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  1. #include <iostream>
  2. #include <vector>
  3. #include <algorithm>
  4. #include <cmath>
  5. #include <iomanip>
  6.  
  7. double percentile(const std::vector<double>& data, double p) {
  8.     if (data.empty()) return NAN;
  9.     double idx = p * (data.size() - 1);
  10.     size_t i = static_cast<size_t>(idx);
  11.     double frac = idx - i;
  12.     return data[i] * (1.0 - frac) + data[std::min(i + 1, data.size() - 1)] * frac;
  13. }
  14.  
  15. void rolling_cagr_stats_dca_correct(const std::vector<double>& returns, int duration) {
  16.     size_t n = returns.size();
  17.     if (n < duration) {
  18.         std::cout << "Not enough data for the specified duration.\n";
  19.         return;
  20.     }
  21.  
  22.     std::vector<double> cagr_list;
  23.  
  24.     for (size_t start = 0; start <= n - duration; ++start) {
  25.         double total_value = 0.0;
  26.  
  27.         for (int j = 0; j < duration; ++j) {
  28.             double compounded = 1.0;
  29.             for (int t = j; t < duration; ++t) {
  30.                 compounded *= (1.0 + returns[start + t]);
  31.             }
  32.             total_value += compounded;
  33.         }
  34.  
  35.         double cagr = std::pow(total_value / duration, 1.0 / duration) - 1.0;
  36.         cagr_list.push_back(cagr);
  37.     }
  38.  
  39.     std::sort(cagr_list.begin(), cagr_list.end());
  40.  
  41.     auto percentile = [](const std::vector<double>& data, double p) {
  42.         double idx = p * (data.size() - 1);
  43.         size_t i = static_cast<size_t>(idx);
  44.         double frac = idx - i;
  45.         return data[i] * (1 - frac) + data[std::min(i + 1, data.size() - 1)] * frac;
  46.     };
  47.  
  48.     double min_cagr = cagr_list.front();
  49.     double max_cagr = cagr_list.back();
  50.     double median_cagr = percentile(cagr_list, 0.50);
  51.     double bottom_15 = percentile(cagr_list, 0.15);
  52.     double top_15 = percentile(cagr_list, 0.85);
  53.  
  54.     std::cout << "=== DCA Mode (Corrected Logic) ===\n";
  55.     std::cout << "Duration: " << duration << " years\n";
  56.     std::cout << "Number of periods: " << cagr_list.size() << "\n";
  57.     std::cout << "Min CAGR: " << std::fixed << std::setprecision(2) << min_cagr * 100 << "%\n";
  58.     std::cout << "Bottom 15th percentile CAGR: " << bottom_15 * 100 << "%\n";
  59.     std::cout << "Median CAGR: " << median_cagr * 100 << "%\n";
  60.     std::cout << "Top 85th percentile CAGR: " << top_15 * 100 << "%\n";
  61.     std::cout << "Max CAGR: " << max_cagr * 100 << "%\n";
  62. }
  63.  
  64.  
  65. int main() {
  66.     std::vector<double> returns = {
  67.         -0.04, 0.14, 0.15, -0.14, -0.19, 0.26, 0.28, 0.04, 0.08, 0.28,
  68.         0.08, -0.06, 0.24, 0.22, -0.01, 0.26, 0.14, -0.02, 0.14, 0.16,
  69.         -0.16, 0.29, 0.15, 0.18, -0.03, 0.20, 0.13, 0.20, 0.02, 0.08,
  70.         -0.04, 0.04, -0.07, 0.33, 0.12, 0.06, 0.15, 0.01, -0.26, 0.31,
  71.         0.22, -0.03, 0.15, 0.19, 0.08, -0.06, 0.16, 0.13, -0.11, 0.21,
  72.         0.13, 0.12, -0.18, 0.15, 0.12
  73.     };
  74.  
  75.     int duration = 18;
  76.     rolling_cagr_stats_dca_correct(returns, duration);
  77.  
  78.     return 0;
  79. }
  80.  
Success #stdin #stdout 0.01s 5288KB
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stdout
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=== DCA Mode (Corrected Logic) ===
Duration: 18 years
Number of periods: 38
Min CAGR: 2.80%
Bottom 15th percentile CAGR: 3.86%
Median CAGR: 5.01%
Top 85th percentile CAGR: 6.44%
Max CAGR: 6.92%
https://ideone.com/SvG1ru
language:
C++ (gcc 8.3)
created:
10 days ago
visibility:
public

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