1 // Main Part about a really dumb investment strategy |
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2 //====================================================== |
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3 |
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4 object CW6b { |
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5 |
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6 |
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7 //two test portfolios |
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8 |
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9 val blchip_portfolio = List("GOOG", "AAPL", "MSFT", "IBM", "FB", "AMZN", "BIDU") |
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10 val rstate_portfolio = List("PLD", "PSA", "AMT", "AIV", "AVB", "BXP", "CCI", |
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11 "DLR", "EQIX", "EQR", "ESS", "EXR", "FRT", "HCP") |
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12 |
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13 import io.Source |
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14 import scala.util._ |
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15 |
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16 // (1) The function below takes a stock symbol and a year as arguments. |
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17 // It should read the corresponding CSV-file and reads the January |
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18 // data from the given year. The data should be collected in a list of |
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19 // strings for each line in the CSV-file. |
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20 |
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21 def get_january_data(symbol: String, year: Int) : List[String] = |
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22 Source.fromFile(symbol ++ ".csv")("ISO-8859-1").getLines.toList.filter(_.startsWith(year.toString)) |
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23 |
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24 |
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25 //test cases |
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26 //blchip_portfolio.map(get_january_data(_, 2018)) |
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27 //rstate_portfolio.map(get_january_data(_, 2018)) |
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28 |
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29 //get_january_data("GOOG", 1980) |
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30 //get_january_data("GOOG", 2010) |
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31 //get_january_data("FB", 2014) |
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32 |
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33 //get_january_data("PLD", 1980) |
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34 //get_january_data("EQIX", 2010) |
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35 //get_january_data("ESS", 2014) |
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36 |
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37 |
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38 // (2) From the output of the get_january_data function, the next function |
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39 // should extract the first line (if it exists) and the corresponding |
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40 // first trading price in that year with type Option[Double]. If no line |
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41 // is generated by get_january_data then the result is None; Some if |
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42 // there is a price. |
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43 |
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44 def get_first_price(symbol: String, year: Int) : Option[Double] = { |
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45 val data = Try(Some(get_january_data(symbol, year).head)) getOrElse None |
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46 data.map(_.split(",").toList(1).toDouble) |
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47 } |
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48 |
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49 //test cases |
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50 //get_first_price("GOOG", 1980) |
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51 //get_first_price("GOOG", 2010) |
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52 //get_first_price("FB", 2014) |
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53 |
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54 /* |
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55 for (i <- 1978 to 2018) { |
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56 println(blchip_portfolio.map(get_first_price(_, i))) |
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57 } |
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58 |
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59 for (i <- 1978 to 2018) { |
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60 println(rstate_portfolio.map(get_first_price(_, i))) |
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61 } |
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62 */ |
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63 |
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64 |
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65 // (3) Complete the function below that obtains all first prices |
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66 // for the stock symbols from a portfolio (list of strings) and |
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67 // for the given range of years. The inner lists are for the |
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68 // stock symbols and the outer list for the years. |
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69 |
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70 def get_prices(portfolio: List[String], years: Range): List[List[Option[Double]]] = |
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71 for (year <- years.toList) yield |
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72 for (symbol <- portfolio) yield get_first_price(symbol, year) |
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73 |
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74 |
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75 //test cases |
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76 |
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77 //println("Task 3 data from Google and Apple in 2010 to 2012") |
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78 //val goog_aapl_prices = get_prices(List("GOOG", "AAPL"), 2010 to 2012) |
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79 //println(goog_aapl_prices.toString ++ "\n") |
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80 |
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81 //val p_fb = get_prices(List("FB"), 2012 to 2014) |
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82 //val tt = get_prices(List("BIDU"), 2004 to 2008) |
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83 |
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84 |
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85 // (4) The function below calculates the change factor (delta) between |
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86 // a price in year n and a price in year n + 1. |
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87 |
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88 def get_delta(price_old: Option[Double], price_new: Option[Double]) : Option[Double] = { |
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89 (price_old, price_new) match { |
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90 case (Some(x), Some(y)) => Some((y - x) / x) |
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91 case _ => None |
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92 } |
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93 } |
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94 |
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95 |
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96 // (5) The next function calculates all change factors for all prices (from a |
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97 // portfolio). The input to this function are the nested lists created by |
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98 // get_prices above. |
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99 |
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100 def get_deltas(data: List[List[Option[Double]]]): List[List[Option[Double]]] = |
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101 for (i <- (0 until (data.length - 1)).toList) yield |
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102 for (j <- (0 until (data(0).length)).toList) yield get_delta(data(i)(j), data(i + 1)(j)) |
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103 |
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104 |
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105 |
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106 // test case using the prices calculated above |
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107 |
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108 //println("Task 5 change prices from Google and Apple in 2010 and 2011") |
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109 //val goog_aapl_deltas = get_deltas(goog_aapl_prices) |
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110 //println(goog_aapl_deltas.toString ++ "\n") |
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111 |
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112 //val ttd = get_deltas(tt) |
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113 |
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114 |
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115 // (6) Write a function that given change factors, a starting balance and an index, |
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116 // calculates the yearly yield, i.e. new balance, according to our dumb investment |
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117 // strategy. Index points to a year in the data list. |
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118 |
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119 def yearly_yield(data: List[List[Option[Double]]], balance: Long, index: Int): Long = { |
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120 val somes = data(index).flatten |
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121 val somes_length = somes.length |
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122 if (somes_length == 0) balance |
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123 else { |
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124 val portion: Double = balance.toDouble / somes_length.toDouble |
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125 balance + (for (x <- somes) yield (x * portion)).sum.toLong |
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126 } |
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127 } |
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128 |
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129 // test case using the deltas calculated above |
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130 //println("Task 6 yield from Google and Apple in 2010 with balance 100") |
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131 |
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132 //val d0 = goog_aapl_deltas(0)(0) |
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133 //val d1 = goog_aapl_deltas(0)(1) |
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134 //println(s"50 * ${d0.get} + 50 * ${d1.get} = ${50.toDouble * d0.get + 50.toDouble * d1.get}") |
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135 |
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136 |
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137 //val goog_aapl_yield = yearly_yield(goog_aapl_deltas, 100, 0) |
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138 //println("Rounded yield: " ++ goog_aapl_yield.toString ++ "\n") |
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139 |
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140 |
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141 //yearly_yield(get_prices(rstate_portfolio, 2016 to 2018), 100, 2) |
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142 //get_prices(rstate_portfolio, 2016 to 2018)(2).flatten.sum |
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143 |
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144 |
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145 // (7) Write a function compound_yield that calculates the overall balance for a |
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146 // range of years where in each year the yearly profit is compounded to the new |
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147 // balances and then re-invested into our portfolio. For this use the function and |
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148 // results generated under (6). The function investment calls compound_yield |
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149 // with the appropriate deltas and the first index. |
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150 |
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151 |
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152 def compound_yield(data: List[List[Option[Double]]], balance: Long, index: Int): Long = { |
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153 if (index >= data.length) balance else { |
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154 val new_balance = yearly_yield(data, balance, index) |
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155 compound_yield(data, new_balance, index + 1) |
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156 } |
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157 } |
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158 |
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159 def investment(portfolio: List[String], years: Range, start_balance: Long): Long = { |
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160 compound_yield(get_deltas(get_prices(portfolio, years)), start_balance, 0) |
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161 } |
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162 |
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163 |
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164 |
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165 //test cases for the two portfolios given above |
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166 |
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167 //println("Real data: " + investment(rstate_portfolio, 1978 to 2019, 100)) |
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168 //println("Blue data: " + investment(blchip_portfolio, 1978 to 2019, 100)) |
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169 |
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170 } |
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171 |
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172 |
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173 |
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