Tools
Discounted Free Cash Flow Calculator
A command-line tool to query stocks and run discounted free cash flow analyses. You may need to install numerize and tabulate. This can be done with the following terminal commands: 1) pip install numerize 2) pip install tabulate. To run, download the python executable below and type “python inv_insights.py” into a terminal. The directory of the python file may need to be specified as well (eg, python /Users/xyzname/Desktop/inv_insights.py).
Type a symbol to pull up basic statistics (eg, price, market cap, forward and trailing PE ratios). Then, type “dcf” to start a DCF analysis for that security. Type “quit” to exit the program. All equity data (US & INT) is sourced from roic.ai.
A command-line tool to evaluate the historical difference in returns between dollar-cost averaging and lump-sum investing. You may need to install the python library tabulate if it has not already been installed. This can be completed with the terminal command “pip install tabulate”. To run, first download the .csv file (data) below and save it on your Desktop. Then, download the python executable script (tool) below and type “python dca_vs_lump_calc.py” into a terminal. The directory of the python file may need to be specified: e.g., python /x/y/Desktop/dca_vs_lump_calc.py.
Type the number of months to dollar cost average for and the total years invested to run an analysis and receive a breakdown of how often, on average, one strategy has outperformed the other historically (when investing in the S&P 500), and by how much. After an analysis, type “r” to enter new info or “q” to exit the program. All Standard and Poor’s 500 (S&P 500) data is sourced from Robert Shiller’s online data at econ.yale.edu/~shiller/data.htm.
Dollar Cost Average vs. Lump Sum Calculator
Retirement Calculator
A command-line tool to calculate retirement savings and evaluate different retirement plans. You may need to install numerize and tabulate. This can be done with the following terminal commands: 1) pip install numerize 2) pip install tabulate. To run, download the python executable below and type “python retirement_calculator.py” into a terminal. The directory of the python file may need to be specified (eg, python /x/y/z/retirement_calculator.py).
Input years until retirement, savings/investments and income data, expected inflation and investment returns, and post-retirement needs to run an analysis with summary statistics, a year by year view of retirement savings, and whether your retirement plan is on track. Type “r” to restart or “q” to exit the program.
A command-line tool to find the S&P 500’s return between two dates (from 1871 to 2022), including adjustments for dividend reinvestment and CPI inflation. You may need to install the python library tabulate if it hasn’t already been installed. This can be completed with the terminal command “pip install tabulate”. To run, first download the .csv file (data) below and save it on your Desktop as is. Then, download the python executable (tool) below and type “python sp500_return_calc.py” into a terminal. The directory of the python file may need to be specified: e.g., python /x/y/Desktop/sp500_return_calc.py.
Type a start date and end date to run an analysis and receive comprehensive S&P 500 return numbers, annualized and in total. After an analysis, type “r” to enter new dates or “q” to exit the program. All S&P 500 and economic data is sourced from Robert Shiller’s online data at econ.yale.edu/~shiller/data.htm.
S&P 500 Return Calculator
Multiple Matrix Table
A spreadsheet matrix of fair value multiples (of free cash flow or earnings) given a 10-year growth rate and terminal growth rate. The row headers represent 10-year growth rates, while the column headers represent terminal growth rates. For example, the cell with value 14.3 (row value 4 and column value 1.5) means that a business that will grow free cash flow/earnings at 4% for the next 10 years then at 1.5% in perpetuity is worth 14.3 times its current free cash flow/earnings. In this example, a discount rate of 10% is used. The spreadsheet has different sheets for different discount rates, as well as a sheet to plug in your own discount rate and any custom numbers. These multiples were created by a program performing mass DCF models and tracing back to current free cash flow multiples. Click the link below to open the spreadsheet.