portfolio-analytics

| French version

PortfolioAnalytics v0.0.4 (Changelog)

In order to track my personal stock market investments performances, as well as to analyse trading strategies on my blog Le Quant 40, I wanted to use portfolio performances measures computed in JavaScript.

Why in JavaScript ? Because I am a fan of Google Sheets, which is easily extensible thanks to Google Apps Script, a JavaScript-based language.

After several fruitless hours of Googling (incomplete codes, incorrect codes, undocumented codes...), I decided to create my own JavaScript library of such portfolio performances measures, hoping that it could be useful to other people...

Features

• Compatible with Google Sheets
• Compatible with any browser supporting ECMAScript 5 (i.e., front-end development)
• Compatible with Node.js (i.e., back-end development)
• (Performances) Automatically uses JavaScript Typed Arrays
• (Accuracy) Internally uses accurate numerical algorithms (e.g., corrected two pass algorithms for mean, variance, skewness and kurtosis, accurate algorithm for error function...)
• Code continuously tested and integrated by Travis CI
• Code heavily documented using JSDoc

Usage

Usage in Google Sheets

If you would like to use PortfolioAnalytics in Google Sheets, you can either:

• (Recommended) Import the external Google Apps Script library with Script ID 1NXwj16pdgcJT-XG5LiWRJyRW604Dj26U4lqgGsJJfOKLum4y9grakXPI into your spreadsheet script

or:

• Import the JavaScript files from the dist/gs directory into your spreadsheet script

In both cases, providing data to the PortfolioAnalytics functions is then accomplished your preferred way:

• Using a wrapper function in your spreadsheet script, directly accessible from your spreadsheet, to which you can provide a standard data range (A1:A99...), e.g.:

function computeUlcerIndexWrapper(iEquityCurveRange) {
  // Convert the input range coming from the spreadsheet into an array
  var aInternalArray = [];
  for (var i=0; i<iEquityCurveRange.length; ++i) {
    aInternalArray.push(iEquityCurveRange[i][0]);
  }
    
  // Compute the index
  var ulcerIndex = PortfolioAnalytics.ulcerIndex(aInternalArray);
  
  // Return it to the spreadsheet
  return ulcerIndex;
}

• Using pure Google Apps Script functions - typically the getRange(...) familly of functions -, optimized for speed, e.g.:

function computeUlcerIndex() {
  // Adapted from https://developers.google.com/apps-script/reference/spreadsheet/sheet#getrangerow-column-numrows
 var ss = SpreadsheetApp.getActiveSpreadsheet();
 var sheet = ss.getSheets()[0];
 var range = sheet.getRange(1, 1, 100); // A1:A100
 var values = range.getValues();
 
 // Convert the above range into an array
 var aInternalArray = [];
 for (var row in values) {
   for (var col in values[row]) {
     aInternalArray.push(values[row][col]);
   }
 }
 
  // Compute the index
  var ulcerIndex = PortfolioAnalytics.ulcerIndex(aInternalArray);
  
  // Do something with it (use it in a computation, write it back to the spreadsheet, etc.)
  ...
}

You can find examples of PortfolioAnalytics usage in this spreadsheet.

Usage inside a browser

If you would like to use PortfolioAnalytics inside a browser you can download its source code and/or its minified source code.

You then just need to include this code in an HTML page, e.g.:

<script src="portfolio_analytics.dist.min.js" type="text/javascript"></script>

To be noted that if the browser is compatible with JavaScript Typed Arrays, you can provide such arrays in input to PortfolioAnalytics for better performances, e.g.:

PortfolioAnalytics.arithmeticReturns(new Float64Array([100.0, 109.75, 111.25]))
// Will output a Float64Array

Usage with Node.js

If you would like to use PortfolioAnalytics with Node.js, you simply need to declare it as a dependency of your project in your package.json file.

Then, this is standard Node.js code, e.g.:

var PortfolioAnalytics = require('portfolio-analytics');
...
var ui = PortfolioAnalytics.ulcerIndex([100, 110, 105, 102, 95]);
// ui == 0.07204222820421435

Examples

Drawdowns related measures

PortfolioAnalytics.maxDrawdown([1, 2, 1]); 
// The maximum drawdown
 
PortfolioAnalytics.drawdownFunction([1, 2, 1]); 
// The drawdown function
 
PortfolioAnalytics.topDrawdowns([1, 2, 1], 1); 
// The top 'n' drawdowns (second largest drawdown, etc.) with their start/end indexes
 
PortfolioAnalytics.ulcerIndex([1, 2, 1]);
// The Ulcer Index
 
PortfolioAnalytics.painIndex([1, 2, 1]);
// The Pain Index, also corresponding to the average of the drawdown function
 
PortfolioAnalytics.conditionalDrawdown([100, 90, 80], 0.5);
// The conditional drawdown

Returns related measures

PortfolioAnalytics.cumulativeReturn([1, 2, 1]); 
// The cumulative return from first to last period
 
PortfolioAnalytics.cagr([1, 2, 1], [new Date("2015-12-31"), new Date("2016-12-31"), new Date("2017-12-31")]); 
// The compound annual growth rate (CAGR) from first to last date
 
PortfolioAnalytics.arithmeticReturns([1, 2, 1]); 
// The arithmetic returns for all periods
 
PortfolioAnalytics.valueAtRisk([1, 2, 1], 0.7);
// The (percent) value at risk

Sharpe ratio related measures

PortfolioAnalytics.sharpeRatio([100, 110, 105, 107.5, 115], [100, 100, 100, 100, 100]); 
// The Sharpe ratio
 
PortfolioAnalytics.biasAdjustedSharpeRatio([100, 110, 105, 107.5, 115], [100, 100, 100, 100, 100]); 
// The Sharpe ratio adjusted for its bias
 
PortfolioAnalytics.doubleSharpeRatio([100, 110, 105, 107.5, 115], [100, 100, 100, 100, 100]); 
// The double Sharpe ratio (i.e., the Sharpe ratio, adjusted for its estimation risk)
 
PortfolioAnalytics.sharpeRatioConfidenceInterval([100, 110, 105, 107.5, 115], [100, 100, 100, 100, 100], 0.05); 
// The confidence interval for the Sharpe ratio (here, at 5% significance level)
 
PortfolioAnalytics.probabilisticSharpeRatio([100, 110, 105, 107.5, 115], [100, 100, 100, 100, 100], 0); 
// The probabilistic Sharpe ratio (i.e., the probability that the Sharpe ratio is greater 
// than a reference Sharpe ratio, here 0)
 
PortfolioAnalytics.minimumTrackRecordLength([100, 110, 105, 107.5, 115], [100, 100, 100, 100, 100], 0.05, 0); 
// The minimum track record length (i.e., the minimal length of the track record of the performance 
// to have statistical confidence, here at 95%, that the Sharpe ratio is greater than a reference Sharpe ratio, here 0)

Returns to variability related measures

PortfolioAnalytics.gainToPainRatio([1, 2, 1]); 
// The gain to pain ratio

How to contribute ?

Fork the projet from Github...

Instal the Grunt dependencies

npm install

Develop...

Compile

• The following command generates the files to be used inside a browser or with Node.js in the dist directory:

grunt deliver

• The following command generates the files to be used in Google Sheets in the dist\gs directory:

grunt deliver-gs

Test

Any of the following two commands run the QUnit unit tests contained in the test directory on the generated file dist\portfolio_analytics.dev.min.js:

npm test

grunt test

Submit a pull-request...

License

MIT License