1 // Main Part about a really dumb investment strategy

     2 //======================================================

     3 

     4 object CW6b {

     5 

     6 

     7 //two test portfolios

     8 

     9 val blchip_portfolio = List("GOOG", "AAPL", "MSFT", "IBM", "FB", "AMZN", "BIDU")

    10 val rstate_portfolio = List("PLD", "PSA", "AMT", "AIV", "AVB", "BXP", "CCI", 

    11                             "DLR", "EQIX", "EQR", "ESS", "EXR", "FRT", "HCP") 

    12 

    13 import io.Source

    14 import scala.util._

    15 

    16 // (1) The function below takes a stock symbol and a year as arguments.

    17 //     It should read the corresponding CSV-file and reads the January 

    18 //     data from the given year. The data should be collected in a list of

    19 //     strings for each line in the CSV-file.

    20 

    21 def get_january_data(symbol: String, year: Int) : List[String] = 

    22   Source.fromFile(symbol ++ ".csv")("ISO-8859-1").getLines.toList.filter(_.startsWith(year.toString))

    23 

    24 

    25 //test cases

    26 //blchip_portfolio.map(get_january_data(_, 2018))

    27 //rstate_portfolio.map(get_january_data(_, 2018))

    28 

    29 //get_january_data("GOOG", 1980)

    30 //get_january_data("GOOG", 2010)

    31 //get_january_data("FB", 2014)

    32 

    33 //get_january_data("PLD", 1980)

    34 //get_january_data("EQIX", 2010)

    35 //get_january_data("ESS", 2014)

    36 

    37 

    38 // (2) From the output of the get_january_data function, the next function 

    39 //     should extract the first line (if it exists) and the corresponding

    40 //     first trading price in that year with type Option[Double]. If no line 

    41 //     is generated by get_january_data then the result is None; Some if 

    42 //     there is a price.

    43 

    44 def get_first_price(symbol: String, year: Int) : Option[Double] = {

    45   val data = Try(Some(get_january_data(symbol, year).head)) getOrElse None 

    46   data.map(_.split(",").toList(1).toDouble)

    47 }

    48 

    49 //test cases

    50 //get_first_price("GOOG", 1980)

    51 //get_first_price("GOOG", 2010)

    52 //get_first_price("FB", 2014)

    53 

    54 /*

    55 for (i <- 1978 to 2018) {

    56   println(blchip_portfolio.map(get_first_price(_, i)))

    57 }

    58 

    59 for (i <- 1978 to 2018) {

    60   println(rstate_portfolio.map(get_first_price(_, i)))

    61 }

    62 */ 

    63 

    64 

    65 // (3) Complete the function below that obtains all first prices

    66 //     for the stock symbols from a portfolio (list of strings) and 

    67 //     for the given range of years. The inner lists are for the

    68 //     stock symbols and the outer list for the years.

    69 

    70 def get_prices(portfolio: List[String], years: Range): List[List[Option[Double]]] = 

    71   for (year <- years.toList) yield

    72     for (symbol <- portfolio) yield get_first_price(symbol, year)

    73 

    74 

    75 //test cases

    76 

    77 //println("Task 3 data from Google and Apple in 2010 to 2012")

    78 //val goog_aapl_prices = get_prices(List("GOOG", "AAPL"), 2010 to 2012)

    79 //println(goog_aapl_prices.toString ++ "\n")

    80 

    81 //val p_fb = get_prices(List("FB"), 2012 to 2014)

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

    83 

    84 

    85 // (4) The function below calculates the change factor (delta) between

    86 //     a price in year n and a price in year n + 1. 

    87 

    88 def get_delta(price_old: Option[Double], price_new: Option[Double]) : Option[Double] = {

    89   (price_old, price_new) match {

    90     case (Some(x), Some(y)) => Some((y - x) / x)

    91     case _ => None

    92   }

    93 }

    94 

    95 

    96 // (5) The next function calculates all change factors for all prices (from a 

    97 //     portfolio). The input to this function are the nested lists created by 

    98 //     get_prices above.

    99 

   100 def get_deltas(data: List[List[Option[Double]]]):  List[List[Option[Double]]] =

   101   for (i <- (0 until (data.length - 1)).toList) yield 

   102     for (j <- (0 until (data(0).length)).toList) yield get_delta(data(i)(j), data(i + 1)(j))

   103 

   104 

   105 

   106 // test case using the prices calculated above

   107 

   108 //println("Task 5 change prices from Google and Apple in 2010 and 2011")

   109 //val goog_aapl_deltas = get_deltas(goog_aapl_prices)

   110 //println(goog_aapl_deltas.toString ++ "\n")

   111 

   112 //val ttd = get_deltas(tt)

   113 

   114 

   115 // (6) Write a function that given change factors, a starting balance and an index,

   116 //     calculates the yearly yield, i.e. new balance, according to our dumb investment 

   117 //     strategy. Index points to a year in the data list.

   118 

   119 def yearly_yield(data: List[List[Option[Double]]], balance: Long, index: Int): Long = {

   120   val somes = data(index).flatten

   121   val somes_length = somes.length

   122   if (somes_length == 0) balance

   123   else {

   124     val portion: Double = balance.toDouble / somes_length.toDouble

   125     balance + (for (x <- somes) yield (x * portion)).sum.toLong

   126   }

   127 }

   128 

   129 // test case using the deltas calculated above

   130 //println("Task 6 yield from Google and Apple in 2010 with  balance 100")

   131 

   132 //val d0 = goog_aapl_deltas(0)(0)

   133 //val d1 = goog_aapl_deltas(0)(1)

   134 //println(s"50 * ${d0.get} + 50 * ${d1.get} = ${50.toDouble * d0.get + 50.toDouble * d1.get}")

   135 

   136 

   137 //val goog_aapl_yield = yearly_yield(goog_aapl_deltas, 100, 0)

   138 //println("Rounded yield: " ++ goog_aapl_yield.toString ++ "\n")

   139 

   140 

   141 //yearly_yield(get_prices(rstate_portfolio, 2016 to 2018), 100, 2) 

   142 //get_prices(rstate_portfolio, 2016 to 2018)(2).flatten.sum

   143 

   144 

   145 // (7) Write a function compound_yield that calculates the overall balance for a 

   146 //     range of years where in each year the yearly profit is compounded to the new 

   147 //     balances and then re-invested into our portfolio. For this use the function and 

   148 //     results generated under (6). The function investment calls compound_yield

   149 //     with the appropriate deltas and the first index.

   150 

   151 

   152 def compound_yield(data: List[List[Option[Double]]], balance: Long, index: Int): Long = {

   153   if (index >= data.length) balance else {

   154     val new_balance = yearly_yield(data, balance, index)

   155     compound_yield(data, new_balance, index + 1)

   156   }

   157 }

   158 

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

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

   161 }

   162 

   163 

   164 

   165 //test cases for the two portfolios given above

   166 

   167 //println("Real data: " + investment(rstate_portfolio, 1978 to 2019, 100))

   168 //println("Blue data: " + investment(blchip_portfolio, 1978 to 2019, 100))

   169 

   170 }

   171 

   172 

   173