer programs and trading bots to facilitate advantageous algorithmic or high frequency trading, traders have been attempting to adapt artificial intelligence into their trading strategies in order to gain an edge over the market. 

What is AI Crypto Trading?

Since cryptocurrencies are at the forefront of technological innovation, it makes sense that crypto traders are also some of the earliest adopters of AI technology to aid their plays in the market. Using computers to aid in trading activity is no novelty, as currently around 65-70% of stock market trading is estimated to be algorithmic trading. However, the difference is that for the past several decades, algorithmic trading has been more or less considered a technique used by sophisticated or institutional investors who have the resources and tech-savvy required to take advantage of programmatic trading strategies. In this respect, tools like ChatGPT and other AI trading bots have leveled the playing field for everyday retail traders. For example, Phemex recently released its own grid futures trading bots feature that allows any user to automate their futures trading and make profits without need to always be by their computer executing trades. 

Despite the obvious benefits of algorithmic trading, it is imperative to properly utilize this technology for what it was designed to do. Trading algorithms can typically produce accurate forecasts of future market patterns by using historical data. But it is still impossible to predict every change because unexpected things happen (such as the Coronavirus outbreak, which greatly impacted all global markets and many believe actually spurred the 2021 cryptocurrency bull run because of the monetary printing it catalyzed).

Therefore, over-reliance may be dangerous when faced with black swan events, or market disruptions. Doing your own research or seeking the assistance of an experienced financial advisor is highly recommended if you are new to trading or if you are relying entirely on algo-trading. Even though algo-trading automates many tasks, setup can still be challenging and the general trading strategy should still be within your personal conviction.

AI-Powered Trading Techniques

  • Large Language Models: Programs like ChatGPT are LLMs that represent generative text models optimized for specific tasks. They scrap and process a vast amount of data across the internet, and can help traders interpret charts and read indicators based on historical trends. Beyond Phemex’s trading bots, crypto projects such as Omni for Solana uses AI assistance to support passive income strategies. 
  • Machine Learning: In trading, machine learning methods like supervised and unsupervised learning are frequently employed. By analyzing past data, these algorithms are able to spot trends and forecast future changes in the market.
  • Natural Language Processing (NLP): NLP algorithms are able to assess sentiment in the market and make trading decisions based on the collective insights of the community by analyzing financial news, headlines, and social media sentiment.
  • Deep Learning: Complex pattern recognition is an area in which deep learning techniques such as neural networks excel. Large datasets can be analyzed with them, and predictions based on complex correlations between variables can be made.
  • Reinforcement Learning: Through trial and error, reinforcement learning algorithms are able to discover the best trading tactics. To maximize long-term gains, they can modify their system in response to incentives or sanctions they incur from their activities.


Benefits of AI Trading 

Cryptocurrencies are a notoriously volatile investment vehicle, capable of experiencing 20% market swings within the span of one week or even a single day at times. AI crypto trading instills a myriad of advantages, not least of which is the ability to take away human emotion from executing trades. The future of crypto trading will likely move in the same direction of traditional market investing, which means adopting stronger trading software and using computers as an aid to find an edge. 

Less Research Time - Traders can save time, manage their transactions, and effortlessly consult advice from automating research procedures and using data-driven tactics through AI-powered algorithms. According to a recent study, using algorithmic techniques can boost productivity by over 10%, and the possibility of accidental human errors such as misclicking are eliminated. 

Iterated Backtesting - In order to assess the performance of trading strategies, AI systems can backtest them using historical data. This enables traders to increase the effectiveness of their design and success rate. Furthermore, LLMs have the ability to finetune current trading strategies by learning from results in real-time. 

Risk management - AI systems are able to evaluate market risks and modify trading plans as necessary. Additionally, they can consult historical scams to identify irregularities and possible rug pulls to achieve risk reduction.

Improved Decision Making - Artificial intelligence processes have the capacity to instantly evaluate enormous volumes of news, social media, financial data, and other sources. This makes it simpler to spot trade opportunities and make data-driven judgments. It also gives users an advantage over human traders by enabling them to respond more rapidly to changes in the market or news cycle, before others are even aware.

Reduced Emotional Biases - Emotions have the power to impair reason and cause traders to make illogical conclusions. By performing transactions in accordance with predetermined rules and data-driven analysis, AI and algorithmic tools like Phemex trading bots help alleviate human biases.

Enhanced Efficiency - AI-driven trading systems can execute trades with the least amount of latency possible since they can analyze massive volumes of data far faster than humans. Because of its effectiveness, trading activities may scale up and down with lower transaction costs.

The Future of Artificial Intelligence in Financial Markets

As technology continues to advance, greater adoption of AI-powered trading is inevitable. This means that the market competition for AI tools will also increase, specifically around those that support trading functions. With this future vision in mind, Phemex has already begun integrating a myriad of leading algorithmic trading tools, such as Teal Street and Haas Online, through the Phemex Broker program. As machine learning capability evolves, it’s likely that reinforcement learning algorithms will be able to better optimize portfolio construction and asset allocation, adapting to market dynamics for maximum returns. 

Another likely trend for artificial intelligence tools is the rise of explainability. Especially when it comes to trading functions which place money at risk, users are naturally apprehensive to completely hand the reins over to a third-party, even if that third-party is a purported trading AI that’s built to conquer markets by synthesizing innumerable data. If AI algorithms are able to not only recommend an action but also provide a comprehensible explanation for the reasons behind such action, then users would feel more comfortable making those trading decisions. In the same vein, AI programs that develop stronger risk management strategies will likely enjoy a competitive advantage.  

Best AI Crypto Projects to Keep an Eye On

Not only will crypto trading experience increased disruption from AI-empowered strategies, but the crypto industry will also see more projects that incorporate AI technology with blockchain networks. There are already significant projects in pursuit of this endeavor, and prospects are positive as they seek to combine two of the most salient new technologies of the past decade.

Phemex (PT) - As one of the most innovative exchanges in the crypto space, Phemex has shown willingness to disrupt through its Phemex Web3 ecosystem and decentralization effort via the PhemexDAO facilitated by the Phemex Token. Its futures grid trading bots are among the best and most beginner-friendly options as an AI trading bot to automate trading actions with low barriers to entry. Furthermore, it plans to release a social trading platform to elevate the trading experience through collaborative insights.  

The Graph (GRT) - This unique project leverages the blockchain’s decentralized open ledger to gather and synthesize data transparently. It indexes blockchain data comparable to how Web 2.0 search engines like Google indexes the web. Since artificial intelligence relies on access to a swath of relevant data, GRT naturally lends itself to becoming a solid foundation to build AI-dApps in Web 3.0.

SingularityNET (AGIX) - Thanks to its globally accessible AI marketplace, SingularityNET is a blockchain-powered platform that allows anybody to "create, share, and monetize" AI services. Users can explore, test, and purchase a wide range of AI services through the SingularityNET marketplace using the project’s native token AGIX. The marketplace also offers a channel through which AI developers can simply track the effectiveness of their solutions. One way to interpret SingularityNET is that it’s the Web 3.0 version of OpenAI’s recently announced GPT Store

Ocean Protocol (OCEAN) - One of the most contentious aspects of Web 2.0 is data security and privacy. Ocean Protocol develops tools and a marketplace platform for Web 3.0 users to protect, share, and commercialize data while maintaining data privacy. By enabling anyone to tokenize their data and potentially sell it, the project provides a potential solution to the current legal debate surrounding AI’s mass scraping of online data.  

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