c#计算股票和指数之间的投资组合贝塔

Question

有谁知道计算投资组合或股票与基准（例如 C# 中的 S&P 等指数）的 Beta（贝塔系数）的方法？

我已经有 2 个 double 类型的数组用于此类计算，但我找不到任何巧妙的方法来执行此操作。

StatisticFormula.BetaFunction 方法 (Double, Double) 存在，但它为每个参数接受一个值，而不是一个数组——这在统计上没有意义。

提前致谢

Answer 1

我不知道有什么好的 C# Finance/Statistics 包，所以我直接写了方法并借鉴了这个统计包：https://www.codeproject.com/Articles/42492/Using-LINQ-to-Calculate-Basic-Statistics

using System;
using System.Collections.Generic;
using System.Linq;

namespace ConsoleApplication1
{
    static class Program
    {
        static void Main(string[] args)
        {
            double[] closingPriceStock = { 39.32, 39.45, 39.27, 38.73, 37.99, 38.38, 39.53, 40.55, 40.78, 41.3, 41.35, 41.25, 41.1, 41.26, 41.48, 41.68, 41.77, 41.92, 42.12, 41.85, 41.54 };
            double[] closingPriceMarket = { 1972.18, 1988.87, 1987.66, 1940.51, 1867.61, 1893.21, 1970.89, 2035.73, 2079.61, 2096.92, 2102.44, 2091.54, 2083.39, 2086.05, 2084.07, 2104.18, 2077.57, 2083.56, 2099.84, 2093.32, 2098.04 };

            double[] closingPriceStockDailyChange = new double[closingPriceStock.Length - 1];
            double[] closingPriceMarketDailyChange = new double[closingPriceMarket.Length - 1];

            for (int i = 0; i < closingPriceStockDailyChange.Length; i++)
            {
                closingPriceStockDailyChange[i] = (closingPriceStock[i + 1] - closingPriceStock[i]) * 100 / closingPriceStock[i];
                closingPriceMarketDailyChange[i] = (closingPriceMarket[i + 1] - closingPriceMarket[i]) * 100 / closingPriceMarket[i];
            }

            double beta = Covariance(closingPriceStockDailyChange, closingPriceMarketDailyChange) / Variance(closingPriceMarketDailyChange);

            Console.WriteLine(beta);

            Console.Read();
        }


        public static double Variance(this IEnumerable<double> source)
        {
            int n = 0;
            double mean = 0;
            double M2 = 0;

            foreach (double x in source)
            {
                n = n + 1;
                double delta = x - mean;
                mean = mean + delta / n;
                M2 += delta * (x - mean);
            }
            return M2 / (n - 1);
        }

        public static double Covariance(this IEnumerable<double> source, IEnumerable<double> other)
        {
            int len = source.Count();

            double avgSource = source.Average();
            double avgOther = other.Average();
            double covariance = 0;

            for (int i = 0; i < len; i++)
                covariance += (source.ElementAt(i) - avgSource) * (other.ElementAt(i) - avgOther);

            return covariance / len;
        }

    }


}

这必须重构才能在函数中计算 beta，您可以导入链接包以避免我包含的静态方法等，但这只是一个玩具示例。

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