Fin-Maestro

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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

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.

5. Indices Health

This module employs a color-coded system to show the overall valuation status of all NSE indices. It makes use of the hues red, orange, and green. Green means that the valuations are good enough to begin SIPs, while orange and red indicate that the valuations are neutral and expensive respectively.

Output:
1. List of indices that are colored-wrapped

6. SWOT Analyzer

This module examines a stock's technical parameters and fundamentals before generating a SWOT that lists the stock's strengths, weaknesses, opportunities, and threats.

Inputs:
1. Stock name

Output:
1. SWOT for the requested stock.

7. Fundamental Scans

This module examines the financial data of the stocks and sorts stocks that are attractive according to their Graham number, book value, annual sales, and earnings.

Output:
1. List of stocks attractive as per its book value. 
2. List of stocks attractive as per its sales. 
3. List of stocks attractive as per its earnings.
4. List of stocks trading below Graham Number.

8. Crypto Technical Scans

For traders' convenience, this module analyses the technical charts of the specified cryptocurrency and then generates a plot showing the automatically generated support and resistance levels for that cryptocurrency.

Inputs:
1. Cryptocurrency name

Output:
1. List of stocks attractive as per its book value. 
2. List of stocks attractive as per its sales. 
3. List of stocks attractive as per its earnings.
4. List of stocks trading below Graham Number.

9. Strategy Backtester

For any requested stock, this module now backtests a hardcoded trading strategy and generates a visually appealing report with information on the number of trades, total returns, maximum drawdown, and average return.

Inputs:
1. Stock name

Output:
1. A plot indicating the backtest results for the requested stock.

10. Buy/Sell Signals Generator

For any requested stock, this module produces a visually appealing plot with long/short green and red colored markers respectively as signals. These signals can be used to interpet the further direction of the stock.

Inputs:
1. Stock name
2. Number of signals (total number of buy or sell signals that must be plotted)

Output:
1. A visually appealing plot indicating buy and sell signals for the requested stock.

Contributing:

Please feel free to suggest improvements, bugs by creating an issue.
Please follow the Guidelines for Contributing while making a pull request.
Please check the Upcoming Features for a list of exciting features we plan to implement in the future.

Disclaimer:

DO NOT use the results provided by the web app 'solely' to make your trading/investment decisions.
Always backtest and analyze the stocks manually before you trade.
Consult your financial advisor before making any trading/investment decisions.
The authors/contributors and the web app will not be held liable for your losses.