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The Thinking Crypto Bot: AI Strategies, Platforms & Your Edge
By nature, trading is a complex activity involving many concepts to help traders analyze the markets and find profit-making opportunities. These concepts address a wide range of possible scenarios as the price of an asset fluctuates over time.
Each scenario presents a unique challenge at a specific juncture, where manual traders should be able to adapt to changing market conditions while evolving with them.
Such an adaptation process requires constant refining of both the trader's skills and the trading strategy capabilities. Algorithms and automation emerged as an optimized solution for this ongoing procedure.
In that context, artificial intelligence (AI) represents a further step toward improving the efficiency of trading strategies operated by algorithms and automated systems.
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What is AI Trading?
But what does AI trading mean exactly? This approach provides algorithms with self-learning capabilities to process new data from the latest changes in market conditions autonomously. The ultimate goal here is to achieve efficient prediction models.
While algo trading focuses on automated execution based on pre-established rules, AI trading agents go beyond aiming to make autonomous decisions by analyzing vast amounts of data at a fraction of a second, if possible.
At its core, AI trading leverages the best of the principal concepts in the world of algorithmic trading:
- Automated execution at high speed.
- Data analysis and in-depth research through quantitative models.
- High-frequency trading to distribute large volumes of orders across different markets at once.
When implementing this approach, market participants benefit from computerized learning of trading agents who can analyze current and historical market data to decide when to buy or sell based on predictive modeling.
How Crypto AI Trading Platforms Work: Signals Execution, Portfolio Balance and Statistical Arbitrage
An AI crypto trading platform can be any software developed to execute automated trading decisions and market analysis. In such a case, we should distinguish between commercial software, such as Altrady, Bitsgap, and Wundertrading, and proprietary development.
While commercial platforms provide already-made solutions through automated trading services, proprietary developments may accomplish more complex and custom traders' goals. Both methods strive to solve crucial issues regarding trading efficiency and optimization.
AI trading platforms rely on machine learning, deep learning, and natural language processing models that allow algorithms to recognize patterns and perform sentiment analysis on top of self-learning procedures, enhancing artificial intelligence features over time.
Crypto trading AI platforms focus on developing systems and training bots to perform autonomous decisions in the digital assets market, aiming to gain an edge amid intrinsic volatility. AI trading bot systems can work for several purposes, for example:
- Automated trading execution.
- Smart portfolio balancing.
- Arbitrage strategies.
Let's use the commercial software alternatives mentioned above to depict some examples.
Altrady For Automated Trading Execution
This multi-exchange is a perfect benchmark for putting together algorithmic trading and quantitative research with the ease of a bot feature.
Among the different automated options offered, the Signal Bot stands out as a reliable solution to automate executions based on alerts. Traders can implement a Signal Bot powered by Altrady's partner provider, Fox Signals, which backs up its signals based on AI.
The Signal Bot scans the market 24/7 and employs algorithms to open positions when a signal matches the entry and exit settings.
Learn more about the Signal Bot here.
Bitsgap For Balanced Porfolios
Bitsgap is a crypto trading platform where traders can utilize an AI assistant to deploy multiple trading bots based on market trends analysis.
By executing and maintaining several positions simultaneously, traders can reach optimal portfolio balance as the AI assistant monitors the market continuously. This method launches and closes the bots as they meet the profit criteria.
Regarding portfolio building, this research from QuantConnect discusses implementing a 40-60 portfolio using Bitcoin as an example in the era of AI.
Wundertrading For AI Arbitrage
The Wundertrading approach consists of a bot powered by mathematical models and a machine learning classifier expected to identify statistical arbitrage (Stat Arb) opportunities.
By continuously assessing historical market data correlations of similar price movements between two trading pairs, this AI bot seeks spread deviations on trending prices when they return to their average values.
The bot generates standardized values based on the relationship between the mean-reversion concept and the regular distribution of the trading pairs spread.
As soon as the spread surpasses the standard values established by the bot, it triggers a signal that opens simultaneous long and short positions, buying a pair while selling the other, generally employing high-frequency trading.
The Role of Backtesting
The high effectiveness of AI trading systems requires training and testing their performance against historical data and statistics that could enrich the predictive process. Backtesting is a crucial step in this sense.
This process allows developers to collect insightful information to optimize the bots over time. Similarly, traders can assess which strategies adapt more proficiently to the course of action of specific assets.
Moreover, the backtesting results may contribute to further developments due to the self-learning capabilities of artificial intelligence.
Trading Crypto with AI Platforms: Advantages and Disadvantages
Adventages
- Enhanced trading efficiency: The ability to process vast amounts of real-time data increases the AI response speed amidst current events or fresh news.
- Accurate predictions: AI can recognize complex patterns humans might miss, making the algorithms more effective in anticipating potential trends and subtle correlations into market shifts.
- Emotionless execution: Since algorithms operate according to pre-defined rules, their execution is purely rational, eliminating biases, fear, and greed.
Disadventages
- Data quality and algorithmic errors: Training algorithms on biased-inaccurate data can lead to flawed decision-making and low-quality performance.
- Adaptability and overfitting: Reliance on historical data could lead models to struggle with adaptability during unexpected market events, where new patterns eventually emerge.
- Technical and cybersecurity risks: AI models may demand constant monitoring as bugs and connectivity issues raise security and deployment concerns.
Conclusion
The era of AI has conquered several fields, and the trading one is not out of the game. Crypto AI platforms offer traders more efficient methods to manage trading capital and engage in complex strategies.
The offer is broad, ranging from arbitrage to portfolio balancing bots. In Altrady-multiexchange, users can find AI features via the Signal Bot. If you are interested, starting a free trial account here today can dive you into the AI crypto trading world.
