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我对皮尔逊相关系数的这个问题感到非常沮丧。我有一个程序可以在指定的时间段内每天输出两个股票代码的股票值，我还绘制了这些值的图表。您可以选择美元、欧元和瑞典克朗进行输出。但是，根据我选择的货币，我的皮尔逊相关系数似乎有所不同？我不知道这是正确的还是某处有错误？进行计算的实际功能似乎还可以，所以我不明白...

根据货币，系数应该不同还是应该相同？股票的欧元和瑞典克朗货币价值是通过将股票的美元价值乘以同一天欧元或瑞典克朗的收盘价来计算的。

该方法计算系数：

public double CorrelationCalc(ArrayList<Integer> list1, ArrayList<Integer> list2) {
    double sumX= 0.0, sumY = 0.0, sumXX = 0.0, sumYY = 0.0, sumXY = 0.0;

    int length = list1.size();

    for (int i=0; i<length; i++) {
        int x = list1.get(i);
        int y = list2.get(i);

        sumX+=x;
        sumY+=y;
        sumXX+=x*x;
        sumYY+=y*y;
        sumXY+=x*y;
    }

        double cov = sumXY / length - sumX*sumY / length / length;

        double sigmaX = Math.sqrt(sumXX / length - sumX*sumX / length / length);
        double sigmaY = Math.sqrt(sumYY / length - sumY*sumY / length / length);

        return cov/sigmaX/sigmaY;


}

股票收盘价是通过 .csv 文件从 yahoo Finance 获取的，这些循环获取这些值并将它们添加到数组列表中。

//This one is for when USD is selected. (Close value for each date located 
//at index 4 on each line in the csv file)
while ((line = buf.readLine())!=null && (line2 = buf2.readLine())!= null) {
    if(n != 0) { //First row contains text only
        close1 = (Math.round(100 * Double.parseDouble(line.split(",")[4]))/100.0);
        close2 = Math.round(100 * Double.parseDouble(line2.split(",")[4]))/100.0;

        ticker1List.add((int) Math.round(close1));
        ticker2List.add((int) Math.round(close2));
    }
    n++;
}

和。buf3 是读取汇率 csv 的字符串缓冲区

//This one is for non USD (SEK or EUR). multiplies the values with the currency rate
while ((line = buf.readLine())!=null && (line2 = buf2.readLine())!= null && (line3 = buf3.readLine())!= null) {
    if(n != 0) {//First row contains text only
            while (!line.split(",")[0].equals(line3.split(",")[0])) { //Makes sure that dates match
                line3 = buf3.readLine();
            }
        close1 = (Math.round(100 * Double.parseDouble(line.split(",")[4])*Double.parseDouble(line3.split(",")[4]))/100.0);
        close2 = Math.round(100 * Double.parseDouble(line2.split(",")[4])*Double.parseDouble(line3.split(",")[4]))/100.0;


        ticker1List.add((int) Math.round(close1));
        ticker2List.add((int) Math.round(close2));
    }
    n++;
}

ticker1List 和 ticker2List 是后来发送到上述方法进行计算的列表。

输出样本：

美元

ticker1List = {542, 535, 539, 547, 559, 563, 575, 579, 578, 581, 573, 574, 560, 556, 561, 553, 562, 558, 566, 564, 565, 565, 578, 567 , 564, 558, 561, 555, 549, 541, 544, 545, 549, 548, 549, 549, 540, 541, 544, 533, 545, 543, 549, 557, 574, 566, 564, 561, 549 , 551, 553, 543, 535, 542, 549, 546, 539, 539, 549, 546, 547, 549, 553, 557, 555, 547, 554, 554, 545, 549, 554, 555, 552, 550 , 543, 542, 553, 550, 547, 543, 545, 547, 556, 558, 560, 563, 559, 558, 553, 541, 540, 543, 547, 546, 550, 542, 545, 556, 572 , 584, 584, 602, 700, 693, 695, 695, 675, 655, 658, 660, 661}ticker2List = {44, 44, 44, 44, 44, 44, 44, 43, 43, 43, 42, 43, 42, 42, 41, 41, 42, 42, 43, 42, 43, 43, 43, 41, 41, 41, 41, 41, 41, 40, 42, 42, 41, 41, 42, 42, 42, 42, 42, 42, 43, 43, 43, 43, 48, 48, 49, 49, 49, 49, 48, 48, 46, 47, 48, 47, 47, 48, 49, 48, 48, 48, 48, 47, 47, 47, 48, 47, 47,47, 47, 47, 46, 46, 46, 46, 47, 46, 46, 45, 46, 46, 47, 46, 46, 46, 46, 46, 45, 44, 44, 44, 44, 44, 44, 44, 45, 45, 46, 46, 46, 47, 47, 47, 47, 46, 46, 46, 45, 45, 46 }

皮尔逊：0.1439484634863799

瑞典克朗

Currency rate = {8.55523, 8.509, 8.5914, 8.564, 8.5947, 8.5379, 8.6162, 8.6554, 8.54502, 8.5075, 8.5015, 8.4947, 8.4503, 8.4634, 8.46479, 8.51185, 8.4701, 8.51984, 8.38558, 8.2967, 8.23152, 8.4052, 8.24647, 8.23443, 8.253, 8.13911, 8.11373, 8.12167, 8.09872, 8.17692, 8.1593, 8.20512, 8.2148, 8.26875, 8.28135, 8.29895, 8.3914, 8.2918, 8.31362, 8.4409, 8.58413, 8.548, 8.4556, 8.51005, 8.4676, 8.4153, 8.33381, 8.3411, 8.3424, 8.22841, 8.19809, 8.24101, 8.23992, 8.3265, 8.30831, 8.25121, 8.2754, 8.2294, 8.3507, 8.36978, 8.40981, 8.3328, 8.34131, 8.5058, 8.60651, 8.6354, 8.6344, 8.72934, 8.6574, 8.69648, 8.63365, 8.58971, 8.714, 8.7647, 8.81522, 8.81353, 8.75727, 8.6755, 8.6743, 8.5591, 8.52942, 8.65399, 8.6243, 8.5889, 8.586, 8.58851, 8.493, 8.51087, 8.50157, 8.61801, 8.6706, 8.6013, 8.68419, 8.6546, 8.7287, 8.5913, 8.62343, 8.55167, 8.4879、8.4632、8。33779、8.32539、8.2671、8.3381、8.36064、8.3922、8.28541、8.40471、8.4139、8.3832、8.42055}

给

ticker1List = {4562, 4485, 4532, 4600, 4634, 4722, 4808, 4826, 4781, 4841, 4777, 4859, 4752, 4752, 4839, 4751, 4902, 4826, 4902, 4826, 4902, 4826, 4917, 48748, 918, 48748, 28, 44 , 4787, 4789, 4818, 4764, 4739, 4684, 4640, 4664, 4761, 4754, 4804, 4835, 4758, 4742, 4736, 4576, 4701, 4721, 4754, 4866, 4953, 4889, 4857, 4775, 4577 ，4593，4649，4545，4468，4461，4543，4543，45476，4476，4492，4525，4525，4525，4482，4520，4520，4609，4644，4644，4644，4621，4605 ，4561，4499，4576，4548，4497，4455，4446，4470，4470，4528，4528，4541，4585，4610，4594，4594，4561，4561，4549，4549 , 4962, 4965, 5120, 5978, 5997, 5991, 5935, 5799, 5607, 5655, 5613, 5659}

ticker2List = {369, 370, 371, 370, 365, 368, 367, 361, 356, 359, 353, 363, 357, 359, 354, 356, 363, 361, 369, 364, 372, 369, 365, 353 , 350, 352, 352, 349, 351, 349, 354, 355, 359, 360, 365, 368, 367, 370, 367, 358, 370, 371, 372, 378, 413, 415, 423, 417, 406 , 405, 406, 398, 386, 384, 395, 391, 393, 397, 401, 398, 394, 392, 397, 396, 391, 392, 403, 404, 396, 404, 403, 395, 385, 383 , 384, 379, 386, 384, 378, 373, 374, 376, 378, 374, 375, 374, 377, 376, 373, 373, 363, 369, 372, 378, 375, 377, 377, 378, 385 , 388, 389, 397, 398, 406, 407, 389, 396, 393, 390, 386, 396}

皮尔逊：0.20617640237659246

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1 回答 1

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只有当两只股票都以相同的货币报价时，您的实施才有效，因为它们都通过相同的汇率时间序列（代码中的 buf3）进行转换。当它们都使用本国货币时，它们的相关性可能不同于它们都转换为另一种货币时的相关性，因为汇率不是恒定的。例如，如果两只股票都是欧元，而您以美元计算它们的相关性，那么您计算的是基于美元的投资者在将美元兑换成欧元然后购买股票后所经历的相关性。时间序列的部分波动是由于 EURUSD 汇率的变动，而不仅仅是股票价格。相比之下，这两种资产的欧元投资者只会体验到股票价格的相关性，而不会受到外汇汇率的影响。

这真的取决于你想在这里完成什么。例如，您的代码不会处理以不同货币本地报价的股票。如果是这种情况，只要外汇汇率保持一致并假设完美精确，那么无论您计算相关性的货币是什么，转换为共同货币后资产价格之间的相关性都是相同的。如果资产 1 以欧元报价，资产 2 以美元报价，您将在以下情况下获得相同的相关性：

  1. Correl（资产 1 美元，资产 2）
  2. Correl（资产 1，资产 2 欧元）
  3. Correl（资产 1 瑞典克朗，资产 2 瑞典克朗）

即使在比较不同货币的资产时，也有合理的应用来计算它们的相关性，而完全不考虑汇率，即资产 1 的欧元与资产 2 的美元。这将导致与上述不同的相关性。

于 2017-03-21T20:17:48.403 回答