Fin Maestro Web

Find your trading, investing edge using the most advanced web app for technical and fundamental research combined with real time sentiment analysis.

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Install / Use

npx skills add devfinwiz/Fin-Maestro-Web

Installs into whichever agent you are using.

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README

<h1>Disclaimer: This project is not maintained anymore. Do reach out if you feel you can contribute in any way. </h1> <p align="center"> <img width="458" alt="N2" src="https://user-images.githubusercontent.com/78873223/225271710-28960aeb-8bb4-475d-8c4c-af323fe4b222.PNG"> </p> <div align="center">

</div> <h1 align="center">Fin-Maestro </h1> <p align="center"> <a href="https://www.codefactor.io/repository/github/devfinwiz/fin-maestro"> <img src="https://img.shields.io/badge/CodeFactor-A-blue&?style=for-the-badge&color=blue"> </a> <a href=""> <img src="https://img.shields.io/badge/Python-3.10.11-blue&?style=for-the-badge&color=blue"> </a> <a href=""> <img src="https://img.shields.io/badge/Vue.js-3-blue&?style=for-the-badge&color=blue"> </a> <a href="https://github.com/devfinwiz/Fin-Maestro/blob/master/LICENSE"> <img src="https://img.shields.io/github/license/devfinwiz/Fin-Maestro?color=maroon&style=for-the-badge"> </a> <a href="https://github.com/devfinwiz/Fin-Maestro/commits/master"> <img src="https://img.shields.io/github/last-commit/devfinwiz/Fin-Maestro?color=yellow&style=for-the-badge"> </a> <a href="https://github.com/devfinwiz/Fin-Maestro/graphs/contributors"> <img src="https://img.shields.io/github/contributors/devfinwiz/Fin-Maestro?color=indigo&style=for-the-badge"> </a> <a href="https://github.com/devfinwiz/Fin-Maestro/issues"> <img src="https://img.shields.io/github/issues-raw/devfinwiz/Fin-Maestro?color=indigo&style=for-the-badge"> </a> </p><br>

Change Log

🚀 Introducing Fin-Maestro-Kin:

Our new all-in-one finance API, designed to revolutionize financial data analysis and processing.

✔ Seamlessly fetch historical data, analyze market trends, and evaluate sentiment with ease.

⚡ Empowered with FastAPI brilliance, offering lightning-fast performance and scalability.

📦 Publish your own financial applications powered by Fin-Maestro-Kin and witness unparalleled insights into the market.

🔗 View Fin-Maestro-Kin on PyPI

Fin-Maestro

Fin-Maestro is a cutting-edge web application that aims to make it easier for market participants to operate more effectively and intelligently by thoroughly examining various parameters of various financial instruments.

How install Fin-Maestro?

(Refer to branch 'docker'.)

Manual: To be able to raise the project you must have the following prerequisites:

[x] Vite.js (https://vitejs.dev/guide/)

[x] python 3.10.11 (https://www.python.org/downloads/release/python-31011/)

In the case of the backend, go to the path ~/backend/scr/ and execute the following command: pip install -r requirements.txt

Additionally you should consider installing the libraries TA_Lib, tensorflow, stable-baselines3 and tensorflow-intel

In the case of the frontend, go to the path ~/frontend/ and execute the following command: npm install and then execute: npm run dev
Docker: To be able to raise the project you must have the following prerequisites:

[x] Docker/Docker-compose (https://docs.docker.com/desktop/)

Go to the main path and run the following command: docker-compose up -d --build

Common step to enable QuestDB Integration to Fin-Maestro for smart caching:

Run QuestDB Image: <br>

docker run -p 9000:9000 -p 9009:9009 -p 8812:8812 -p 9003:9003 questdb/questdb:7.3.3

Fin-Maestro is comprised of 10 main modules:

1. Valuation Determiner

The Valuation Determiner considers a variety of the stock's financial factors before calculating its fair value using the book value, yearly sales, annual earnings, and Graham number. It determines if the stock is undervalued, reasonably valued, or overvalued after the computation is complete.

Input: 
1. Stock Name

Output:
1. Valuation as per book value (VAP_BV)
2. Valuation as per annual sales (VAP_SALES)
3. Valuation as per earnings (VAP_EARNINGS)
4. Valuation as per Graham number (VAP_GRAHAM)
5. Status: Undervalued / Fairly Valued / Overvalued

Unique Aspect:

For equities from various sectors, a separate procedure is utilised to determine the fair value. The Valuation Determiner module automatically modifies the stock's fair value computation process to produce enhanced dependability and accuracy.

Reason: 
Some stocks tend to trade at higher multiples due to it's nature of the business. Example: FMCG Stocks, monopoly/duopoly stocks
Thus, if such stocks are not differentiated, the result obtained would always indicate that stock is overvalued. This may result 
in missed chances to add companies to your portfolio at the right time.

2. Mock Trader

Without using real money for trading, market participants can place simulated trades using Mock Trader. Participants in the market might use these trades to test a certain trading strategy or analysis.

Input: 
1. Stock Name
2. Transaction type: Buy/Sell

Output:
1. Trading position in the requested stock.

3. Sentiment Analyzer

The Sentiment Analyzer module analyses option chain data for indices and securities to produce a sentiment that indicates whether the index or stock is oversold, slightly oversold, slightly overbought, or overbought.

Input: 
1. Stock Name

Output:
1. Sentiment for Nifty and Bank Nifty (needs no user input)
2. Sentiment for requested stock (oversold, slightly oversold, slightly overbought, or overbought)

4. Pattern Analyzer

Finding a certain technical chart pattern across all the stocks is done by the Pattern Analyzer module, which then outputs the stock name and a chart showing the pattern's position with a yellow pointer just above it. Also, it can exclude equities whose technical charts show a breakdown, breakout, or consolidation.

Input: 
1. Technical pattern name

Output:
1. Candlestick chart of stocks where the pattern is located indicating the target pattern's position with yellow pointer.
2. List of stocks that witnessing consolidation, breakout or breakdown.