IN SCALA COULD YOU COMPLETE THE FUNCTIONS: get_january_data, get_first_price, get_prices, get_delta, get_deltas, yearly_yield, compound_yield AND investment 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", "HCP") // (1) The function below takes a stock symbol and a year as arguments. // It should read the corresponding CSV-file and then extract the January // data from the given year. The data should be collected in a list of // strings (one entry for each line in the CSV-file). import io.Source import scala.util._ def get_january_data(symbol: String, year: Int) : List[String] = ??? // (2) From the output of the get_january_data function, the next function // should extract the first line (if it exists) and the corresponding // first trading price in that year with type Option[Double]. If no line // is generated by get_january_data then the result is None; and Some if // there is a price. def get_first_price(symbol: String, year: Int) : Option[Double] = ??? // (3) Complete the function below that obtains all first prices // for the stock symbols from a portfolio (list of strings) and // for the given range of years. The inner lists are for the // stock symbols and the outer list for the years. def get_prices(portfolio: List[String], years: Range) : List[List[Option[Double]]] = ??? // (4) The function below calculates the change factor (delta) between // a price in year n and a price in year n + 1. def get_delta(price_old: Option[Double], price_new: Option[Double]) : Option[Double] = ??? // (5) The next function calculates all change factors for all prices (from a // portfolio). The input to this function are the nested lists created by // get_prices above. def get_deltas(data: List[List[Option[Double]]]) : List[List[Option[Double]]] = ??? // (6) Write a function that given change factors, a starting balance and an index, // calculates the yearly yield, i.e. new balance, according to our dumb investment // strategy. Index points to a year in the data list. def yearly_yield(data: List[List[Option[Double]]], balance: Long, index: Int) : Long = ??? // (7) Write a function compound_yield that calculates the overall balance for a // range of years where in each year the yearly profit is compounded to the new // balances and then re-invested into our portfolio. For this use the function and // results generated under (6). The function investment calls compound_yield // with the appropriate deltas and the first index. def compound_yield(data: List[List[Option[Double]]], balance: Long, index: Int) : Long = ??? def investment(portfolio: List[String], years: Range, start_balance: Long) : Long = ??? //Test cases for the two portfolios given above //println("Real data: " + investment(rstate_portfolio, 1978 to 2019, 100)) //println("Blue data: " + investment(blchip_portfolio, 1978 to 2019, 100))
IN SCALA
COULD YOU COMPLETE THE FUNCTIONS: get_january_data, get_first_price, get_prices, get_delta, get_deltas, yearly_yield, compound_yield AND investment
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", "HCP")
// (1) The function below takes a stock symbol and a year as arguments.
// It should read the corresponding CSV-file and then extract the January
// data from the given year. The data should be collected in a list of
// strings (one entry for each line in the CSV-file).
import io.Source
import scala.util._
def get_january_data(symbol: String, year: Int) : List[String] = ???
// (2) From the output of the get_january_data function, the next function
// should extract the first line (if it exists) and the corresponding
// first trading price in that year with type Option[Double]. If no line
// is generated by get_january_data then the result is None; and Some if
// there is a price.
def get_first_price(symbol: String, year: Int) : Option[Double] = ???
// (3) Complete the function below that obtains all first prices
// for the stock symbols from a portfolio (list of strings) and
// for the given range of years. The inner lists are for the
// stock symbols and the outer list for the years.
def get_prices(portfolio: List[String], years: Range) : List[List[Option[Double]]] = ???
// (4) The function below calculates the change factor (delta) between
// a price in year n and a price in year n + 1.
def get_delta(price_old: Option[Double], price_new: Option[Double]) : Option[Double] = ???
// (5) The next function calculates all change factors for all prices (from a
// portfolio). The input to this function are the nested lists created by
// get_prices above.
def get_deltas(data: List[List[Option[Double]]]) : List[List[Option[Double]]] = ???
// (6) Write a function that given change factors, a starting balance and an index,
// calculates the yearly yield, i.e. new balance, according to our dumb investment
// strategy. Index points to a year in the data list.
def yearly_yield(data: List[List[Option[Double]]], balance: Long, index: Int) : Long = ???
// (7) Write a function compound_yield that calculates the overall balance for a
// range of years where in each year the yearly profit is compounded to the new
// balances and then re-invested into our portfolio. For this use the function and
// results generated under (6). The function investment calls compound_yield
// with the appropriate deltas and the first index.
def compound_yield(data: List[List[Option[Double]]], balance: Long, index: Int) : Long = ???
def investment(portfolio: List[String], years: Range, start_balance: Long) : Long = ???
//Test cases for the two portfolios given above
//println("Real data: " + investment(rstate_portfolio, 1978 to 2019, 100))
//println("Blue data: " + investment(blchip_portfolio, 1978 to 2019, 100))
Trending now
This is a popular solution!
Step by step
Solved in 3 steps with 2 images
