Update README.md

README.md

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 ![Logo](https://github.com/ggsmith842/thrifty-rabbit/blob/main/thirfyRabbit.jpg?raw=true)
 
+# Modern Portfolio Methods in Python
 
+This repository provides a set of Python modules that implement modern portfolio methods. The modules can be used to collect price data, use goal-based advising techniques, analyze a portfolio for diversification, and visualize the efficient frontier of a portfolio.
 
-### Goals:
-1. Monitor a portfolio for performance and health.
-2. Optimize a portfolio by creating a robo-advisor with an objective of maximizing long-term returns.
+## Installation
 
-#### 1. Monitoring
+To install the modules, simply clone the repository and run the following command:
 
-How will this be done?
+pip install -e .
 
-1. Collect fundamental data for assets in the portfolio using the [yfinance](https://pypi.org/project/yfinance/) package.
-2. Calculate metrics used to evaluate a stock for a dividend portfolio
-    - Yield (%)
-    - Dividend Payout Ratio
-    - Dividend Coverage Ratio
-    - Free Cash Flow to Equity
-    - Net Debt to EBIDTA Ratio
-    - BETA (Volatitlity)
-3. Establish rules determining the health of the assets in the portfolio. Examples are:
-    - a company stops paying a dividend
-    - a dividend yield has steadily descrased for 2 quarters
-    - a company is low on cash
-4. Develop a portfolio health score and thresholds using the rules and metrics established above
-5. Visualize and report results
-6. Automate reporting and data refreshes.
+## Usage
+The modules in this repository can be used as follows:
 
-#### 2. Automate and Optimize
+To collect price data, use the get_price_data() function.
+To use goal-based advising techniques, use the goal_based_advising() function.
+To analyze a portfolio for diversification, use the portfolio_diversification() function.
+To visualize the efficient frontier of a portfolio, use the efficient_frontier() function.
 
-1. Using [pyportfolioopt](https://pypi.org/project/pyportfolioopt/)
 
-(Coming soon)
+## Examples
+The repository includes a number of examples that demonstrate how to use the modules. The examples can be found in the examples directory.
 
+## Documentation
+The documentation for the modules can be found in the docs directory. The documentation includes detailed descriptions of the functions and classes in the modules.
+
+## Contributing
+Contributions to this repository are welcome. To contribute, simply fork the repository and submit a pull request.
+
+## License
+This repository is licensed under the MIT License.
+## Credits
+
+This package uses the following packages:
+
+* yfinance: https://pypi.org/project/yfinance/
+* pypfopt: https://pypfopt.readthedocs.io/en/stable/
+
+## References
+* [Robo-Advisor with Python: A hands-on guide to building and operating your own Robo-advisor](https://github.com/aki-ranin/robo-advisor-with-python) 
+* [yfinance documentation](https://pypi.org/project/yfinance/)
+* [pypfopt documentation](https://pypfopt.readthedocs.io/en/stable/)
 
 
-### Data Model
 
-(Coming soon)