WeQuant Quantitative Artificial Intelligence Platform
For years, WeQuant has been working, innovating, and trading in the cryptocurrency industry. WeQuant’s mission is to help define the industry’s future. WeQuant empowers brilliant people in mathematics, physics, and computer science to seek, push, and apply cutting-edge research to global financial markets.
WeQuant is pushing the boundaries of crypto infrastructure. For years, WeQuant has provided liquidity security to global financial markets, and we are now focusing on algorithmic trading and advanced technology fields. WeQuant is an ambitious startup on a mission to become one of the world’s leading trading companies. We established a firm complementary haircut for the placement of artificial intelligence in the quantitative market. We anticipate change, constantly improve and innovate, and dare to dream what might be. Making things happen today in order to improve tomorrow.
We advocate for robust, well-regulated markets that encourage competitive and transparent markets. We believe in equitable market access and a level playing field, and we actively support measures that promote both.
What role does artificial intelligence play in the cryptocurrency market?
Because blockchain offers secure data storage and sharing, AI may be used to analyze and derive insights from historical and real-time blockchain data. Blockchain transactions can also show behavioral patterns that can assist make sense of the crypto market’s drivers.
Ways AI Can be Used for Crypto Investing
Understanding the extremely unpredictable crypto market and carrying out bitcoin investments require a significant amount of effort and talent. With the rise of more technologically advanced technologies, asset managers are increasingly turning to AI, Machine Learning (ML), and Natural Language Processing (NLP) to make sense of crypto assets in fund portfolios.
AI in cryptocurrency investing can provide:
- More precise predictions
- Sentiment analysis on cryptocurrency exchanges
- Automated cryptocurrency trading
- Improved investment monetization
More Accurate Crypto Market Predictions with AI
The volatility of the market is one of the most significant issues in bitcoin trading, and traditional research, extraction, and analysis processes are inefficient when it comes to discovering investments and buy/sell signals. Investors may identify and forecast major events in the crypto market and make more informed investment decisions by gathering, cleaning, processing, and analyzing enormous volumes of unstructured data.
Furthermore, combining AI and blockchain creates an even more potent combo. Blockchain keeps a digital record of everything of value, not just transactions. Because blockchain offers secure data storage and sharing, AI may be used to analyze and derive insights from historical and real-time blockchain data. Blockchain transactions can also disclose behavioral patterns, which can aid in making sense.
AI Crypto Market Sentiment Analysis
Sentiment analysis is the application of artificial intelligence (AI) and natural language processing (NLP) to assess people’s sentiments or thoughts on a specific topic. Within cryptocurrency investing, an overall positive emotion toward a digital currency might anticipate an increase in price, whilst an overall negative sentiment can predict a decline in price.
To evaluate the cryptocurrency market’s attitude, news, blogs, articles, forums, social posts, stock message boards, and even comments relating to them must be collected, processed, and analyzed to determine whether it is negative, neutral, or positive. Market manipulation can be discovered by anomalous behaviour found in sentiment indicators. The following forms of sentiment analysis are commonly employed to analyze the bitcoin market:
- Polarity analysis examines statements and assigns labels based on how they are positive,negative, or neutral. After considering the overall score, investors and economists can track patterns and changes in the score.
- Tone/emotion: NLP can be used to analyze the text’s emotion or tone. Analyzing various typesof emotions that occur yields insights.
- Aspect-based sentiment classification classifying data by the specific firm or service and
detects the sentiment associated with each one . Analyzing client feedback by linking sentiments with a product or service is one example.
Strategies for Automated Crypto Trading
Because AI can mimic human intellect, investors and analysts frequently employ AI in high- frequency trading methods. Traders who can execute trades on bitcoin exchanges swiftly make more money. High-frequency trading is a type of algorithmic trading practiced by investment and hedge funds in which a computer executes a huge number of orders in fractions of a second. Algorithms based on mathematical computing data, predictive analytics, and prediction methodologies may assess markets in seconds and buy or sell cryptocurrencies.
Insights into Monetizing Cryptocurrency
Crypto traders place a high value on numerous signals. However, with unstructured data dominating the digital landscape, manually generating reliable signals might be practically impossible. Data scientists and developers can utilize Natural Language Processing (NLP) to create models that traders can use to access relevant and clean data. Data can be categorised and entities extracted using AI NLP approaches based on certain features such as currency name, document type, currency founder, and more. Data scientists can then provide accurate trading insights in a way that non-technical traders or investors can grasp via an intuitive dashboard or interface. Using the knowledge gathered, investors and traders can increase their profits.