About the client
Eudaimonia specializes in the creation and implementation of robust market forecasting technologies.
They represent the belief that financial markets are not limited to those who only serve themselves; they are dedicated to excellence and bringing the best out of their employees and products: for that end, in and of itself.
Project goals
The primary goal of the project is to build a web platform to leverege historical cryptocurrency data and machine learning models to generate accurate forecasted data regarding the future performance of market. Project should also empower both administrators and users with an efficient and user-friendly platform.
The admin management functionality encompasses the ability to create and set subscriptions, add and update machine learning models, start forecasting. The system should provide documentation for the API, allowing users to easily integrate the application into their own platforms.
Furthermore, the application has to offer features for users to track their requests, access support, and have the flexibility to choose suitable subscription plans that cater to their specific needs.
Key challenge
1. Market Volatility: Faced with the high volatility inherent in the cryptocurrency, stocks, and bonds markets, our team tailored adaptive models that could swiftly respond to sudden price swings and unexpected events, ensuring reliable predictions amidst rapid market changes.
2. Feature Engineering: The task of developing relevant and informative features from raw market data demanded in-depth research. Through domain expertise and rigorous analysis, we successfully identified and integrated key indicators to accurately capture market trends.
3. Efficient Data Pipelines: Recognizing the need for timely and accurate data processing, our team developed efficient and highly parallelized data pipelines. These pipelines ensured seamless acquisition, processing, and feature engineering on the data, optimizing the speed and reliability of our forecasting tools.
4. Centralized System for Model Testing: We created a robust centralized system tailored for the testing and development of a multitude of Time Series Forecasting models. This system, designed for efficiency and modifiability, supported a wide range of model architectures and input features, streamlining our experimentation and optimization processes.
5. Implement the architecture for all of the components of application.
6. Data quality and reliability: Ensuring the historical cryptocurrency data used to train ML models is accurate and up-to-date.
7. Different forecasting schemas and prediction model types.
Our solutions
We developed a Time Series Forecasting solution for volatile financial markets, utilizing adaptive models and efficient data pipelines. Rigorous feature engineering enhanced prediction accuracy, while a centralized system streamlined the testing of diverse forecasting models.
Web application based on microservices architecture, with logical definition of every service purpose. Platform empowers admin and user UI, and offers customer API for the future predictions of cryptocurrencies.
The implementation involved the integration of a trusted crypto data source (polygon. API) to upload the historical information, Google Cloud Vertex AI for the deployment and inference of ML Models, and Azure Functions to prepare and post-process the forecasted data.
Result
With Eudaimonia Aurora everyone got an access to a suite of tools designed to help with making the most out of investments.
Our platform allows tracking of the market trends, analyze historical data, and create custom forecasting scenarios to meet paricular needs. Whether you’re looking to diversify your portfolio or maximize your returns, our Crypto Forecasting Software is the solution you’ve been looking for.