BEIJING, Dec. 26,
2023 /PRNewswire/ -- MicroAlgo Inc. (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 digital asset market and the rapid rise of finance
and tech companies offer 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 are 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 meet the
challenges of the market and capitalize on 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.'s Bitcoin trading prediction
algorithm based on machine learning and technical indicators
utilizes 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 dealing with
non-linear relationships.MicroAlgo Inc. uses 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. Using LSTM for Bitcoin
price time series allows for better prediction of future price
changes.
Decision tree: A decision tree is a tree model that is capable
of performing complex classification and regression by recursively
dividing data. Using decision trees to model different states of
the market provides our algorithms with more flexible predictive
capabilities.
To more fully understand the technical aspects of the
Bitcoin market, MicroAlgo Inc.'s machine learning and
technical indicator-based Bitcoin trading prediction
algorithm employs a series of technical indicators that analyze
market data, such as price and volume, to extract potential market
patterns. Below are the main technical indicators:
Moving averages (MA): MA are curves formed by averaging prices
over a certain period, which can be used to smooth out 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 fluctuations and
potential trend reversals.
The combined use of these technical indicators allows the
algorithmic technique to analyze the Bitcoin market in
a more comprehensive and multifaceted manner, providing the model
with richer characteristics.
MicroAlgo Inc.'s Bitcoin trading prediction
algorithm based on machine learning and technical indicators plays
a crucial role in the construction of the technical foundation with
data processing and feature engineering. A large amount of raw
market data from multiple Bitcoin exchanges was
required, including price, volume, and market depth. In the data
preparation phase, the following processing was required:
Data cleaning: Removing abnormal values, filling in missing
values, and ensuring 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 through the calculation and transformation of technical
indicators, including the crossover of moving averages, the value
of RSI, and the width of Bollinger bands, etc., in order to better
reflect 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.
Overall, the technical foundation of the algorithm is built on
an in-depth understanding and full utilization of machine learning
models and metrics, 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 analyzing, modelling, and
forecasting the full spectrum of the Bitcoin market.
The selection and design of this technical framework allows 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. Provide an
intelligent decision-making tool for Bitcoin
trading.
By incorporating machine learning models, technical indicator
analysis, and advanced quantitative trading strategies, a
Bitcoin trading prediction algorithm based on machine
learning and technical indicators from MicroAlgo Inc. has
demonstrated superior 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.'s 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 an
affirmation 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 exempted company, is dedicated to the development and
application of bespoke 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 achieve technical goals. The range of
MicroAlgo's services includes algorithm optimization,
accelerating 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 customers through bespoke 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,"
"believes," "predicts," "potential," "continue," and similar
expressions are intended to identify such forward-looking
statements. These forward-looking statements include, without
limitation, MicroAlgo's expectations with respect to future
performance and anticipated financial impacts of the business
transaction.
MicroAlgo undertakes no obligation to update these statements
for revisions or changes after the date of this release, except as
may be required by law.
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SOURCE Microalgo.INC