Python Financial Model focused on Dividend Yield
Budget: $250 – $750 USD
I am looking for a Python developer to create a financial model focused on analyzing average dividend yield. The model should be able to analyze specific stocks as requested by the client. The ideal candidate should have experience in finance and Python programming. The output format required is a graphical interface in Pandas for Python allowing the user to select different variables to determine historical return based upon the selected variables. Here are some specific details:
1. There will be around 350 individual equities. The list will be provided.
2. The data points provided for each equity will be date, price, dividend yield, total return value in CSV format.
3. Daily values that will need to be calculated are 5 year average dividend yield, percentage above or below, average dividend yield total return percentage, annualized total return, total years.
4. Would like to be able to screen an equity for when its dividend yield is above its 5 year average dividend yield by a certain % (i.e. 25%) and determine return if the equity was purchased when dividend yield is above the average.
5. Would also like to be able to always compare with the S&P 500’s (SPY) return over same time period. Same data will be provided for SPY.
6. Ultimately would like to be able to analyze all 350 +/- equites return based upon buy criteria of dividend yield being over a % of 5 year average, and determine averages.
1. There will be around 350 individual equities. The list will be provided.
2. The data points provided for each equity will be date, price, dividend yield, total return value in CSV format.
3. Daily values that will need to be calculated are 5 year average dividend yield, percentage above or below, average dividend yield total return percentage, annualized total return, total years.
4. Would like to be able to screen an equity for when its dividend yield is above its 5 year average dividend yield by a certain % (i.e. 25%) and determine return if the equity was purchased when dividend yield is above the average.
5. Would also like to be able to always compare with the S&P 500’s (SPY) return over same time period. Same data will be provided for SPY.
6. Ultimately would like to be able to analyze all 350 +/- equites return based upon buy criteria of dividend yield being over a % of 5 year average, and determine averages.