--- a/marking1/drumb.scala~ Thu Mar 08 12:32:50 2018 +0000
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,151 +0,0 @@
-// 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)
-
-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 q1 = get_deltas(get_prices(List("GOOG", "AAPL", "BIDU"), 2000 to 2017))
-yearly_yield(q1, 100, 0)
-yearly_yield(q1, 100, 1)
-yearly_yield(q1, 100, 2)
-yearly_yield(q1, 100, 3)
-yearly_yield(q1, 100, 4)
-yearly_yield(q1, 100, 5)
-yearly_yield(q1, 100, 6)
-
-investment(List("GOOG", "AAPL", "BIDU"), 2004 to 2017, 100)
-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 2017, 100))
-//println("Blue data: " + investment(blchip_portfolio, 1978 to 2017, 100))
-
-for (i <- 2000 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))
- println("test: " + investment(List("GOOG", "AAPL", "BIDU"), 2000 to i, 100))
-}
-
-
-*/
-//1984
-//1992
-}