1 // Advanvced Part 3 about a really dumb investment strategy |
1 // Main Part about a really dumb investment strategy |
2 //========================================================== |
2 //====================================================== |
3 |
3 |
4 //object CW6c { |
4 //object CW6b { // for purposes of generating a jar |
5 |
5 |
6 |
6 |
7 //two test portfolios |
7 //two test portfolios |
8 |
8 |
9 val blchip_portfolio = List("GOOG", "AAPL", "MSFT", "IBM", "FB", "AMZN", "BIDU") |
9 val blchip_portfolio = List("GOOG", "AAPL", "MSFT", "IBM", "FB", "AMZN", "BIDU") |
10 val rstate_portfolio = List("PLD", "PSA", "AMT", "AIV", "AVB", "BXP", "CCI", |
10 val rstate_portfolio = List("PLD", "PSA", "AMT", "AIV", "AVB", "BXP", "CCI", |
11 "DLR", "EQIX", "EQR", "ESS", "EXR", "FRT", "GGP", "HCP") |
11 "DLR", "EQIX", "EQR", "ESS", "EXR", "FRT", "HCP") |
12 |
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13 // (1) The function below should obtain the first trading price |
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14 // for a stock symbol by using the query |
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15 // |
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16 // http://ichart.yahoo.com/table.csv?s=<<symbol>>&a=0&b=1&c=<<year>>&d=1&e=1&f=<<year>> |
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17 // |
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18 // and extracting the first January Adjusted Close price in a year. |
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19 |
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20 |
12 |
21 import io.Source |
13 import io.Source |
22 import scala.util._ |
14 import scala.util._ |
23 |
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 |
24 def get_january_data(symbol: String, year: Int) : List[String] = |
21 def get_january_data(symbol: String, year: Int) : List[String] = |
25 Source.fromFile(symbol ++ ".csv").getLines.toList.filter(_.startsWith(year.toString)) |
22 Source.fromFile(symbol ++ ".csv")("ISO-8859-1").getLines.toList.filter(_.startsWith(year.toString)) |
26 |
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. |
27 |
43 |
28 def get_first_price(symbol: String, year: Int) : Option[Double] = { |
44 def get_first_price(symbol: String, year: Int) : Option[Double] = { |
29 val data = Try(Some(get_january_data(symbol, year).head)) getOrElse None |
45 val data = Try(Some(get_january_data(symbol, year).head)) getOrElse None |
30 data.map(_.split(",").toList(1).toDouble) |
46 data.map(_.split(",").toList(1).toDouble) |
31 } |
47 } |
32 |
48 |
33 get_first_price("GOOG", 1980) |
49 //test cases |
34 get_first_price("GOOG", 2010) |
50 //get_first_price("GOOG", 1980) |
35 get_first_price("FB", 2014) |
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 */ |
36 |
63 |
37 |
64 |
38 // Complete the function below that obtains all first prices |
65 // (3) Complete the function below that obtains all first prices |
39 // for the stock symbols from a portfolio for the given |
66 // for the stock symbols from a portfolio (list of strings) and |
40 // range of years |
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. |
41 |
69 |
42 def get_prices(portfolio: List[String], years: Range): List[List[Option[Double]]] = |
70 def get_prices(portfolio: List[String], years: Range): List[List[Option[Double]]] = |
43 for (year <- years.toList) yield |
71 for (year <- years.toList) yield |
44 for (symbol <- portfolio) yield get_first_price(symbol, year) |
72 for (symbol <- portfolio) yield get_first_price(symbol, year) |
45 |
73 |
46 |
74 |
47 // test case |
75 //test cases |
48 val p_fb = get_prices(List("FB"), 2012 to 2014) |
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49 val p = get_prices(List("GOOG", "AAPL"), 2010 to 2012) |
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50 |
76 |
51 val tt = get_prices(List("BIDU"), 2004 to 2008) |
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") |
52 |
80 |
53 // (2) The first function below calculates the change factor (delta) between |
81 //val p_fb = get_prices(List("FB"), 2012 to 2014) |
54 // a price in year n and a price in year n+1. The second function calculates |
82 //val tt = get_prices(List("BIDU"), 2004 to 2008) |
55 // all change factors for all prices (from a portfolio). |
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. |
56 |
87 |
57 def get_delta(price_old: Option[Double], price_new: Option[Double]) : Option[Double] = { |
88 def get_delta(price_old: Option[Double], price_new: Option[Double]) : Option[Double] = { |
58 (price_old, price_new) match { |
89 (price_old, price_new) match { |
59 case (Some(x), Some(y)) => Some((y - x) / x) |
90 case (Some(x), Some(y)) => Some((y - x) / x) |
60 case _ => None |
91 case _ => None |
61 } |
92 } |
62 } |
93 } |
63 |
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 |
64 def get_deltas(data: List[List[Option[Double]]]): List[List[Option[Double]]] = |
100 def get_deltas(data: List[List[Option[Double]]]): List[List[Option[Double]]] = |
65 for (i <- (0 until (data.length - 1)).toList) yield |
101 for (i <- (0 until (data.length - 1)).toList) yield |
66 for (j <- (0 until (data(0).length)).toList) yield get_delta(data(i)(j), data(i + 1)(j)) |
102 for (j <- (0 until (data(0).length)).toList) yield get_delta(data(i)(j), data(i + 1)(j)) |
67 |
103 |
68 |
104 |
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105 |
69 // test case using the prices calculated above |
106 // test case using the prices calculated above |
70 val d = get_deltas(p) |
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71 val ttd = get_deltas(tt) |
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72 |
107 |
73 // (3) Write a function that given change factors, a starting balance and a year |
108 //println("Task 5 change prices from Google and Apple in 2010 and 2011") |
74 // calculates the yearly yield, i.e. new balanace, according to our dump investment |
109 //val goog_aapl_deltas = get_deltas(goog_aapl_prices) |
75 // strategy. Another function calculates given the same data calculates the |
110 //println(goog_aapl_deltas.toString ++ "\n") |
76 // compound yield up to a given year. Finally a function combines all |
111 |
77 // calculations by taking a portfolio, a range of years and a start balance |
112 //val ttd = get_deltas(tt) |
78 // as arguments. |
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79 |
113 |
80 |
114 |
81 def yearly_yield(data: List[List[Option[Double]]], balance: Long, year: Int): Long = { |
115 // (6) Write a function that given change factors, a starting balance and an index, |
82 val somes = data(year).flatten |
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 |
83 val somes_length = somes.length |
121 val somes_length = somes.length |
84 if (somes_length == 0) balance |
122 if (somes_length == 0) balance |
85 else { |
123 else { |
86 val portion: Double = balance.toDouble / somes_length.toDouble |
124 val portion: Double = balance.toDouble / somes_length.toDouble |
87 balance + (for (x <- somes) yield (x * portion)).sum.toLong |
125 balance + (for (x <- somes) yield (x * portion)).sum.toLong |
88 } |
126 } |
89 } |
127 } |
90 |
128 |
91 def compound_yield(data: List[List[Option[Double]]], balance: Long, year: Int): Long = { |
129 // test case using the deltas calculated above |
92 if (year >= data.length) balance else { |
130 //println("Task 6 yield from Google and Apple in 2010 with balance 100") |
93 val new_balance = yearly_yield(data, balance, year) |
131 |
94 compound_yield(data, new_balance, year + 1) |
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) |
95 } |
156 } |
96 } |
157 } |
97 |
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98 //yearly_yield(d, 100, 0) |
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99 //compound_yield(d.take(6), 100, 0) |
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100 |
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101 //test case |
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102 //yearly_yield(d, 100, 0) |
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103 //yearly_yield(d, 225, 1) |
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104 //yearly_yield(d, 246, 2) |
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105 //yearly_yield(d, 466, 3) |
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106 //yearly_yield(d, 218, 4) |
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107 |
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108 //yearly_yield(d, 100, 0) |
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109 //yearly_yield(d, 125, 1) |
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110 |
158 |
111 def investment(portfolio: List[String], years: Range, start_balance: Long): Long = { |
159 def investment(portfolio: List[String], years: Range, start_balance: Long): Long = { |
112 compound_yield(get_deltas(get_prices(portfolio, years)), start_balance, 0) |
160 compound_yield(get_deltas(get_prices(portfolio, years)), start_balance, 0) |
113 } |
161 } |
114 |
162 |
115 /* |
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116 val q1 = get_deltas(get_prices(List("GOOG", "AAPL", "BIDU"), 2000 to 2017)) |
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117 yearly_yield(q1, 100, 0) |
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118 yearly_yield(q1, 100, 1) |
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119 yearly_yield(q1, 100, 2) |
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120 yearly_yield(q1, 100, 3) |
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121 yearly_yield(q1, 100, 4) |
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122 yearly_yield(q1, 100, 5) |
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123 yearly_yield(q1, 100, 6) |
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124 |
163 |
125 investment(List("GOOG", "AAPL", "BIDU"), 2004 to 2017, 100) |
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126 val one = get_deltas(get_prices(rstate_portfolio, 1978 to 1984)) |
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127 val two = get_deltas(get_prices(blchip_portfolio, 1978 to 1984)) |
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128 |
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129 val one_full = get_deltas(get_prices(rstate_portfolio, 1978 to 2017)) |
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130 val two_full = get_deltas(get_prices(blchip_portfolio, 1978 to 2017)) |
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131 |
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132 one_full.map(_.flatten).map(_.sum).sum |
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133 two_full.map(_.flatten).map(_.sum).sum |
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134 |
164 |
135 //test cases for the two portfolios given above |
165 //test cases for the two portfolios given above |
136 |
166 |
137 //println("Real data: " + investment(rstate_portfolio, 1978 to 2017, 100)) |
167 //println("Real data: " + investment(rstate_portfolio, 1978 to 2019, 100)) |
138 //println("Blue data: " + investment(blchip_portfolio, 1978 to 2017, 100)) |
168 //println("Blue data: " + investment(blchip_portfolio, 1978 to 2019, 100)) |
139 |
169 |
140 for (i <- 2000 to 2017) { |
170 //} |
141 println("Year " + i) |
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142 //println("Real data: " + investment(rstate_portfolio, 1978 to i, 100)) |
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143 //println("Blue data: " + investment(blchip_portfolio, 1978 to i, 100)) |
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144 println("test: " + investment(List("GOOG", "AAPL", "BIDU"), 2000 to i, 100)) |
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145 } |
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146 |
171 |
147 |
172 |
148 */ |
173 |
149 //1984 |
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150 //1992 |
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151 //} |
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