XIRR Calculation

Question

How do I calculate Excel's XIRR function using C#?

Answer 1

According to XIRR function openoffice documentation (formula is same as in excel) you need to solve for XIRR variable in the following f(xirr) equation:

You can calculate xirr value by:

1. calculating derivative of above function -> f '(xirr)
2. after having f(xirr) and f'(xirr) you can solve for xirr value by using iterative Newton's method - famous formula->
   

EDIT
I've got a bit of time so, here it is - complete C# code for XIRR calculation:

class xirr
    {
        public const double tol = 0.001;
        public delegate double fx(double x);

        public static fx composeFunctions(fx f1, fx f2) {
            return (double x) => f1(x) + f2(x);
        }

        public static fx f_xirr(double p, double dt, double dt0) {
            return (double x) => p*Math.Pow((1.0+x),((dt0-dt)/365.0));
        }

        public static fx df_xirr(double p, double dt, double dt0) {
            return (double x) => (1.0/365.0)*(dt0-dt)*p*Math.Pow((x+1.0),(((dt0-dt)/365.0)-1.0));
        }

        public static fx total_f_xirr(double[] payments, double[] days) {
            fx resf = (double x) => 0.0;

            for (int i = 0; i < payments.Length; i++) {
                resf = composeFunctions(resf,f_xirr(payments[i],days[i],days[0]));
            }

            return resf;
        }

        public static fx total_df_xirr(double[] payments, double[] days) {
            fx resf = (double x) => 0.0;

            for (int i = 0; i < payments.Length; i++) {
                resf = composeFunctions(resf,df_xirr(payments[i],days[i],days[0]));
            }

            return resf;
        }

        public static double Newtons_method(double guess, fx f, fx df) {
            double x0 = guess;
            double x1 = 0.0;
            double err = 1e+100;

            while (err > tol) {
                x1 = x0 - f(x0)/df(x0);
                err = Math.Abs(x1-x0);
                x0 = x1;
            }

            return x0;
        }

        public static void Main (string[] args)
        {
            double[] payments = {-6800,1000,2000,4000}; // payments
            double[] days = {01,08,16,25}; // days of payment (as day of year)
            double xirr = Newtons_method(0.1,
                                         total_f_xirr(payments,days),
                                         total_df_xirr(payments,days));

            Console.WriteLine("XIRR value is {0}", xirr);
        }
    }

BTW, keep in mind that not all payments will result in valid XIRR because of restrictions of formula and/or Newton method!

cheers!

Answer 2

I started with 0x69's solution but eventually some new scenarios caused Newton's Method to fail. I created a "smart" version, which uses Bisection Method (slower) when Newton's fails.

Please notice the inline references to multiple sources I used for this solution.

Finally, you are not going to be able to reproduce some of these scenarios in Excel, for Excel itself uses Newton's method. Refer to XIRR, eh? for an interesting discussion about this.

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

// See the following articles:
//   http://blogs.msdn.com/b/lucabol/archive/2007/12/17/bisection-based-xirr-implementation-in-c.aspx
//   http://www.codeproject.com/Articles/79541/Three-Methods-for-Root-finding-in-C
//   http://www.financialwebring.org/forum/viewtopic.php?t=105243&highlight=xirr
// Default values based on Excel doc 
//   http://office.microsoft.com/en-us/excel-help/xirr-function-HP010062387.aspx

namespace Xirr
{
    public class Program
    {
        private const Double DaysPerYear = 365.0;
        private const int MaxIterations = 100;
        private const double DefaultTolerance = 1E-6;
        private const double DefaultGuess = 0.1;

    private static readonly Func<IEnumerable<CashItem>, Double> NewthonsMethod =
        cf => NewtonsMethodImplementation(cf, Xnpv, XnpvPrime);

    private static readonly Func<IEnumerable<CashItem>, Double> BisectionMethod =
        cf => BisectionMethodImplementation(cf, Xnpv);

    public static void Main(string[] args)
    {
        RunScenario(new[]
            {
                // this scenario fails with Newton's but succeeds with slower Bisection
                new CashItem(new DateTime(2012, 6, 1), 0.01),
                new CashItem(new DateTime(2012, 7, 23), 3042626.18),
                new CashItem(new DateTime(2012, 11, 7), -491356.62),
                new CashItem(new DateTime(2012, 11, 30), 631579.92),
                new CashItem(new DateTime(2012, 12, 1), 19769.5),
                new CashItem(new DateTime(2013, 1, 16), 1551771.47),
                new CashItem(new DateTime(2013, 2, 8), -304595),
                new CashItem(new DateTime(2013, 3, 26), 3880609.64),
                new CashItem(new DateTime(2013, 3, 31), -4331949.61)
            });
        RunScenario(new[]
            {
                new CashItem(new DateTime(2001, 5, 1), 10000),
                new CashItem(new DateTime(2002, 3, 1), 2000),
                new CashItem(new DateTime(2002, 5, 1), -5500),
                new CashItem(new DateTime(2002, 9, 1), 3000),
                new CashItem(new DateTime(2003, 2, 1), 3500),
                new CashItem(new DateTime(2003, 5, 1), -15000)
            });
    }

    private static void RunScenario(IEnumerable<CashItem> cashFlow)
    {
        try
        {
            try
            {
                var result = CalcXirr(cashFlow, NewthonsMethod);
                Console.WriteLine("XIRR [Newton's] value is {0}", result);
            }
            catch (InvalidOperationException)
            {
                // Failed: try another algorithm
                var result = CalcXirr(cashFlow, BisectionMethod);
                Console.WriteLine("XIRR [Bisection] (Newton's failed) value is {0}", result);
            }
        }
        catch (ArgumentException e)
        {
            Console.WriteLine(e.Message);
        }
        catch (InvalidOperationException exception)
        {
            Console.WriteLine(exception.Message);
        }
    }

    private static double CalcXirr(IEnumerable<CashItem> cashFlow, Func<IEnumerable<CashItem>, double> method)
    {
        if (cashFlow.Count(cf => cf.Amount > 0) == 0)
            throw new ArgumentException("Add at least one positive item");

        if (cashFlow.Count(c => c.Amount < 0) == 0)
            throw new ArgumentException("Add at least one negative item");

        var result = method(cashFlow);

        if (Double.IsInfinity(result))
            throw new InvalidOperationException("Could not calculate: Infinity");

        if (Double.IsNaN(result))
            throw new InvalidOperationException("Could not calculate: Not a number");

        return result;
    }

    private static Double NewtonsMethodImplementation(IEnumerable<CashItem> cashFlow,
                                                      Func<IEnumerable<CashItem>, Double, Double> f,
                                                      Func<IEnumerable<CashItem>, Double, Double> df,
                                                      Double guess = DefaultGuess,
                                                      Double tolerance = DefaultTolerance,
                                                      int maxIterations = MaxIterations)
    {
        var x0 = guess;
        var i = 0;
        Double error;
        do
        {
            var dfx0 = df(cashFlow, x0);
            if (Math.Abs(dfx0 - 0) < Double.Epsilon)
                throw new InvalidOperationException("Could not calculate: No solution found. df(x) = 0");

            var fx0 = f(cashFlow, x0);
            var x1 = x0 - fx0/dfx0;
            error = Math.Abs(x1 - x0);

            x0 = x1;
        } while (error > tolerance && ++i < maxIterations);
        if (i == maxIterations)
            throw new InvalidOperationException("Could not calculate: No solution found. Max iterations reached.");

        return x0;
    }

    internal static Double BisectionMethodImplementation(IEnumerable<CashItem> cashFlow,
                                                         Func<IEnumerable<CashItem>, Double, Double> f,
                                                         Double tolerance = DefaultTolerance,
                                                         int maxIterations = MaxIterations)
    {
        // From "Applied Numerical Analysis" by Gerald
        var brackets = Brackets.Find(Xnpv, cashFlow);
        if (Math.Abs(brackets.First - brackets.Second) < Double.Epsilon)
            throw new ArgumentException("Could not calculate: bracket failed");

        Double f3;
        Double result;
        var x1 = brackets.First;
        var x2 = brackets.Second;

        var i = 0;
        do
        {
            var f1 = f(cashFlow, x1);
            var f2 = f(cashFlow, x2);

            if (Math.Abs(f1) < Double.Epsilon && Math.Abs(f2) < Double.Epsilon)
                throw new InvalidOperationException("Could not calculate: No solution found");

            if (f1*f2 > 0)
                throw new ArgumentException("Could not calculate: bracket failed for x1, x2");

            result = (x1 + x2)/2;
            f3 = f(cashFlow, result);

            if (f3*f1 < 0)
                x2 = result;
            else
                x1 = result;
        } while (Math.Abs(x1 - x2)/2 > tolerance && Math.Abs(f3) > Double.Epsilon && ++i < maxIterations);

        if (i == maxIterations)
            throw new InvalidOperationException("Could not calculate: No solution found");

        return result;
    }

    private static Double Xnpv(IEnumerable<CashItem> cashFlow, Double rate)
    {
        if (rate <= -1)
            rate = -1 + 1E-10; // Very funky ... Better check what an IRR <= -100% means

        var startDate = cashFlow.OrderBy(i => i.Date).First().Date;
        return
            (from item in cashFlow
             let days = -(item.Date - startDate).Days
             select item.Amount*Math.Pow(1 + rate, days/DaysPerYear)).Sum();
    }

    private static Double XnpvPrime(IEnumerable<CashItem> cashFlow, Double rate)
    {
        var startDate = cashFlow.OrderBy(i => i.Date).First().Date;
        return (from item in cashFlow
                let daysRatio = -(item.Date - startDate).Days/DaysPerYear
                select item.Amount*daysRatio*Math.Pow(1.0 + rate, daysRatio - 1)).Sum();
    }

    public struct Brackets
    {
        public readonly Double First;
        public readonly Double Second;

        public Brackets(Double first, Double second)
        {
            First = first;
            Second = second;
        }

        internal static Brackets Find(Func<IEnumerable<CashItem>, Double, Double> f,
                                      IEnumerable<CashItem> cashFlow,
                                      Double guess = DefaultGuess,
                                      int maxIterations = MaxIterations)
        {
            const Double bracketStep = 0.5;
            var leftBracket = guess - bracketStep;
            var rightBracket = guess + bracketStep;
            var i = 0;
            while (f(cashFlow, leftBracket)*f(cashFlow, rightBracket) > 0 && i++ < maxIterations)
            {
                leftBracket -= bracketStep;
                rightBracket += bracketStep;
            }

            return i >= maxIterations
                       ? new Brackets(0, 0)
                       : new Brackets(leftBracket, rightBracket);
        }
    }

    public struct CashItem
    {
        public DateTime Date;
        public Double Amount;

        public CashItem(DateTime date, Double amount)
        {
            Date = date;
            Amount = amount;
        }
    }
}

}

Answer 3

Thanks to contributors of the nuget package located at Excel Financial Functions. It supports many financial methods - AccrInt, Irr, Npv, Pv, XIrr, XNpv, etc.,

1. Install and import the package.
2. As all the methods are static in Financial class, directly call specific method as Financial.<method_name> with required parameters.

Example:

using Excel.FinancialFunctions;

namespace ExcelXirr
{
    class Program
    {
        static void Main(string[] args)
        {
            List<double> valList =new List<double>();
            valList.Add(4166.67);
            valList.Add(-4166.67);
            valList.Add(-4166.67);
            valList.Add(-4166.67);
            List<DateTime> dtList = new List<DateTime>();
            dtList.Add(new DateTime(2014, 9, 1));
            dtList.Add(new DateTime(2014, 10, 1));
            dtList.Add(new DateTime(2014, 11, 1));
            dtList.Add(new DateTime(2014, 12, 1));
            double result = Financial.XIrr(valList, dtList);
            Console.WriteLine(result);
            Console.ReadLine();
        }
    }
}

Result is same as Excel.

Answer 4

The other answers show how to implement XIRR in C#, but if only the calculation result is needed you can call Excel's XIRR function directly in the following way:

First add reference to Microsoft.Office.Interop.Excel and then use the following method:

    public static double Xirr(IList<double> values, IList<DateTime> dates)
    {
        var xlApp = new Application();

        var datesAsDoubles = new List<double>();
        foreach (var date in dates)
        {
            var totalDays = (date - DateTime.MinValue).TotalDays;
            datesAsDoubles.Add(totalDays);
        }

        var valuesArray = values.ToArray();
        var datesArray = datesAsDoubles.ToArray();

        return xlApp.WorksheetFunction.Xirr(valuesArray, datesArray);
    }

Answer 5

This repo from GitHub - klearlending/XIRR has sample code on how to calculate XIRR.

The author also provided a blogpost XIRR-demystified, that explains the logic and reasoning.

So far that lib is giving close to accurate results for me. (Still exploring it and forked it for personal use)