# Get SPY from yahoo
getSymbols("SPY",
           from ="2000-01-01",
           to ="2016-06-30",
           src ="yahoo",
           adjust = T)
# Plot the closing price of SPY
plot(Cl(SPY))

# Plot the closing prices of SPY
plot(Cl(SPY))
# Add a 200-day SMA using lines()
lines(SMA(Cl(SPY), n = 200), col ="red")

# Load the quantstrat package
library(quantstrat)
# Create initdate, from, and to strings
initdate <- "1999-01-01"
from <- "2003-01-01"
to <- "2015-12-31"
# Set the timezone to UTC
Sys.setenv(TZ="UTC")
# Set the currency to USD
currency("USD")

# Load the quantmod package
library(quantmod)
# Retrieve SPY from yahoo
getSymbols("SPY",from = from, to=to, src="yahoo", adjust = T)
# Use stock() to initialize SPY and set currency to USD
stock("SPY",currency="USD")

# Define your trade size and initial equity
tradesize <- 100000
initeq <- 100000
# Define the names of your strategy, portfolio and account
strategy.st <- "firststrat"
portfolio.st <- "firststrat"
account.st <- "firststrat"
# Remove the existing strategy if it exists
rm.strat(strategy.st)

# Initialize the portfolio
initPortf(portfolio.st, symbols ="SPY", initDate =initdate, currency ="USD")
# Initialize the account
initAcct(account.st, portfolios =portfolio.st, initDate =initdate, currency = "USD", initEq =initeq)
# Initialize the orders
initOrders(portfolio.st, initDate =initdate)
# Store the strategy
strategy(strategy.st, store = T)

# Create a 200-day SMA
spy_sma <- SMA(Cl(SPY),200)
plot.xts(spy_sma)
# Create an RSI with a 3-day lookback period
spy_rsi <- RSI(Cl(SPY),3)
spy_rsi

# Plot the closing prices of SPY
plot(Cl(SPY));lines(SMA(Cl(SPY), n =200), col ="red")

# Plot the closing price of SPY
plot(Cl(SPY))
# Plot the RSI 2
plot(RSI(Cl(SPY),2))

# Add a 200-day SMA indicator to strategy.st
add.indicator(strategy = strategy.st,
              # Add the SMA function
              name = "SMA",
              # Create a lookback period
              arguments = list(x = quote(Cl(mktdata)), n = 200),
              label = "SMA200")

# Add a 50-day SMA indicator to strategy.st
add.indicator(strategy = strategy.st,
              # Add the SMA function
              name = "SMA",
              # Create a lookback period
              arguments = list(x =quote(Cl(mktdata)), n = 50),
              label = "SMA50")

plot.xts(Cl(SPY));lines(SMA(Cl(SPY),200),col="red");lines(SMA(Cl(SPY),50),col="blue")

# Add an RSI 3 indicator to strategy.st
add.indicator(strategy = strategy.st,
              # Add the RSI 3 function
              name ="RSI",
              # Create a lookback period
              arguments = list(x=quote(Cl(mktdata)),n=3),
              label ="RSI_3")

plot.xts(Cl(SPY));lines(SMA(Cl(SPY),200))
plot.xts(RSI(Cl(SPY),200));lines(SMA(RSI(Cl(SPY),200),50),col="red")

# Declare the DVO function
DVO <- function(HLC, navg =2, percentlookback =126) {
  # Compute the ratio between closing prices to the average of high and low
  ratio <- Cl(HLC)/((Hi(HLC) + Lo(HLC))/2)
  # Smooth out the ratio outputs using a moving average
  avgratio <- SMA(ratio, n =navg)
  # Convert ratio into a 0-100 value
  out <- runPercentRank(avgratio, n = percentlookback, exact.multiplier = 1) * 100
  colnames(out) <- "DVO"
  return(out)
}

# Add the DVO indicator to the strategy
add.indicator(strategy = strategy.st, name = "DVO",
              arguments = list(HLC = quote(HLC(mktdata)), navg =2, percentlookback =126),
              label = "DVO_2_126")

# Use applyIndicators to test indicators
test <- applyIndicators(strategy =strategy.st, mktdata = OHLC(SPY))
head(test)
# Subset data between Sep. 1 and Sep. 5 of 2013
test_subset <- test["2013-09-1/2013-09-5"]

plot.xts(Cl(SPY));lines(test)
plot.xts(test)
plot.xts(test_subset)

# A sigComparison which specifies that SMA50 must be greater than SMA200
add.signal(strategy.st, name = "sigComparison",
           # I'm are interested in the relationship between the SMA50 and the SMA200
           arguments = list(columns = c("SMA50", "SMA200"),
                            # Particularly, I'm are interested when the SMA50 is greater than the SMA200
                            relationship = "gt"),
           label = "longfilter")

# Add a sigCrossover which specifies that the SMA50 is less than the SMA200
add.signal(strategy.st, name = "sigCrossover",
           # We're interested in the relationship between the SMA50 and the SMA200
           arguments = list(columns = c("SMA50", "SMA200"),
                            # The relationship is that the SMA50 crosses under the SMA200
                            relationship = "lt"),
           label = "filterexit")

# Implement a sigThreshold which specifies that DVO_2_126 must be less than 2
add.signal(strategy.st, name = "sigThreshold",
           # Use the DVO_2_126 column
           arguments = list(column = "DVO_2_126",
                            # The threshold is 20
                            threshold =20,
                            # I want the oscillator to be under this value
                            relationship = "lt",
                            # I'm interested in every instance that the oscillator is less than 20
                            cross =F),
           label = "longthreshold")

# A sigThreshold signal that specifies that DVO_2_126 must cross above 80
add.signal(strategy.st, name = "sigThreshold",
           # Reference the column of DVO_2_126
           arguments = list(column = "DVO_2_126",
                            # Set a threshold of 80
                            threshold =80,
                            # The oscillator must be greater than 80
                            relationship = "gt",
                            # We are interested only in the cross
                            cross =TRUE),
           label = "thresholdexit")

# Create dataset: test
test_init <- applyIndicators(strategy.st, mktdata = OHLC(SPY))
test <- applySignals(strategy = strategy.st, mktdata =test_init)

# Add a sigFormula signal
add.signal(strategy.st, name = "sigFormula",
           arguments = list(formula = "longfilter & longthreshold",
                            cross = T),
           label = "longentry")

add.rule(strategy.st, name = "ruleSignal",
         arguments = list(sigcol = "filterexit", sigval = TRUE, orderqty = "all",
                        ordertype = "market", orderside = "long",
                        replace = FALSE, prefer = "Open"),
         type = "exit")

add.rule(strategy.st, name = "ruleSignal",
         arguments = list(sigcol = "thresholdexit", sigval = TRUE, orderqty = "all",
                        ordertype = "market", orderside = "long",
                        replace = FALSE, prefer = "Open"),
         type = "exit")

# Create an entry rule of 1 share when all conditions line up to enter into a position
add.rule(strategy.st, name = "ruleSignal",
         arguments=list(sigcol = "longentry",
                        sigval =T,
                        orderqty =1,
                        ordertype = "market",
                        orderside = "long",
                        replace =F,
                        prefer = "Open"),
         type = "enter")

# Add a rule that uses an osFUN to size an entry position
add.rule(strategy = strategy.st, name = "ruleSignal",
         arguments = list(sigcol = "longentry", sigval = TRUE, ordertype = "market", orderside = "long", replace = FALSE, prefer = "Open",
                          # Use the osFUN called osMaxDollar
                          osFUN =osMaxDollar,
                          # The tradeSize argument should be equal to tradesize (defined earlier)
                          tradeSize =tradesize,
                          # The maxSize argument should be equal to tradesize as well
                          maxSize =tradesize),
         type = "enter")

# Use applyStrategy() to apply the strategy.
end <- applyStrategy(strategy =strategy.st, portfolios =portfolio.st)
# Update your portfolio (portfolio.st)
updatePortf(portfolio.st)
daterange <- time(getPortfolio(portfolio.st)$summary)[-1]
# Update your account (account.st)
updateAcct(account.st, daterange)
updateEndEq(account.st)
tradeStats(portfolio.st)

# Use chart.Posn to view system's performance on SPY
chart.Posn(Portfolio =portfolio.st, Symbol = "SPY")

# Compute the SMA50
sma50 <- SMA(x = Cl(SPY), n =50)
# Compute the SMA200
sma200 <- SMA(x = Cl(SPY), n =200)
# Compute the DVO_2_126 with an navg of 2 and a percentlookback of 126
dvo <- DVO(HLC = HLC(SPY), navg =2, percentlookback =126)
# Recreate the chart.Posn of the strategy from the previous exercise
chart.Posn(Portfolio=portfolio.st,Symbol="SPY")
# Overlay the SMA50 on your plot as a blue line
add_TA(sma50, on =1, col = "blue")
# Overlay the SMA200 on your plot as a red line
add_TA(sma200, on =1, col = "red")
# Add the DVO_2_126 to the plot in a new window
add_TA(dvo,2)

# Get instrument returns
instrets <- PortfReturns(account.st)
# Compute Sharpe ratio from returns
SharpeRatio.annualized(instrets, geometric = FALSE)