// 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")

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)

// (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)

  }

}

def investment(portfolio: List[String], years: Range, start_balance: Long): Long = {

  compound_yield(get_deltas(get_prices(portfolio, years)), start_balance, 0)

}

//test cases for the two portfolios given above

}