Modern Portfolio Theory Statistics
September 21, 2014 by Gouthaman BalaramanThis is a small widget that lets you view the modern portfolio theory statistics for a selection of stocks
This widget shows Modern Portfolio Theory (MPT) statistics for a selected list of stocks. The calculations were made using Quandl data in the WIKI dataset. The ETF SPY was used as a benchmark using a 5-year time horizon. If the time series is not long enough, then an N/A is shown. You can also download the CSV_File containing all the metrics.
| Ticker | {{tickerData.Ticker}} |
| Alpha (%) | {{tickerData.Alpha}} |
| Beta | {{tickerData.Beta}} |
| R-Squared | {{tickerData.RSquared}} |
| Momentum (%) | {{tickerData.Momentum}} |
| Annualized Return (%) | {{tickerData.AnnualizedReturn}} |
| Standard Deviation (%) | {{tickerData.StandardDeviation}} |
| Sharpe Ratio | {{tickerData.SharpeRatio}} |
| Sortino Ratio | {{tickerData.SortinoRatio}} |
| Information Ratio | {{tickerData.InformationRatio}} |
| Treynor Ratio | {{tickerData.TreynorRatio}} |
| Tracking Error (%) | {{tickerData.TrackingError}} |
| Upside Capture (%) | {{tickerData.UpsideCapture}} |
| Downside Capture (%) | {{tickerData.DownsideCapture}} |
{{message}}
finance investing widget
Related Post
- Understanding the Econometric Factor Model
- Econometric Factor Model
- Calculating Stock Beta, Volatility, and More
- On the Convergence of Hull White Monte Carlo Simulations
- Valuing Options on Commodity Futures Using QuantLib Python
I am Goutham Balaraman, and I explore topics in quantitative finance, programming, and data science. You can follow me @gsbalaraman.
Updated posts from this blog and transcripts of Luigi's screencasts on YouTube is compiled into QuantLib Python Cookbook .