Inspiration
Effective investment of financial assets in prospective firms:
- Purchase of assets of promising companies with high profitability for dividends.
- Purchase of assets of promising companies with high profitability for resale.
- Identification of financial bubbles.
What it does
The software is based on a proprietary innovation-driven market model. We have integrated it into Google Cloud using BigQuery to improve efficiency and performance. Our solution analyzes the current operations of a selected company and provides investment recommendations by assessing whether its market price corresponds to its profitability, through calculating the growth rates of its profits and the increase in its stock price. Our innovation-driven market model describes and forecasts the dynamics of company sales and profits based on the accumulation of information within the economic system. The modeling is performed in accordance with the algorithm of the innovation-driven market model, using the statistical law of random walk (the gambler’s ruin problem) for a given number of transactions. Non-economic preferences and innovations are taken into account.
How we built it
We created a working chatbot based on business analytics, using our own mathematical model of the investment market, written in Python.
Challenges we ran into
Writing a chatbot code based on business analytics using an investment market model and integrating it into BigQuery.
Accomplishments that we're proud of
We have created a working chatbot model based on business analytics, based on the investment market model.
What we learned
We developed technology to integrate an innovation-market model using business analytics using BigQuery in Google Cloud.
What's next for THE INNOVATION-MARKET MODEL IN GOOGLE CLOUD
We will develop a service for analyzing the economic activities of companies and generating recommendations for investors to enable effective capital investments.
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