Add short_selling.parquet and README.md

README.md

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+---
+icon: sort-down
+description: >-
+  This section covers the usage of various short-selling datasets for risk
+  analysis.
+---
+
+# Short Selling
+
+> **Data Notice**: This dataset provides academic research access with a 6-month data lag. 
+> For real-time data access, please visit [sov.ai](https://sov.ai) to subscribe. 
+> For market insights and additional subscription options, check out our newsletter at [blog.sov.ai](https://blog.sov.ai).
+
+```python
+from datasets import load_dataset
+df_over_shorted = load_dataset("sovai/short_selling", split="train").to_pandas().set_index(["ticker","date"])
+```
+    
+
+
+Data is updated weekly as data arrives after market close US-EST time.
+
+
+`Tutorials` are the best documentation — [<mark style="color:blue;">`Short Selling Tutorial`</mark>](https://colab.research.google.com/github/sovai-research/sovai-public/blob/main/notebooks/datasets/Short%20Data.ipynb)
+
+<table data-column-title-hidden data-view="cards"><thead><tr><th>Category</th><th>Details</th></tr></thead><tbody><tr><td><strong>Input Datasets</strong></td><td>Financial Intermediaries, NASDAQ, NYSE, CME</td></tr><tr><td><strong>Models Used</strong></td><td>Parsing Techniques</td></tr><tr><td><strong>Model Outputs</strong></td><td>Predictions, Volume</td></tr></tbody></table>
+
+***
+
+## Description
+
+This dataset provides comprehensive information on short-selling activity for various stocks, including metrics on short interest, volume, and related indicators.&#x20;
+
+It offers investors and analysts insights into market sentiment, potential short squeezes, and overall risk assessment, enabling more informed decision-making in trading strategies and liquidity analysis.
+
+## Data Access
+
+### Over-shorted Dataset
+
+The Over-Shorted dataset provides information on short interest and potentially over-shorted stocks, offering insights into short selling activity and related metrics.
+
+#### Latest Data
+
+```python
+import sov as sov
+df_over_shorted = sov.data("short/over_shorted")
+```
+
+#### All Data
+
+```python
+import sov as sov
+df_over_shorted = sov.data("short/over_shorted", full_history=True)
+```
+
+### Short Volume Dataset
+
+The Short Volume dataset offers information on the short selling volume for specified stocks, including breakdowns by different types of market participants.
+
+#### Latest Data
+
+```python
+import sov as sov
+df_short_volume = sov.data("short/volume")
+```
+
+#### All Data
+
+```python
+import sov as sov
+df_short_volume = sov.data("short/volume", full_history=True)
+```
+
+### Accessing Specific Tickers
+
+You can also retrieve data for specific tickers across these datasets. For example:
+
+```python
+df_ticker_over_shorted = sov.data("short/over_shorted", tickers=["AAPL", "MSFT"])
+df_ticker_short_volume = sov.data("short/volume", tickers=["AAPL", "MSFT"])
+```
+
+## Data Dictionary
+
+**Over-Shorted Dataset:**
+
+| Column Name        | Description                             |
+| ------------------ | --------------------------------------- |
+| ticker             | Stock symbol                            |
+| date               | Date of the data point                  |
+| over\_shorted      | Measure of how over-shorted a stock is  |
+| over\_shorted\_chg | Change in the over-shorted measure      |
+| short\_interest    | Number of shares sold short             |
+| number\_of\_shares | Total number of outstanding shares      |
+| short\_percentage  | Percentage of float sold short          |
+| short\_prediction  | Predicted short interest                |
+| days\_to\_cover    | Number of days to cover short positions |
+| market\_cap        | Market capitalization of the company    |
+| total\_revenue     | Total revenue of the company            |
+| volume             | Trading volume                          |
+
+
+
+**Short Volume Dataset:**
+
+| Column Name                    | Description                                           |
+| ------------------------------ | ----------------------------------------------------- |
+| ticker                         | Stock symbol                                          |
+| date                           | Date of the data point                                |
+| short\_volume                  | Volume of shares sold short                           |
+| total\_volume                  | Total trading volume                                  |
+| short\_volume\_ratio\_exchange | Ratio of short volume to total volume on the exchange |
+| retail\_short\_ratio           | Ratio of short volume from retail traders             |
+| institutional\_short\_ratio    | Ratio of short volume from institutional traders      |
+| market\_maker\_short\_ratio    | Ratio of short volume from market makers              |
+
+## Use Cases
+
+* Short Squeeze Analysis: Identify potentially over-shorted stocks that might be candidates for a short squeeze.
+* Risk Assessment: Evaluate the short interest in a stock as part of overall risk assessment.
+* Market Sentiment Analysis: Use short volume data to gauge market sentiment towards specific stocks.
+* Trading Strategy Development: Incorporate short selling data into quantitative trading strategies.
+* Liquidity Analysis: Assess the liquidity of a stock by analyzing the days to cover metric.
+* Sector Trends: Identify trends in short selling activity across different sectors or industries.
+
+
+
+These datasets form a comprehensive toolkit for short selling analysis, enabling detailed examination of short interest, volume, and related metrics across different equities.

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