# HG changeset patch # User Christian Urban # Date 1520512389 0 # Node ID fb229ff1740947e081148acac6f7089ce237c7e2 # Parent 4c9497ab5caa51375ab3d60a250b318ac99a8e3f error corrected diff -r 4c9497ab5caa -r fb229ff17409 marking1/drumb.scala~ --- 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=<>&a=0&b=1&c=<>&d=1&e=1&f=<> -// -// 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 -}