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library(RJSONIO)
library(xts)

Quandl <- function(code, env = .GlobalEnv, type = c('raw', 'ts', 'zoo', 'xts'), start_date, end_date, transformation = c('', 'diff', 'rdiff', 'normalize', 'cumul'), collapse = c('', 'weekly', 'monthly', 'quarterly', 'annual'), rows, authcode = Quandl.auth()) {
  
  ## Flag to indicate frequency change due to collapse
  freqflag = FALSE
  
  # remove everything before the "/" for assigning the symbols to variable names
  sym.names <- gsub(".*/", "", code)

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Quandl <- function(Symbols, env=.GlobalEnv, from="2000-01-01", to=Sys.Date(), auth=NULL) {
  # Function to pull data using the quandl API
  # Returns an xts object
  # Input Args
  # Symbols     : character vector of quandl codes of the datasets you want to retrieve
  # from        : character vector of the start date in yyyy-mm-dd
  # to          : character vector of the end date in yyyy-mm-dd
  # auth        : authentication toke for quandl API access www.quandl.com/api
  
  # Base url for the quandl api

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library(shiny)
library(PerformanceAnalytics)
data(managers)


# Define server logic required to plot relative performance
shinyServer(function(input, output) {
  
  # Use charts.PerformanceSummary from Performance Analytics package
  # to generate a performance summary plot

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# Backtest of ETF Replay Ranking Algorithm

# clear the workspace
rm(list=ls())

# step-by-step example of ETF Replay Ranking Algorithm

##### etfReplayRank Function #####
# we can use the same step-by-step approach outlined above to write a function
# to rank instruments based on ETF Replay

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# Ranking Algorithm for ETF Replay

# Rank based on 3 factors
# 1. ReturnA    (ret1)
# 2. ReturnB    (ret2)
# 3. Volatility (vol)

# Returns are ranked from high to low
# Volatility is ranked from low to high

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/**
 * @title Using Sugar Function diff()
 * @author Ross Bennett
 * @license GPL (>= 2)
 * @tags sugar, diff
 * @summary Illustrates the use of sugar function diff()
 */

/**
 * The sugar function diff() computes the difference of consecutive elements (i.e. lag = 1) 

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/**
 * @title Using Sugar Function cumsum()
 * @author Ross Bennett
 * @license GPL (>= 2)
 * @tags sugar cumsum
 * @summary Demonstrates different ways to compute the cumulative
 *   sum of a vector and illustrates the use of sugar function cumsum().
 */
 
 #include <Rcpp.h>