Metadata-Version: 2.4
Name: numin2
Version: 1.0.1
Summary: numin package
Author-email: Gautam Shroff <gautam.shroff@iiitd.ac.in>
Project-URL: Homepage, https://github.com/gmshroff/ai_fin
Project-URL: Issues, https://github.com/gmshroff/ai_fin/issues
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.10
Description-Content-Type: text/markdown
Requires-Dist: anvil_uplink
Requires-Dist: import_ipynb
Requires-Dist: ipython
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: pandas_ta
Requires-Dist: pytz
Requires-Dist: requests

# numin2 Package

**numin2** is a Python package designed for algorithmic trading and backtesting providing an API called **Numin2API**.

**numin (v1)** is out of service as of Dec 2025

**numin2** is under development; features available are documented below

## Features

- **Data Retrieval:** Download training, round, and validation data.
- **Prediction Submission:**  TBD
- **Real-Time Round Management:** TBD
- **Backtesting:** Backtesting cross-sectional predictions vs targets for Nifty50
- **File Management:** TBD
- **Returns Summary:** TBD

## Supported Methods

- **Data Download:**
    - `get_data_for_month(self,year,month,batch_size=4,window_size=100,target_type='rank'):`
    -   Returns a torch dataloader for the given year and month of Nifty 50 or n returns
    -   Dimension of each day is 100,n. Returns tensor of shape batch_size,window_size,n for features. Default n=50. (Later n will be a parameter).
    -   Targets are next day returns / ranked returns of shape batch_size,n

- **Backytesting**
    - `backtest_positions(positions,targets)`
    - Taks a batch of positions for 50 stocks
    - Returns a dict such as {'daily_pnl','total_profit','sharpe_ratio,'mean_daily_return'}

## Installation

Install numin2 using pip:

```bash
pip install numin2

