Is it genuinely possible for AI to accurately forecast cryptocurrency prices?
Exploring the World of Cryptocurrency AI Predictions: Unveiling the Best Crypto Prediction Apps for Accurate Price Forecasts
The idea of computer programs predicting asset prices may seem like a concept from a distant future, but the use of artificial intelligence (AI) in market prediction has been a topic of research for quite some time. In fact, a 2015 paper published in the International Journal of Computer Applications discusses an “intelligent stock market forecasting” system that utilizes neural networks and fuzzy inference systems to uncover patterns in nonlinear and chaotic systems.
The researchers of the aforementioned paper attempted to predict future stock values for January 2012 using historical data from BEXIMCO Ltd. Their simulation revealed an average error of 1.84 percent. The researchers concluded that by creating a strong knowledge base and training the system with a larger input dataset, more error-free prediction prices can be generated.
Now, let’s shift our focus to the use of AI in predicting cryptocurrency prices. Researchers often turn to artificial neural networks (ANN) to identify patterns in large volumes of data that would be time-consuming for humans to interpret. Is there an AI solution for predicting cryptocurrency prices? A recent paper published in 2021 by the Multidisciplinary Digital Publishing Institute introduces an AI model for precisely this purpose.
According to the authors of the paper, the AI model demonstrates excellent predictions based on the mean absolute percentage error (MAPE). The MAPE is a statistical measure used to assess the accuracy of a forecasting model. For Bitcoin (BTC), Ethereum (ETH), and Litecoin (LTC), the algorithm achieved MAPE percentages of 0.2454%, 0.8267%, and 0.2116% respectively.
It’s worth noting that the paper explains the use of 80% of historical data from January 2018 to October 2020 for training, and the remaining 20% from October 2020 to June 2020 for testing. However, the model’s long-term performance in the face of ever-changing market conditions remains uncertain.
While researchers continue to work diligently to harness the power of AI for precise crypto price predictions, the practical applications are currently quite limited. Nevertheless, there are AI-powered market prediction and analysis tools available for those interested in AI tools for cryptocurrency trading.
One such tool is Santiment, which employs AI to generate a summary of the current social media discourse surrounding assets. While it doesn’t directly predict market movement, it allows human traders to quickly analyze large amounts of data to make their own decisions. Other offerings, like ChatGPT Trend Master and ChatGPT Crypto Tactics by OctoBot Cloud, use OpenAI’s ChatGPT to make predictions.
KepingAI Long Short TF Free, available on 3commas, is another AI bot that provides limited insight into its operational mechanisms but emphasizes its use of artificial intelligence. PionexGPT uses AI to create traditional trading bots by writing custom TradingView’s pine scripts. CryptoHopper, on the other hand, uses AI to analyze various strategies and autonomously decide which one to use.
However, it’s important to approach AI crypto trading bots with caution. The Commodity Futures Trading Commission (CFTC) has warned about the prevalence of AI crypto trading bots as a cover for scams. Even some AI experts share a limited optimism about the potential of this AI application. Laurence Moroney, AI Lead at Google, believes that AI will enhance the efficiency of human financial advisors rather than replace them.
To identify the best AI trading models, certain metrics are employed. The Meta Model Contribution (MMC) and benchmark model contribution (BMC) gauge a predictive model’s impact on the overall performance of a combined meta model and its contribution relative to specific benchmark models, respectively. Hedge funds have been incorporating AI into their operations, using it to analyze data, predict market movements, and forecast corrections in supply and demand imbalances.
While AI cannot predict the future, it can assist advanced traders in making more profitable trades by managing risks and maximizing gains. The availability of AI tools for the average trader may be limited, but exploring online courses in artificial intelligence programming or creating a custom solution can be fruitful endeavors.
In conclusion, the realm of cryptocurrency AI predictions is a fascinating one. While there are promising AI models and tools available, it’s essential to approach them with caution and remain aware of the potential risks. AI can enhance human decision-making processes, but it is not a crystal ball for predicting the future of cryptocurrency prices.
