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* Risk-Return Analysis with OpenBB This notebook demonstrates advanced techniques for risk-return analysis and portfolio optimization using OpenBB. We'll explore various asset classes, implement modern portfolio theory, and utilize OpenBB's extensive financial analysis capabilities. This comprehensive guide covers: Data collection and preprocessing Exploratory data analysis with visualizations Risk and return calculations Efficient frontier computation Portfolio optimization techniques Advanced risk metrics (VaR, CVaR) Performance attribution Scenario analysis and stress testing By the end of this notebook, you'll have a deep understanding of how to use OpenBB for sophisticated financial analysis and portfolio management. * Update COMMUNITY_EXAMPLE_TEMPLATE (1).ipynb * Update COMMUNITY_EXAMPLE_TEMPLATE (1).ipynb * Update COMMUNITY_EXAMPLE_TEMPLATE (1).ipynb * Update COMMUNITY_EXAMPLE_TEMPLATE (1).ipynb * Rename COMMUNITY_EXAMPLE_TEMPLATE (1).ipynb to Risk-Return Tradeoff Model Notebook (1).ipynb * Add files via upload * Delete examples/Risk-Return Tradeoff Model Notebook #6710.ipynb * Update Risk-Return Tradeoff Model Notebook (1).ipynb * Rename Risk-Return Tradeoff Model Notebook (1).ipynb to Risk-Return Tradeoff Model Notebook.ipynb * Rename Risk-Return Tradeoff Model Notebook.ipynb to Risk-Return Analysis and Portfolio Management in OpenBB * Delete examples/Risk-Return Analysis and Portfolio Management in OpenBB * Add files via upload * Rename Risk-Return Analysis and Portfolio Management in OpenBB (2).ipynb to Risk-Return Analysis and Portfolio Management in OpenBB.ipynb * Delete examples/Risk-Return Analysis and Portfolio Management in OpenBB.ipynb * Add files via upload * Rename Risk-Return Analysis and Portfolio Management in OpenBB (1).ipynb to Risk-Return Analysis and Portfolio Management in OpenBB.ipynb * Delete examples/Risk-Return Analysis and Portfolio Management in OpenBB.ipynb * Add files via upload Images Encoding have been changes to base64 to prevent spelling errors while merging * Delete examples/Risk-Return Analysis and Portfolio Management in OpenBB (1).ipynb * Add files via upload Cell Output Images Encoding has been changed to base64 which may have caused spelling errors. --------- Co-authored-by: James Maslek <jmaslek11@gmail.com>
Jupyter Notebook Examples Using the OpenBB Platform
This folder is a collection of example notebooks that demonstrate some of the ways to get started with using the OpenBB Platform. To run them, ensure that the active kernel selected is the same Python virtual environment where OpenBB was installed.
Table of Contents
googleColab
This notebook installs the OpenBB Platform in a Google Colab environment with examples for:
- Logging into OpenBB Hub
- Setting the output preference
- Fetching options and company fundamentals data
- Creating bar chart visualizations
findSymbols
This notebook provides an introduction to discovering, finding, and searching ticker symbols.
- Search
- Find company and institutional filings
- Screen stocks by region and metrics
loadHistoricalPriceData
This notebook walks through collecting historical price data, at different intervals, using a variety of sources.
- Loading data with different intervals, and changing sources
- A brief explanation of ticker symbology
- Resampling a time series index
- Some differences between providers, and comparing outputs
financialStatements
This set of examples introduces financial statements in the OpenBB Platform and compares the free cash flow yields of large-cap retail industry companies.
- Financial statements
- What to expect with data from different sources
- Financial attributes
- Ratios and other metrics
copperToGoldRatio
This notebook explains how to calculate and plot the Copper-to-Gold ratio.
- Loading historical front-month futures prices.
- Getting the historical series from FRED for the 10-year constant maturity US treasury bill.
- Performing basic DataFrame operations.
- Creating charts with Plotly Graph Objects.
openbbPlatformAsLLMTools
This notebook shows you how you can use OpenbB Platform as functions in an LLM by leveraging function calling.
- Create an LLM tool from an OpenBB Platform function
- Convert all OpenBB Platform functions to LLM tools
- Build a basic Langchain agent that can utilize function calling
- Run the agent
usdLiquidityIndex
This notebook demonstrates how to query the Federal Reserve Economic Database and recreate the USD Liquidity Index.
- Search FRED for series IDs.
- Load multiple series as a single call.
- Unpacking the data response from the FRED query.
- Perform arithmetic operations on a DataFrame.
- Normalization methods for a series or DataFrame.
- Simple processes for creating charts.
impliedEarningsMove
This notebook demonstrates how to calculate the implied earnings move using options prices from free sources.
- Get upcoming earnings calendar.
- Fetch options chains data.
- Get the last price of the underlying stock.
- Find the nearest call and put strikes to the last price of the stock.
- Calculate the implied daily move using the price of a straddle.
streamlit/news
This is an example Streamlit dashboard for news headlines with data from Biztoc, Benzinga, FMP, Intrinio, and Tiingo.
:::warning At least one API key is required. You can get a free Biztoc API key here :::
To run, copy the file to your system, open a terminal, navigate to where the file is, and with your obb Python environment active, enter:
pip install streamlit
pip install openbb-biztoc
streamlit run news.py