1 // Main Part 1 about a really dumb investment strategy |
1 // Main Part 1 about a really dumb investment strategy |
2 //===================================================== |
2 //=================================================== |
3 |
3 |
4 |
4 object M1 { |
5 // generate jar with |
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6 // > scala -d drumb.jar drumb.scala |
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7 |
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8 |
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9 object M1 { |
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10 |
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11 |
5 |
12 //two test portfolios |
6 //two test portfolios |
13 |
7 |
14 val blchip_portfolio = List("GOOG", "AAPL", "MSFT", "IBM", "FB", "AMZN", "BIDU") |
8 val blchip_portfolio = List("GOOG", "AAPL", "MSFT", "IBM", "FB", "AMZN", "BIDU") |
15 val rstate_portfolio = List("PLD", "PSA", "AMT", "AIV", "AVB", "BXP", "CCI", |
9 val rstate_portfolio = List("PLD", "PSA", "AMT", "AIV", "AVB", "BXP", "CCI", |
16 "DLR", "EQIX", "EQR", "ESS", "EXR", "FRT", "HCP") |
10 "DLR", "EQIX", "EQR", "ESS", "EXR", "FRT", "HCP") |
17 |
11 |
18 import io.Source |
12 import io.Source |
19 import scala.util._ |
13 import scala.util._ |
20 |
14 |
21 // (1) The function below takes a stock symbol and a year as arguments. |
15 // ADD YOUR CODE BELOW |
22 // It should read the corresponding CSV-file and reads the January |
16 //====================== |
23 // data from the given year. The data should be collected in a list of |
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24 // strings for each line in the CSV-file. |
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25 |
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26 def get_january_data(symbol: String, year: Int) : List[String] = |
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27 Source.fromFile(symbol ++ ".csv")("ISO-8859-1").getLines().toList.filter(_.startsWith(year.toString)) |
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28 |
17 |
29 |
18 |
30 //test cases |
19 // (1) |
31 //blchip_portfolio.map(get_january_data(_, 2018)) |
20 def get_january_data(symbol: String, year: Int) : List[String] = { |
32 //rstate_portfolio.map(get_january_data(_, 2018)) |
21 Try(Source.fromFile(s"${symbol}.csv").getLines.toList.filter(_.startsWith(year.toString))).getOrElse(Nil) |
33 |
22 } |
34 //get_january_data("GOOG", 1980) |
23 // (2) |
35 //get_january_data("GOOG", 2010) |
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36 //get_january_data("FB", 2014) |
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37 |
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38 //get_january_data("PLD", 1980) |
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39 //get_january_data("EQIX", 2010) |
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40 //get_january_data("ESS", 2014) |
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41 |
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42 |
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43 // (2) From the output of the get_january_data function, the next function |
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44 // should extract the first line (if it exists) and the corresponding |
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45 // first trading price in that year with type Option[Double]. If no line |
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46 // is generated by get_january_data then the result is None; Some if |
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47 // there is a price. |
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48 |
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49 def get_first_price(symbol: String, year: Int) : Option[Double] = { |
24 def get_first_price(symbol: String, year: Int) : Option[Double] = { |
50 val data = Try(Some(get_january_data(symbol, year).head)) getOrElse None |
25 val list = get_january_data(symbol, year) |
51 data.map(_.split(",").toList(1).toDouble) |
26 if (list == Nil) None else { |
52 } |
27 Some(list.head.split(",").toList(1).toDouble) |
53 |
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54 //test cases |
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55 //get_first_price("GOOG", 1980) |
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56 //get_first_price("GOOG", 2010) |
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57 //get_first_price("FB", 2014) |
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58 |
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59 /* |
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60 for (i <- 1978 to 2018) { |
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61 println(blchip_portfolio.map(get_first_price(_, i))) |
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62 } |
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63 |
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64 for (i <- 1978 to 2018) { |
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65 println(rstate_portfolio.map(get_first_price(_, i))) |
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66 } |
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67 */ |
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68 |
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69 |
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70 // (3) Complete the function below that obtains all first prices |
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71 // for the stock symbols from a portfolio (list of strings) and |
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72 // for the given range of years. The inner lists are for the |
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73 // stock symbols and the outer list for the years. |
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74 |
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75 def get_prices(portfolio: List[String], years: Range): List[List[Option[Double]]] = |
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76 for (year <- years.toList) yield |
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77 for (symbol <- portfolio) yield get_first_price(symbol, year) |
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78 |
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79 |
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80 //test cases |
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81 |
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82 //println("Task 3 data from Google and Apple in 2010 to 2012") |
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83 //val goog_aapl_prices = get_prices(List("GOOG", "AAPL"), 2010 to 2012) |
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84 //println(goog_aapl_prices.toString ++ "\n") |
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85 |
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86 //val p_fb = get_prices(List("FB"), 2012 to 2014) |
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87 //val tt = get_prices(List("BIDU"), 2004 to 2008) |
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88 |
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89 |
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90 // (4) The function below calculates the change factor (delta) between |
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91 // a price in year n and a price in year n + 1. |
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92 |
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93 def get_delta(price_old: Option[Double], price_new: Option[Double]) : Option[Double] = { |
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94 (price_old, price_new) match { |
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95 case (Some(x), Some(y)) => Some((y - x) / x) |
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96 case _ => None |
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97 } |
28 } |
98 } |
29 } |
99 |
30 |
100 |
31 |
101 // (5) The next function calculates all change factors for all prices (from a |
32 // (3) |
102 // portfolio). The input to this function are the nested lists created by |
33 def get_prices(portfolio: List[String], years: Range) : List[List[Option[Double]]] = { |
103 // get_prices above. |
34 for (n <- years.toList) yield{ |
104 |
35 for (m <- portfolio) yield{ |
105 def get_deltas(data: List[List[Option[Double]]]): List[List[Option[Double]]] = |
36 get_first_price(m, n) |
106 for (i <- (0 until (data.length - 1)).toList) yield |
37 } |
107 for (j <- (0 until (data(0).length)).toList) yield get_delta(data(i)(j), data(i + 1)(j)) |
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108 |
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109 |
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110 |
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111 // test case using the prices calculated above |
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112 |
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113 //println("Task 5 change prices from Google and Apple in 2010 and 2011") |
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114 //val goog_aapl_deltas = get_deltas(goog_aapl_prices) |
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115 //println(goog_aapl_deltas.toString ++ "\n") |
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116 |
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117 //val ttd = get_deltas(tt) |
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118 |
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119 |
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120 // (6) Write a function that given change factors, a starting balance and an index, |
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121 // calculates the yearly yield, i.e. new balance, according to our dumb investment |
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122 // strategy. Index points to a year in the data list. |
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123 |
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124 def yearly_yield(data: List[List[Option[Double]]], balance: Long, index: Int): Long = { |
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125 val somes = data(index).flatten |
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126 val somes_length = somes.length |
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127 if (somes_length == 0) balance |
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128 else { |
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129 val portion: Double = balance.toDouble / somes_length.toDouble |
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130 balance + (for (x <- somes) yield (x * portion)).sum.toLong |
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131 } |
38 } |
132 } |
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133 |
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134 // test case using the deltas calculated above |
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135 //println("Task 6 yield from Google and Apple in 2010 with balance 100") |
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136 |
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137 //val d0 = goog_aapl_deltas(0)(0) |
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138 //val d1 = goog_aapl_deltas(0)(1) |
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139 //println(s"50 * ${d0.get} + 50 * ${d1.get} = ${50.toDouble * d0.get + 50.toDouble * d1.get}") |
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140 |
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141 |
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142 //val goog_aapl_yield = yearly_yield(goog_aapl_deltas, 100, 0) |
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143 //println("Rounded yield: " ++ goog_aapl_yield.toString ++ "\n") |
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144 |
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145 |
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146 //yearly_yield(get_prices(rstate_portfolio, 2016 to 2018), 100, 2) |
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147 //get_prices(rstate_portfolio, 2016 to 2018)(2).flatten.sum |
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148 |
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149 |
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150 // (7) Write a function compound_yield that calculates the overall balance for a |
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151 // range of years where in each year the yearly profit is compounded to the new |
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152 // balances and then re-invested into our portfolio. For this use the function and |
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153 // results generated under (6). The function investment calls compound_yield |
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154 // with the appropriate deltas and the first index. |
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155 |
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156 |
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157 def compound_yield(data: List[List[Option[Double]]], balance: Long, index: Int): Long = { |
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158 if (index >= data.length) balance else { |
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159 val new_balance = yearly_yield(data, balance, index) |
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160 compound_yield(data, new_balance, index + 1) |
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161 } |
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162 } |
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163 |
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164 def investment(portfolio: List[String], years: Range, start_balance: Long): Long = { |
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165 compound_yield(get_deltas(get_prices(portfolio, years)), start_balance, 0) |
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166 } |
39 } |
167 |
40 |
168 |
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169 |
42 |
170 //test cases for the two portfolios given above |
43 // (4) |
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44 def get_delta(price_old: Option[Double], price_new: Option[Double]) : Option[Double] = { |
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45 if (price_old != None && price_new != None) Some((price_new.get - price_old.get) / price_old.get) else None |
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46 } |
171 |
47 |
172 println("Real data: " + investment(rstate_portfolio, 1978 to 2019, 100)) |
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173 println("Blue data: " + investment(blchip_portfolio, 1978 to 2019, 100)) |
49 |
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50 // (5) |
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51 def get_deltas(data: List[List[Option[Double]]]) : List[List[Option[Double]]] = { |
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52 for (n <- data.tail) yield{ |
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53 for (m <- n) yield{ |
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54 get_delta(data(data.tail.indexOf(n))(n.indexOf(m)),m) |
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55 } |
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56 } |
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57 } |
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58 |
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59 // (6) |
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60 def yearly_yield(data: List[List[Option[Double]]], balance: Long, index: Int) : Long = { |
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61 if(data.length == 0) balance else{ |
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62 val equal = balance / data(index).flatten.length |
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63 val list = for(n <- data(index).flatten) yield n * equal |
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64 (balance + list.sum).toLong |
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65 } |
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66 } |
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67 |
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68 // (7) |
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69 def compound_yield(data: List[List[Option[Double]]], balance: Long, index: Int) : Long = { |
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70 val deltas = get_deltas(data) |
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71 if (deltas.length == 0) balance else{ |
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72 if(deltas.length - 1 == index) yearly_yield(deltas, balance, index) else compound_yield(data, yearly_yield(deltas, balance, index), index + 1) |
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73 } |
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74 } |
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75 |
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76 def investment(portfolio: List[String], years: Range, start_balance: Long) : Long = { |
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77 val list = get_prices(portfolio, years) |
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78 compound_yield(list, start_balance, 0) |
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79 } |
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80 |
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81 |
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82 |
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83 |
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84 //Test cases for the two portfolios given above |
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85 |
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86 //println("Real data: " + investment(rstate_portfolio, 1978 to 2019, 100)) |
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87 //println("Blue data: " + investment(blchip_portfolio, 1978 to 2019, 100)) |
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88 |
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89 |
176 } |
90 } |
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95 // This template code is subject to copyright |
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96 // by King's College London, 2022. Do not |
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97 // make the template code public in any shape |
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98 // or form, and do not exchange it with other |
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99 // students under any circumstance. |
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