trading_engine_buy_testing.R

# We will run throughout 21,24,31,35,39
library(binhf)
library(parallel)
library(foreach)
library(doMC)
library(pbapply)
library(caret)
library(Metrics)
library(methods)
library(plyr)

load("~/Dev/ORF 474/hw2/combined/amzn/20150301_AMZN.RData")
Trades <- Trades[,-c(9:13)] # Removes any junk info we don't need
allDays <- unique(Trades$Date)

first_buy_val_day <- readRDS("allTrain_Day_9_Buy_fefs")
glmnetFitBuy <- readRDS("glmnetFitBuy")

# INITIATE
# Naive Algo follows asks, trades 100 shares if there was a trade at the ask
naiveAlgo <- function(currentPrice_p, currentAsk_p)
{
  if(currentPrice_p >= currentAsk_p)
  {
    return(100)
  } else {
    return(-1)
  }
}

allFinalVWAP_ME <- c()
allFinalVWAP_Market <- c()
allFinalObjectives <- c()
allFinalPovRates <- c()

runSimulation <- function(tradingDay)
{
miniTrades_1 <- Trades[which(Trades$Date == allDays[tradingDay]),]
miniTrades_1$Exchange <- NULL
miniTrades_1$Sym <- NULL
miniTrades_1$SYM_SUFFIX <- NULL
miniTrades_1$Cond <- NULL
miniTrades_1$QU_COND <- NULL

currMarketVWAP <- 0
currMarketVWAP_top <- 0
currMarketVWAP_bottom <- 0

currMyVWAP <- 0
currMyVWAP_top <- 0
currMyVWAP_bottom <- 0

currPOV <- 0
totalBuyVolObs <- 0
currObjective <- 0
currentState <- 0
numSharesToTrade <- 0

dfOfMyTransactions <- data.frame(matrix(ncol = 2))
colnames(dfOfMyTransactions) <- c("Price", "Volume")
dfOfMyTransactions_counter = 1;

for (i in c(1:nrow(miniTrades_1))) {
  currentRow <- miniTrades_1[i,]
  currentTime <- miniTrades_1[i,2]
  currentShares <- miniTrades_1[i,3]
  currentPrice <- miniTrades_1[i,4]
  currentAsk <- miniTrades_1[i,7]
  currentSign <- miniTrades_1[i,9]

  if(currentState == 1)
  {
    dfOfMyTransactions[dfOfMyTransactions_counter,1] = currentAsk
    dfOfMyTransactions[dfOfMyTransactions_counter,2] = numSharesToTrade
    dfOfMyTransactions_counter = dfOfMyTransactions_counter + 1
    currMyVWAP_top = currMyVWAP_top + currentAsk*numSharesToTrade
    currMyVWAP_bottom = currMyVWAP_bottom + numSharesToTrade
    currMyVWAP = currMyVWAP_top/currMyVWAP_bottom
    currPOV = currPOV + numSharesToTrade
    currentState = 0;
  }
  
  currMarketVWAP_top = currMarketVWAP_top + currentPrice*currentShares
  currMarketVWAP_bottom = currMarketVWAP_bottom + currentShares
  currMarketVWAP = currMarketVWAP_top/currMarketVWAP_bottom
  currObjective = max(currMyVWAP - currMarketVWAP, 0)
  
  if (currentSign == 1)
  {
    totalBuyVolObs = totalBuyVolObs + currentShares
  }
  
  # Check if over-participating
  if (currPOV - .1*totalBuyVolObs < 800)
  {
    result = naiveAlgo(currentPrice_p = currentPrice, currentAsk_p = currentAsk)
    if (result > 0)
    {
      currentState = 1
      numSharesToTrade = result
    } else {
      currentState = 0
    }
  }
  
  if (.1*totalBuyVolObs - currPOV > 800){
    currentState = 1
    print("BREAKER EXECUTED")
    numSharesToTrade = 300
  }
}

# Final Reconcilliation if overbought or oversold
if(currPOV > .1*totalBuyVolObs)
{
  dfOfMyTransactions[dfOfMyTransactions_counter,1] = miniTrades_1[i,5]
  dfOfMyTransactions[dfOfMyTransactions_counter,2] = currPOV - .1*totalBuyVolObs
  currMyVWAP_top = currMyVWAP_top + miniTrades_1[i,5]*(currPOV - .1*totalBuyVolObs)
  currMyVWAP_bottom = currMyVWAP_bottom + (currPOV - .1*totalBuyVolObs)
  currMyVWAP = currMyVWAP_top/currMyVWAP_bottom
  currPOV = currPOV - (currPOV - .1*totalBuyVolObs)
  currObjective = max(currMyVWAP - currMarketVWAP, 0)
} else if (currPOV < .1*totalBuyVolObs) {
  dfOfMyTransactions[dfOfMyTransactions_counter,1] = currentAsk
  dfOfMyTransactions[dfOfMyTransactions_counter,2] = .1*totalBuyVolObs - currPOV
  currMyVWAP_top = currMyVWAP_top + currentAsk*(.1*totalBuyVolObs - currPOV)
  currMyVWAP_bottom = currMyVWAP_bottom + (.1*totalBuyVolObs - currPOV)
  currMyVWAP = currMyVWAP_top/currMyVWAP_bottom
  currPOV = currPOV + (.1*totalBuyVolObs - currPOV)
  currObjective = max(currMyVWAP - currMarketVWAP, 0)
}

print(paste0("Our Final VWAP: ", currMyVWAP))
print(paste0("Market's Final VWAP: ", currMarketVWAP))
print(paste0("Objective Function: ", currObjective))
print(paste0("Our Final POV rate: ", currPOV/totalBuyVolObs))

return(c(currMyVWAP, currMarketVWAP, currObjective, currPOV/totalBuyVolObs))
}

listOfDays <- c(21, 24, 31, 35)
for(d in listOfDays)
{
  print(paste0("On day ", d))
  res <- runSimulation(d)
  allFinalVWAP_ME <- c(allFinalVWAP_ME, res[1])
  allFinalVWAP_Market <- c(allFinalVWAP_Market, res[2])
  allFinalObjectives <- c(allFinalObjectives, res[3])
  allFinalPovRates <- c(allFinalPovRates, res[4])
}

print("Results of Simulation: ")
print(paste0("Our Final Simulation Average VWAP: ", mean(allFinalVWAP_ME)))
print(paste0("Market's Final Simulation Average VWAP: ", mean(allFinalVWAP_Market)))
print(paste0("Simulation Average Objective Function: ", mean(allFinalObjectives)))