MicroAlgo Inc. announced Bitcoin Trading Prediction Algorithm based on machine learning and technical indicators

BEIJING, December 26, 2023 /PRNewswire/ — MicroAlgo Inc . (NASDAQ:MIC) was awarded the 2017 FIFA World Cup. MLGO (NASDAQ: MLGO) (the “Company” or “MicroAlgo”), today announced a Bitcoin trading prediction algorithm based on machine learning and technical indicators. The algorithm combines deep learning, technical analysis and quantitative trading strategies to provide investors with more accurate and intelligent decision support. By learning and analyzing a large amount of data from the Bitcoin market, the algorithm can better capture the characteristics and patterns of the market and provide more reliable price predictions.

The booming market for digital assets and the rapid rise of financial and technology companies provide the opportunity to develop innovative trading algorithms. Algorithms based on machine learning and technical indicators are not only better adapted to the complexity of the Bitcoin market, but is also expected to provide investors with smarter and more efficient trading decision-making tools. MicroAlgo Inc. believes that the future of the digital asset market is promising, and MicroAlgo Inc. believes that through algorithmic innovation it can better face the challenges of the market and take advantage of the opportunities. MicroAlgo Inc believes that its innovative algorithm can be applied not only to the Bitcoin market, but also to other digital assets, providing investors with more reliable decision-making support.

MicroAlgo Inc Bitcoin trading prediction algorithm based on machine learning and technical indicators uses a large amount of market data to train a model to predict the future movement of the Bitcoin price. The following are the main machine learning models used:

Support Vector Machines (SVM): SVM is a powerful classification and regression algorithm that performs well in handling non-linear relationships. MicroAlgo Inc. use SVM to capture complex patterns in Bitcoin‘s price movements to help us better understand the market.

Deep learning model: The long short-term memory network (LSTM) is a deep learning model for sequential data that captures long-term dependencies in data. Use LSTM for Bitcoin price time series allows for better prediction of future price changes.

Decision Tree: A decision tree is a tree model capable of performing complex classification and regression by recursively partitioning data. By using decision trees to model different states of the market, our algorithms provide more flexible forecasting capabilities.

To understand the technical aspects of the Bitcoin market, MicroAlgo Inc. s machine learning and technical indicator-based Bitcoin trading prediction algorithm uses a series of technical indicators that analyze market data, such as price and volume, to extract potential market patterns. Below are the most important technical indicators:

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Moving Averages (MA): MA are curves formed by the average prices over a certain period of time, which can be used to smooth price fluctuations and help us capture trends in the market.

Relative Strength Index (RSI): RSI is an indicator used to measure overbought and oversold conditions in the market, which helps us determine the strength of the market.

Bollinger Bands: Bollinger Bands is an indicator that measures price volatility by calculating the standard deviation of prices, which can be used to determine the extent of price swings and potential trend reversals.

The combined use of these technical indicators allows the algorithmic technique to the Bitcoin marketed in a more comprehensive and multifaceted manner, providing the model with richer features.

MicroAlgo Inc Bitcoin trading prediction algorithm based on machine learning and technical indicators play a decisive role in the construction of the technical foundation with data processing and feature engineering. A large amount of raw market data from multiple Bitcoin trade-offs were necessary, including price, volume and market depth. In the data preparation phase, the following processing was necessary:

Data cleaning: Remove abnormal values, fill in missing values ​​and ensure that the data used is clean and complete.

Data standardization: Standardize different features to ensure the stability of the model during the training process.

Feature engineering: A series of representative features are constructed by calculating and transforming technical indicators, including the crossover of moving averages, the value of RSI, and the width of Bollinger bands, etc., in order to understand the dynamics of the market .

These data processing and feature engineering steps provide high-quality training data for our model and a solid foundation for the performance of the algorithm.

In general, the technical foundation of the algorithm is built on a deep understanding and full utilization of machine learning models and statistics, and through data processing and feature engineering, the raw data is transformed into valuable information that provides more comprehensive and accurate inputs to the model. The synergy of these tools enables us to better manage and transform data during data processing and ensure data quality for model training.

By integrating these technical frameworks, we have built a robust and flexible system capable of handling the full spectrum of the Bitcoin market. The choice and design of this technical framework enables our algorithms to not only meet current needs, but also have the feasibility for future expansion and upgrades. The successful development of a Bitcoin trading prediction algorithm based on machine learning and technical indicators amid a booming digital asset market and a wave of fintech innovation. Provides an intelligent decision making tool for Bitcoin trade.

By incorporating machine learning models, technical indicator analysis and advanced quantitative trading strategies, Bitcoin trading prediction algorithm based on machine learning and technical indicators from MicroAlgo Inc. has shown excellent performance on historical data. MicroAlgo Inc. will continue to optimize and upgrade this algorithm to better adapt to the ever-changing market environment and help investors achieve more sustainable and robust investment growth in the digital asset market.

MicroAlgo Inc Bitcoin trading prediction algorithm based on machine learning and technical indicators will become an important milestone in the field of financial technology, leading the way for the future of investment. This is not only a confirmation of technological innovation, but also a strong proof that the financial sector is constantly moving towards intelligence and efficiency.

About MicroAlgo Inc.

MicroAlgo Inc. (the “MicroAlgo”), a Cayman Islands exempt company, is dedicated to the development and application of custom central processing algorithms. MicroAlgo provides comprehensive solutions to customers by integrating central processing algorithms with software or hardware, or both, thereby helping them to increase the number of customers, improve end-user satisfaction, achieve direct cost savings, reduce power consumption and meet technical goals . The range of MicroAlgo’s services include algorithm optimization, accelerated computing power without the need for hardware upgrades, lightweight data processing and data intelligence services. MicroAlgo’s ability to efficiently deliver software and hardware optimization to clients through custom central processing algorithms serves as a driving force for MicroAlgo’s long-term development.

Forward-looking statements

This press release contains statements that may constitute “forward-looking statements”. Forward-looking statements are subject to numerous conditions, many of which are beyond the control of MicroAlgo, including those set forth in the Risk Factors section of MicroAlgo’s periodic reports on Forms 10-K and 8-K filed with the SEC. Copies are available on the SEC’s website, www.sec.gov. Words such as “expect,” “estimate,” “project,” “budget,” “forecast,” “anticipate,” “intend,” “plan,” “may,” “will,” “could,” “should,” “believe,” “anticipate,” “potential,” “continue,” and similar expressions are intended to identify such forward-looking statements. These forward-looking statements include, without limitation, MicroAlgo’s expectations regarding future performance and expected financial impact of the business transaction.

MicroAlgo undertakes no obligation to update these statements for revisions or changes after the date of this release, except as required by law.

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SOURCE Microalgo.INC