Aleksej.Finance 1.0.0

Aleksej.Finance

A comprehensive C# quantitative finance library with 180+ pure-math static methods and zero external dependencies. Every method is public static and takes explicit inputs — no state, no configuration, no side effects.

Built to back the Excel Finance Add-In and usable standalone in any .NET project.

Install

dotnet add package Aleksej.Finance

Target framework: .NET 6.0+

Modules

Options

using Aleksej.Finance.Options;

double call  = BlackScholes.Call(s: 100, k: 100, t: 1, r: 0.05, sigma: 0.20);  // ≈ 10.45
double delta = BlackScholes.Delta(100, 100, 1, 0.05, 0.20, isPut: false);        // ≈ 0.637
double iv    = BlackScholes.ImpliedVolatility(10.45, 100, 100, 1, 0.05, false);  // ≈ 0.200
double amPut = BinomialTree.Price(100, 100, 1, 0.05, 0.20, steps: 500, isPut: true, isAmerican: true);
double fxOpt = GarmanKohlhagen.Call(s: 1.10, k: 1.10, t: 0.5, r: 0.03, rf: 0.01, sigma: 0.10);
double barr  = ExoticOptions.BarrierCall(s: 100, k: 100, h: 120, t: 1, r: 0.05, sigma: 0.20, knockIn: false, isUp: true);
double futOpt = OptionsOnFutures.Call(f: 105, k: 100, t: 0.5, r: 0.05, sigma: 0.20);

Bonds

using Aleksej.Finance.Bonds;

double price   = BondMath.Price(face: 1000, couponRate: 0.05, ytm: 0.05, years: 10); // = 1000
double ytm     = BondMath.YieldToMaturity(950, 1000, 0.05, 10);
double mdur    = BondMath.ModifiedDuration(1000, 0.05, 0.05, 10);
double[] zeros = YieldCurve.Bootstrap(new[] { 0.5, 1.0, 1.5, 2.0 }, new[] { 0.04, 0.042, 0.044, 0.046 });
double payment = MortgageMath.Payment(principal: 500_000, annualRate: 0.065, years: 30); // monthly payment

Derivatives

using Aleksej.Finance.Derivatives;

double fwd  = ForwardFutures.FxForwardPrice(s: 1.10, r: 0.03, rf: 0.01, t: 1);   // ≈ 1.122
double par  = InterestRateSwap.ParSwapRate(new[] { 0.5, 1.0, 1.5, 2.0 }, new[] { 0.028, 0.030, 0.031, 0.032 });
double cap  = BlackModel.CapPrice(1_000_000, strike: 0.04, sigma: 0.20, paymentTimes, zeroRates, forwardRates, accrualFracs);
double vBond = ShortRateModels.VasicekBondPrice(r: 0.03, tau: 5, kappa: 0.15, theta: 0.05, sigma: 0.01);

Credit

using Aleksej.Finance.Credit;

double pd    = CreditDerivatives.MertonDefaultProbability(v: 100, d: 80, t: 1, r: 0.05, sigmaV: 0.25);
double cdsS  = CreditDerivatives.CdsFairSpread(hazardRate: 0.02, r: 0.03, maturity: 5); // ≈ 120bps
double dd    = CreditDerivatives.DistanceToDefault(100, 80, 1, 0.05, 0.25);

Portfolio

using Aleksej.Finance.Portfolio;

double[] mu  = Markowitz.MeanReturns(returns);       // returns is double[T, n]
double[,] cov = Markowitz.CovarianceMatrix(returns);
double[] wMV  = Markowitz.MinVariancePortfolio(cov);
double[] wMS  = Markowitz.MaxSharpePortfolioConstrained(mu, cov, riskFreeRate: 0.05);
double[] wRP  = Markowitz.RiskParityPortfolio(cov);

double pe     = EquityMetrics.PriceToEarnings(price: 150, eps: 6.25);          // 24×
double ev     = EquityMetrics.EnterpriseValue(marketCap: 500e9, debt: 50e9, cash: 30e9);
double kelly  = EquityMetrics.KellyCriterion(mu: 0.12, sigma: 0.20);           // f* = 3.0

double fee    = FeeCalculations.PerformanceFee(currentNav: 115, highWaterMark: 100,
                    previousNav: 100, carryRate: 0.20, hurdleRate: 0.08);
double carry  = FeeCalculations.CarriedInterest(totalDistributions: 200e6,
                    investedCapital: 100e6, preferredReturn: 0.08, holdingYears: 5);

double twr    = PerformanceAttribution.TimeWeightedReturn(new[] { 0.05, -0.02, 0.08 }); // ≈ 11.1%
double irr    = PerformanceAttribution.InternalRateOfReturn(
                    cashFlows: new[] { -1000.0, 200, 300, 400, 400 },
                    times:     new[] { 0.0, 1, 2, 3, 4 });

var (alloc, select, interact, active) = PerformanceAttribution.BhbAttribution(
    portfolioWeights, benchmarkWeights, portfolioReturns, benchmarkReturns);

Risk

using Aleksej.Finance.Risk;

double sharpe  = RiskMetrics.SharpeRatio(daily, riskFreeRateAnnual: 0.05);
double var95   = RiskMetrics.HistoricalVaR(daily, confidence: 0.95);
double sortino = RiskMetrics.SortinoRatio(daily, riskFreeRateAnnual: 0.05);
double beta    = RiskMetrics.Beta(portfolioReturns, benchmarkReturns);
double ir      = RiskMetrics.InformationRatio(portfolioReturns, benchmarkReturns);
double[] ewma  = VolatilityModels.EwmaVolatility(daily, lambda: 0.94);
double gFcast  = VolatilityModels.GarchForecast(currentVariance: 0.0001, omega: 0.000002,
                     alpha: 0.05, beta: 0.90, nDays: 10);

Design Principles

• Zero dependencies — no NuGet packages, no external libraries
• Pure functions — every method is public static, takes all inputs explicitly, no global state
• Numerically stable — Gaussian elimination with partial pivoting, Box-Muller transform, Abramowitz & Stegun CDF, Brent's method, Newton-Raphson
• Modular — outputs of one method are valid inputs to another: YieldCurve.Bootstrap() → InterestRateSwap.SwapValue() → InterestRateSwap.DV01()

Build from Source

git clone https://github.com/aleksejcupic/aleksej-finance
cd aleksej-finance
dotnet build
dotnet pack --configuration Release

Author

Aleksej Cupic · aleksejcupic.com · LinkedIn