1 // Main Part 1 about a really dumb investment strategy

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

     3 

     4 object M1 {

     5 

     6 //two test portfolios

     7 

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

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

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

    11 

    12 

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

    14 //     It should read the corresponding CSV-file and then extract the January 

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

    16 //     strings (one entry for each line in the CSV-file).

    17 

    18 import io.Source

    19 import scala.util._

    20 

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

    22 

    23 

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

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

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

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

    28 //     there is a price.

    29 

    30 

    31 def get_first_price(symbol: String, year: Int) : Option[Double] = ???

    32 

    33 

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

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

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

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

    38 

    39 

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

    41 

    42 

    43 

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

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

    46 

    47 def get_delta(price_old: Option[Double], price_new: Option[Double]) : Option[Double] = ???

    48 

    49 

    50 

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

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

    53 //     get_prices above.

    54 

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

    56 

    57 

    58 

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

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

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

    62 

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

    64 

    65 

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

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

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

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

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

    71 

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

    73 

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

    75 

    76 

    77 

    78 

    79 //Test cases for the two portfolios given above

    80 

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

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

    83 

    84 

    85 }