Codezerg.AlgoTrader

A C# algorithmic trading library for post-market stock strategy evaluation and backtesting.

Features

• Strategy Framework: Clean, event-driven architecture for implementing trading strategies
• Technical Indicators: Built-in SMA, EMA, RSI, MACD, Bollinger Bands, ATR
• Backtesting Engine: Full-featured backtesting with performance metrics
• Multiple Data Sources: CSV files and EODHD API support
• Performance Analytics: Sharpe ratio, max drawdown, win rate, profit factor, and more

Design Constraints

AlgoTrader is intentionally designed with specific constraints to focus on strategy evaluation:

Constraint	Description
Cash accounts only	No margin trading
Long positions only	No short selling
Daily timeframe and above	D1, W1, MN1 only
Bar data only	No tick data support
Complete fills only	No partial order fills
Post-market execution	Orders execute at bar close

Installation

NuGet Package

dotnet add package Codezerg.AlgoTrader

Or via the Package Manager:

Install-Package Codezerg.AlgoTrader

Requirements

• .NET 8.0 or later
• (Optional) EODHD API key for live data

Build from Source

dotnet build

Run Tests

dotnet test

Quick Start

1. Create a Strategy

using AlgoTrader.Indicators; using AlgoTrader.Strategy; public class GoldenCrossStrategy : StrategyBase { private iSMA? _fastMa; private iSMA? _slowMa; // Anchor symbol - determines when OnEvaluate() fires public override string Symbol => "SPY"; protected override void OnInit() { // Initialize indicators _fastMa = new iSMA(Close, 50); _slowMa = new iSMA(Close, 200); } protected override void OnEvaluate() { // Update indicators _fastMa!.Update(); _slowMa!.Update(); if (!_fastMa.Ready || !_slowMa.Ready) return; // Golden cross: fast MA crosses above slow MA var goldenCross = _fastMa[1] <= _slowMa[1] && _fastMa[0] > _slowMa[0]; // Death cross: fast MA crosses below slow MA var deathCross = _fastMa[1] >= _slowMa[1] && _fastMa[0] < _slowMa[0]; if (goldenCross && !HasPosition(Symbol)) { var shares = SharesForAmount(Symbol, EquityPercent(95m)); if (shares > 0) Buy(Symbol, shares); } else if (deathCross && HasPosition(Symbol)) { ClosePosition(Symbol); } } }

2. Run a Backtest

using AlgoTrader.Broker; using AlgoTrader.Core; using AlgoTrader.Data; // Create data provider (CSV or EODHD) var dataProvider = new CsvDataProvider("./data"); // Or: var dataProvider = new EodhdDataProvider(apiKey); // Create broker with initial capital var broker = new BacktestBroker(100_000m, commissionPerShare: 0.01m); // Configure engine var config = new EngineConfig { Timeframe = Timeframe.D1, WarmupBars = 200 // Allow indicators to initialize }; var engine = new Engine(dataProvider, broker, config); engine.AddStrategy(new GoldenCrossStrategy()); // Run backtest var result = await engine.RunAsync("2020-01-01", "2024-12-31"); // Print results Console.WriteLine(result.Summary());

3. View Results

═══════════════════════════════════════════════════════════════ BACKTEST RESULTS ═══════════════════════════════════════════════════════════════ Period: 2020-01-01 to 2024-12-31 Initial Equity: $100,000.00 Final Equity: $142,350.00 ─────────────────────────────────────────────────────────────── RETURNS ─────────────────────────────────────────────────────────────── Total Return: 42.35% ($42,350.00) Annualized: 8.47% ─────────────────────────────────────────────────────────────── RISK ─────────────────────────────────────────────────────────────── Sharpe Ratio: 0.85 Max Drawdown: 15.23% ($15,230.00) ─────────────────────────────────────────────────────────────── TRADES ─────────────────────────────────────────────────────────────── Total Trades: 12 Win Rate: 58.33% (7W / 5L) Profit Factor: 2.15

Architecture

Strategy Layer (user strategies) ↓ Engine Layer (orchestrates execution) ↓ ┌───┴───┐ ↓ ↓ Data Broker

Project Structure

src/AlgoTrader/ ├── Core/ # Engine, types, events, configuration ├── Domain/ # Bar, Order, Position, Account ├── Data/ # DataSeries, SymbolData, providers ├── Broker/ # IBroker, BacktestBroker, Trade ├── Strategy/ # StrategyBase, StrategyContext ├── Indicators/ # SMA, EMA, RSI, MACD, Bands, ATR └── Analysis/ # Metrics, BacktestResult examples/ # Example strategies tests/ # Unit tests

Strategy Development

Strategy Lifecycle

public class MyStrategy : StrategyBase { public override string Symbol => "SPY"; // Anchor symbol protected override void OnInit() { // Called once at start - initialize indicators } protected override void OnEvaluate() { // Called after each bar - implement trading logic } protected override void OnDeinit() { // Called once at end - cleanup } }

Data Access

Data is accessed using reverse indexing where 0 is the most recent bar:

// Anchor symbol data (shorthand) Close[0] // Current bar close Close[1] // Previous bar close Open[0] // Current bar open High[0] // Current bar high Low[0] // Current bar low Volume(0) // Current bar volume // Multi-symbol data access Data["AAPL"].Close[0] // AAPL current close Data["MSFT"].High[1] // MSFT previous high

Trading Functions

// Submit orders Buy(symbol, quantity); // Market buy Buy(symbol, quantity, price, OrderType.Limit); // Limit buy Sell(symbol, quantity); // Market sell ClosePosition(symbol); // Close entire position // Position info HasPosition(symbol) // Check if has position OR pending buy PositionSize(symbol) // Current shares held // Sizing helpers EquityPercent(50m) // 50% of current equity SharesForAmount(symbol, amount) // Shares purchasable for amount

Order Flow

Orders placed in OnEvaluate() are queued and execute after the method returns:

OnEvaluate() called ↓ Buy/Sell orders queued ↓ OnEvaluate() returns ↓ Orders execute at bar close price ↓ Next bar begins

Use HasPosition(symbol) to check both existing positions AND pending buy orders, preventing duplicate orders in the same evaluation cycle.

Indicators

All indicators use the i prefix naming convention:

Indicator	Class	Description
SMA	iSMA	Simple Moving Average
EMA	iEMA	Exponential Moving Average
RSI	iRSI	Relative Strength Index (Wilder's smoothing)
MACD	iMACD	Moving Average Convergence Divergence
Bollinger Bands	iBands	Bollinger Bands (SMA +/- std dev)
ATR	iATR	Average True Range

Usage Example

protected override void OnInit() { // Moving averages var sma = new iSMA(Close, 20); var ema = new iEMA(Close, 12); // RSI var rsi = new iRSI(Close, 14); // MACD var macd = new iMACD(Close, 12, 26, 9); // Bollinger Bands var bands = new iBands(Close, 20, 2.0m); // ATR (requires SymbolData) var atr = new iATR(Data["SPY"], 14); } protected override void OnEvaluate() { // Update indicators sma.Update(); ema.Update(); rsi.Update(); macd.Update(); bands.Update(); atr.Update(); // Access values if (sma.Ready) { var currentSma = sma[0]; var previousSma = sma[1]; } // MACD lines if (macd.Ready) { var macdLine = macd.Main[0]; var signalLine = macd.Signal[0]; var histogram = macd.Histogram[0]; } // Bollinger Bands if (bands.Ready) { var upper = bands.Upper[0]; var middle = bands.Middle[0]; var lower = bands.Lower[0]; } }

Data Providers

CSV Data Provider

Reads from local CSV files with naming convention {SYMBOL}_{TIMEFRAME}.csv:

data/ ├── SPY_D1.csv ├── AAPL_D1.csv └── MSFT_D1.csv

CSV Format:

date,open,high,low,close,volume 2020-01-02,323.54,324.89,322.53,324.87,32145000 2020-01-03,321.16,323.64,321.05,322.41,36156000

Usage:

var provider = new CsvDataProvider("./data");

EODHD Data Provider

Fetches data from the EODHD API:

// Set environment variable // Windows: set EODHD_API_KEY=your_api_key // Linux/Mac: export EODHD_API_KEY=your_api_key var apiKey = Environment.GetEnvironmentVariable("EODHD_API_KEY"); await using var provider = new EodhdDataProvider(apiKey);

Account State Persistence

Account state (balance, positions, orders, trades) can be saved and loaded for two main use cases:

1. Backtesting/Development - Resume backtests or analyze results
2. Daily Execution - Load state, execute latest bar, save state

using Codezerg.AlgoTrader.Domain; // Load existing account or create new one Account account; if (File.Exists("account.json")) account = Account.LoadFromFile("account.json"); else account = new Account(100_000m); // Create broker with the account var broker = new BacktestBroker(account, commissionPerShare: 0.01m); // ... run strategy ... // Save account state account.SaveToFile("account.json");

Saved State Format (JSON):

{ "Balance": 95234.50, "Positions": [ { "Symbol": "SPY", "Quantity": 100, "AvgPrice": 450.25, "OpenedAt": "2024-01-15T00:00:00Z", "MarketPrice": 455.80 } ], "Orders": [], "Trades": [ { "OrderId": "abc-123", "Symbol": "SPY", "Side": "Buy", "Quantity": 100, "Price": 450.25, "Timestamp": "2024-01-15T00:00:00Z", "Commission": 1.00, "Pnl": 0 } ] }

Example Strategies

The examples/ directory contains ready-to-use strategies:

Strategy	Description
BuyAndHoldStrategy	Simple benchmark - buy once and hold
GoldenCrossStrategy	50/200 SMA crossover
MeanReversionStrategy	RSI oversold/overbought with trend filter
MomentumStrategy	Multi-symbol momentum rotation

Running Examples

# Set API key (required for EODHD data) export EODHD_API_KEY=your_api_key # Run default example dotnet run --project examples/Codezerg.AlgoTrader.Examples.csproj # Run stateful example (demonstrates account persistence) dotnet run --project examples/Codezerg.AlgoTrader.Examples.csproj -- --stateful

Performance Metrics

The backtest result includes comprehensive metrics:

Metric	Description
Total Return	Percentage and dollar return
Annualized Return	Compound annual growth rate
Sharpe Ratio	Risk-adjusted return (assumes 2% risk-free rate)
Max Drawdown	Largest peak-to-trough decline
Total Trades	Number of completed round trips
Win Rate	Percentage of profitable trades
Profit Factor	Gross profit / gross loss
Average Win/Loss	Mean winning/losing trade
Largest Win/Loss	Best/worst single trade
Total Commission	Sum of all commissions paid

Type Conventions

• Prices: Use decimal (not float/double) for all monetary values
• Timestamps: Use DateTime for all time-related values
• Bar: Immutable record type
• Order/Position: Mutable classes with state management
• Broker: Async interface (HTTP-ready design)

Configuration

var config = new EngineConfig { Timeframe = Timeframe.D1, // D1, W1, or MN1 WarmupBars = 200 // Bars before trading starts };

License

MIT License - see LICENSE file for details.

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Run tests: dotnet test
5. Submit a pull request