Quant-Trading-Introduction

CODE:
# FIRST CODE OF MY LIFE=========================================================
# TURTLE TRADER ORIGINAL (SPY)
# TREND FOLLOWING SYSTEM
# DADOS DESDE 2023
# CAPITAL INICIAL = $1000
# 10% DO PATRIMÔNIO POR TRADE
# =========================================================

# =========================================================
# BIBLIOTECAS
# =========================================================

library(quantmod)
library(TTR)
library(PerformanceAnalytics)
library(xts)

# =========================================================
# DOWNLOAD DOS DADOS
# =========================================================

getSymbols(
  "SPY",
  src = "yahoo",
  from = "2023-01-01"
)

data <- na.omit(SPY)

# =========================================================
# VISUALIZAR DADOS
# =========================================================

View(data)

# =========================================================
# PARÂMETROS
# =========================================================

# Canal de entrada
ChannelUp  <- 20
ChannelDn  <- 20

# Canal de saída
LongExit   <- 10
ShortExit  <- 10

# Canal fail-safe
FailsafeUp <- 55
FailsafeDn <- 55

# ATR
ATRParam <- 20

# Tick mínimo
Tick <- 0.01

# Capital inicial
initialCapital <- 1000

# Percentual do patrimônio usado por trade
riskPerTrade <- 0.10

# =========================================================
# INDICADORES
# =========================================================

# Breakouts
channelHigh <- runMax(Hi(data), ChannelUp)

channelLow <- runMin(Lo(data), ChannelDn)

# Fail-safe
failsafeHigh <- runMax(Hi(data), FailsafeUp)

failsafeLow <- runMin(Lo(data), FailsafeDn)

# Exits
longExitLine <- runMin(Lo(data), LongExit)

shortExitLine <- runMax(Hi(data), ShortExit)

# ATR ("N" do Turtle)
N <- ATR(HLC(data), n = ATRParam)$atr

# =========================================================
# VARIÁVEIS
# =========================================================

n <- NROW(data)

position <- rep(0, n)

units <- rep(0, n)

strategyRet <- rep(0, n)

# Equity inicializado corretamente
equity <- rep(initialCapital, n)

# =========================================================
# ESTADO DA ESTRATÉGIA
# =========================================================

currentPos <- 0

currentUnits <- 0

currentEntry <- NA

shares <- 0

# =========================================================
# START INDEX
# =========================================================

startIndex <- max(
  ChannelUp,
  ChannelDn,
  LongExit,
  ShortExit,
  FailsafeUp,
  FailsafeDn,
  ATRParam
) + 1

# =========================================================
# LOOP PRINCIPAL
# =========================================================

for(i in startIndex:n)
{
  
  # =====================================================
  # PREÇOS
  # =====================================================
  
  closePrice <- as.numeric(Cl(data)[i])
  
  highPrice <- as.numeric(Hi(data)[i])
  
  lowPrice <- as.numeric(Lo(data)[i])
  
  atr <- as.numeric(N[i])
  
  # Equity anterior
  currentEquity <- equity[i-1]
  
  # =====================================================
  # CANAIS
  # =====================================================
  
  # Breakouts
  L1 <- as.numeric(channelHigh[i-1])
  
  S1 <- as.numeric(channelLow[i-1])
  
  # Fail-safe
  FU <- as.numeric(failsafeHigh[i-1])
  
  FD <- as.numeric(failsafeLow[i-1])
  
  # Exits
  LE <- as.numeric(longExitLine[i-1]) - Tick
  
  SE <- as.numeric(shortExitLine[i-1]) + Tick
  
  # =====================================================
  # PIRAMIDAGEM
  # =====================================================
  
  # Long
  L2 <- L1 + 0.5 * atr
  
  L3 <- L1 + 1.0 * atr
  
  L4 <- L1 + 1.5 * atr
  
  # Short
  S2 <- S1 - 0.5 * atr
  
  S3 <- S1 - 1.0 * atr
  
  S4 <- S1 - 1.5 * atr
  
  # =====================================================
  # ENTRADAS
  # =====================================================
  
  if(currentPos == 0)
  {
    
    # Usa 10% do patrimônio
    allocation <- currentEquity * riskPerTrade
    
    # =================================================
    # LONG ENTRY
    # =================================================
    
    if(highPrice >= L1)
    {
      currentPos <- 1
      
      currentEntry <- L1
      
      currentUnits <- 1
      
      # Fractional shares
      shares <- allocation / currentEntry
    }
    
    # =================================================
    # SHORT ENTRY
    # =================================================
    
    else if(lowPrice <= S1)
    {
      currentPos <- -1
      
      currentEntry <- S1
      
      currentUnits <- 1
      
      # Fractional shares
      shares <- allocation / currentEntry
    }
  }
  
  # =====================================================
  # PIRAMIDAGEM LONG
  # =====================================================
  
  if(currentPos == 1)
  {
    
    if(currentUnits == 1 && highPrice >= L2)
      currentUnits <- 2
    
    if(currentUnits == 2 && highPrice >= L3)
      currentUnits <- 3
    
    if(currentUnits == 3 && highPrice >= L4)
      currentUnits <- 4
  }
  
  # =====================================================
  # PIRAMIDAGEM SHORT
  # =====================================================
  
  if(currentPos == -1)
  {
    
    if(currentUnits == 1 && lowPrice <= S2)
      currentUnits <- 2
    
    if(currentUnits == 2 && lowPrice <= S3)
      currentUnits <- 3
    
    if(currentUnits == 3 && lowPrice <= S4)
      currentUnits <- 4
  }
  
  # =====================================================
  # STOPS LONG
  # =====================================================
  
  if(currentPos == 1)
  {
    
    stopPrice <- currentEntry - 2 * atr
    
    if(lowPrice <= stopPrice || lowPrice <= LE)
    {
      currentPos <- 0
      
      currentUnits <- 0
      
      currentEntry <- NA
      
      shares <- 0
    }
  }
  
  # =====================================================
  # STOPS SHORT
  # =====================================================
  
  if(currentPos == -1)
  {
    
    stopPrice <- currentEntry + 2 * atr
    
    if(highPrice >= stopPrice || highPrice >= SE)
    {
      currentPos <- 0
      
      currentUnits <- 0
      
      currentEntry <- NA
      
      shares <- 0
    }
  }
  
  # =====================================================
  # RETORNO DIÁRIO
  # =====================================================
  
  ret <- as.numeric(
    dailyReturn(Cl(data))[i]
  )
  
  # =====================================================
  # PNL
  # =====================================================
  
  pnl <- ret *
    currentPos *
    currentUnits *
    shares *
    closePrice
  
  # =====================================================
  # SALVA RETORNO
  # =====================================================
  
  strategyRet[i] <- pnl
  
  # =====================================================
  # ATUALIZA EQUITY
  # =====================================================
  
  equity[i] <- equity[i-1] + pnl
  
  # =====================================================
  # SALVA ESTADO
  # =====================================================
  
  position[i] <- currentPos
  
  units[i] <- currentUnits
}

# =========================================================
# CONVERTE PARA XTS
# =========================================================

strategyRet <- xts(
  strategyRet,
  order.by = index(data)
)

strategyRet[is.na(strategyRet)] <- 0

equity <- xts(
  equity,
  order.by = index(data)
)

# =========================================================
# RETORNOS %
# =========================================================

returnsPct <- Return.calculate(equity)

returnsPct[is.na(returnsPct)] <- 0

# =========================================================
# MÉTRICAS
# =========================================================

cat("\n==============================\n")
cat("CAPITAL FINAL\n")
cat("==============================\n")

print(last(equity))

cat("\n==============================\n")
cat("RETORNO TOTAL (%)\n")
cat("==============================\n")

totalReturn <- (
  as.numeric(last(equity)) /
    initialCapital - 1
) * 100

print(round(totalReturn, 2))

cat("\n==============================\n")
cat("ANNUALIZED RETURNS\n")
cat("==============================\n")

print(
  table.AnnualizedReturns(
    returnsPct
  )
)

cat("\n==============================\n")
cat("SHARPE RATIO\n")
cat("==============================\n")

print(
  SharpeRatio.annualized(
    returnsPct
  )
)

cat("\n==============================\n")
cat("MAX DRAWDOWN\n")
cat("==============================\n")

print(
  maxDrawdown(
    returnsPct
  )
)

# =========================================================
# EQUITY CURVE
# =========================================================

charts.PerformanceSummary(
  returnsPct
)

# =========================================================
# GRÁFICO
# =========================================================

chartSeries(
  data,
  theme = chartTheme("white"),
  name = "Turtle Trader - SPY",
  TA = NULL
)

# Canal breakout
addTA(
  channelHigh,
  col = "green"
)

addTA(
  channelLow,
  col = "red"
)

# Fail-safe
addTA(
  failsafeHigh,
  col = "blue"
)

addTA(
  failsafeLow,
  col = "purple"
)

There are several books on quantitative trading that are well worth reading. The books by Perry Kaufmann, Brent Penfold, Robert Carver, and Laurens Bensdorp, for example, would be a good place to start. You can also find videos on YouTube by these authors and others who haven’t written books—such as Adrian Reid or Martyn Tinsley—on the subject. This is merely an illustrative overview of a few “knowledge providers” in the field of quantitative system development. The world of quants is diverse, but it's definitely worth diving into.

Looks like R code, yes?

Yes, my first code

Below is a very informative link that cites excellent references for learning more about quantitative trading. I would scroll down towards the bottom of this link to reach all the useful references. I think you'll find them interesting, especially if you're into statistical analysis.
https://www.quantstart.com/articles/Self-Study-Plan-for-Becoming-a-Quantitative-Trader-Part-I/