Project-idea: Create tool for screening financial instruments and opt for best asset
Main idea: type in a stock and through an API like Google Finance/Yahoo Finance/Bloomberg retrieving the stock prices. Those stock prices can then be computed with a statistics library. Those computed results then get displayed in a table on the User-Front-End. All the stocks can be added into a list on the User-Front. On the left-hand side there is going to be all the names or ISINs of the stock, on the right-hand side there is going to be a listing of all calculated ratios/figures.
This table will be persisted into a database per each user. Each user will have its own session and can register themself. In addition to that there will be a sample template with a few stocks to start with - this is provided to each and every user by default.
Peer Review:
Since you persisted all the stock-ISINs in a table this table can be considered a portfolio. The portfolio can then be compared in a fashion of a peer review.
Also each stock's figure can be peer reviewed.
Charts:
The portfolios figures can be displayed as a Candle-Chart/Bar-Chart and anything else there is availble.
Export Options:
The table can then be exported as an Excel-spreadsheet, Csv-File or Pdf-table with static values.
Additional ideas:
These ideas are only to be implemented if there is enough time left:
+ Manipulation/Creation of own formula. The Python Pandas equation of each figure/stats can be edited and costum adjusted. Those costum adjusted equations are persisted in yet another list (database)
+desktop app written in C++ using the Rest-API of our Controller
+dynamic Excel-Spreadsheet. There is plug-in provided to Excel to be able to use our computations and load them into an excel spreadsheet. They are updated automatically.
+ including charts into exported Excel/Pdf-file (CSV obviously doesn't work)
Specific stats/figures for screening:
drawn from book "Practical Risk-Adjusted Performance Measurement" by Carl R. Bacon as published by Wiley
Descriptive stuff:+ annualised return+ continuously compounded returns (or log returns)+ mean absolute deviation + skewness+ kurtosis+ correlation (other Benchmarks for instance)
Risk (but drawdown, see below):+ sharpe ratio+ revised sharpe ratio+ adjusted sharpe ratio+ skewness-kurtosis ratio
Regression+ Jensen's Alpha (no diff. to "normal" regression alpha)+ Beta (systematic risk or vol) of Capital Asset Pricing Model (no diff. to "normal" regression alpha)
Drawdown+Max Drawdown
Goal
Our goal is it to have a tool that brings up the best stocks to choose from in your portfolio. Those are the ones you want to invest in.