Cryptocurrency Benchmark Index Generation System
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Solution Overview
Problem
Financial institutions face challenges in providing confidence to clients navigating the cryptocurrency ecosystem due to lukewarm institutional investor confidence and a lack of effective data generation methods for cryptocurrencies.
Innovation Solution
A method and system for generating data on cryptocurrencies, including calculating a weighted benchmark index based on market capitalization and prices, predicting future prices using machine learning models, and determining residual risks from equity and sentiment indices, leveraging blockchain transactions and social media analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional data generation methods are used for cryptocurrencies, then the process is simple, but the reliability and confidence of the data is insufficient for institutional investors
Solution Approach 1:
The system segments data generation into multiple specialized modules: blockchain transaction data collection, market data collection, sentiment analysis from social media, benchmark index calculation, and machine learning model training. Each module processes specific data types independently, then integrates results to produce comprehensive reliable data.
Solution Approach 2:
The patent introduces intermediary components including sentiment analysis systems that process social media data as an intermediate step between raw transactions and final price predictions, and benchmark indexes that serve as intermediaries between individual cryptocurrency performances and portfolio-level risk assessments.
2Reliability
If comprehensive data analysis methods are implemented, then investment confidence improves, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by continuously collecting and preprocessing blockchain transaction data, market data, and social media sentiment data in the background before actual analysis requests. Historical data is pre-cleaned and stored in structured formats, and machine learning models are pre-trained on extensive historical datasets, enabling faster real-time analysis.
Solution Approach 2:
The patent implements parameter changes by adjusting the complexity of analysis based on user needs - offering different levels of benchmark index calculations, selective sentiment analysis for specific cryptocurrencies, and configurable machine learning model depths, allowing users to balance processing time against analysis comprehensiveness.
Data Source
AI summary
A method of generating data on cryptocurrencies is described. Using one or more computer processors, a request to display a benchmark index relating to the cryptocurrencies is received. In response to receiving the request, for each of the cryptocurrencies, a market capitalization value and a price of the cryptocurrency over time are determined. Based on the market capitalization values and the prices over time, the benchmark index is generated and then displayed. In addition, based on the total value of one or more cryptocurrencies over a past period of time, the future price of the one or more cryptocurrencies over the future period of time may be predicted.