// Advanvced Part 3 about a really dumb investment strategy
//==========================================================

object CW6c {


//two test portfolios

val blchip_portfolio = List("GOOG", "AAPL", "MSFT", "IBM", "FB", "AMZN", "BIDU", "FOOBAR")
val rstate_portfolio = List("PLD", "PSA", "AMT", "AIV", "AVB", "BXP", "CCI", 
                            "DLR", "EQIX", "EQR", "ESS", "EXR", "FRT", "GGP", "HCP") 

// (1) The function below should obtain the first trading price
// for a stock symbol by using the query
//
//    http://ichart.yahoo.com/table.csv?s=<<symbol>>&a=0&b=1&c=<<year>>&d=1&e=1&f=<<year>> 
// 
// and extracting the first January Adjusted Close price in a year.


import io.Source
import scala.util._

def get_january_data(symbol: String, year: Int) : List[String] = 
  Source.fromFile(symbol ++ ".csv")("ISO-8859-1").getLines.toList.filter(_.startsWith(year.toString))


def get_first_price(symbol: String, year: Int) : Option[Double] = {
  val data = Try(Some(get_january_data(symbol, year).head)) getOrElse None 
  data.map(_.split(",").toList(1).toDouble)
}

get_first_price("GOOG", 1980)
get_first_price("GOOG", 2010)
get_first_price("FB", 2014)


// Complete the function below that obtains all first prices
// for the stock symbols from a portfolio for the given
// range of years

def get_prices(portfolio: List[String], years: Range): List[List[Option[Double]]] = 
  for (year <- years.toList) yield
    for (symbol <- portfolio) yield get_first_price(symbol, year)


// test case
val p_fb = get_prices(List("FB"), 2012 to 2014)
val p = get_prices(List("GOOG", "AAPL"), 2010 to 2012)

val tt = get_prices(List("BIDU"), 2004 to 2008)

// (2) The first function below calculates the change factor (delta) between
// a price in year n and a price in year n+1. The second function calculates
// all change factors for all prices (from a portfolio).

def get_delta(price_old: Option[Double], price_new: Option[Double]) : Option[Double] = {
  (price_old, price_new) match {
    case (Some(x), Some(y)) => Some((y - x) / x)
    case _ => None
  }
}

def get_deltas(data: List[List[Option[Double]]]):  List[List[Option[Double]]] =
  for (i <- (0 until (data.length - 1)).toList) yield 
    for (j <- (0 until (data(0).length)).toList) yield get_delta(data(i)(j), data(i + 1)(j))


// test case using the prices calculated above
val d = get_deltas(p)
val ttd = get_deltas(tt)

// (3) Write a function that given change factors, a starting balance and a year
// calculates the yearly yield, i.e. new balanace, according to our dump investment 
// strategy. Another function calculates given the same data calculates the
// compound yield up to a given year. Finally a function combines all 
// calculations by taking a portfolio, a range of years and a start balance
// as arguments.


def yearly_yield(data: List[List[Option[Double]]], balance: Long, year: Int): Long = {
  val somes = data(year).flatten
  val somes_length = somes.length
  if (somes_length == 0) balance
  else {
    val portion: Double = balance.toDouble / somes_length.toDouble
    balance + (for (x <- somes) yield (x * portion)).sum.toLong
  }
}

def compound_yield(data: List[List[Option[Double]]], balance: Long, year: Int): Long = {
  if (year >= data.length) balance else {
    val new_balance = yearly_yield(data, balance, year)
    compound_yield(data, new_balance, year + 1)
  }
}

yearly_yield(d, 100, 0)
compound_yield(d.take(6), 100, 0)

//test case
yearly_yield(d, 100, 0)
yearly_yield(d, 225, 1)
yearly_yield(d, 246, 2)
yearly_yield(d, 466, 3)
yearly_yield(d, 218, 4)

yearly_yield(d, 100, 0)
yearly_yield(d, 125, 1)

def investment(portfolio: List[String], years: Range, start_balance: Long): Long = {
  compound_yield(get_deltas(get_prices(portfolio, years)), start_balance, 0)
}

val one = get_deltas(get_prices(rstate_portfolio, 1978 to 1984))
val two = get_deltas(get_prices(blchip_portfolio, 1978 to 1984))

val one_full = get_deltas(get_prices(rstate_portfolio, 1978 to 2017))
val two_full = get_deltas(get_prices(blchip_portfolio, 1978 to 2017))

one_full.map(_.flatten).map(_.sum).sum
two_full.map(_.flatten).map(_.sum).sum

//test cases for the two portfolios given above

println("Real data: " + investment(rstate_portfolio, 1978 to 1981, 100))
println("Blue data: " + investment(blchip_portfolio, 1978 to 1981, 100))

for (i <- 1978 to 2017) {
  println("Year " + i)
  println("Real data: " + investment(rstate_portfolio, 1978 to i, 100))
  println("Blue data: " + investment(blchip_portfolio, 1978 to i, 100))
}
//1984
//1992
}
