Monte Carlo Options Pricing

A high-performance options pricing library and gRPC server built in C++ using Monte Carlo simulation methods.

Overview

This project provides a complete solution for pricing various types of financial options using Monte Carlo simulation. It consists of two main components:

• Core Library (lib/) - High-performance C++ pricing engine
• gRPC Server (server/) - Network-accessible pricing service with clients

Project Structure

MonteCarloLib/
├── lib/                          # Core Options Pricing Library
│   ├── include/                  # Public headers
│   ├── src/                      # Implementation
│   ├── tests/                    # Python tests
│   ├── build.sh                  # Build script
│   └── README.md                 # Library documentation
│
├── server/                       # gRPC Service
│   ├── protos/                   # Protocol buffer definitions
│   ├── server/                   # Server implementation
│   ├── client/                   # C++ and Python clients
│   ├── build.sh                  # Build script
│   └── README.md                 # Server documentation
│
└── README.md                     # This file

---

Core Library (lib/)

The core library provides a C API for pricing various option types using Monte Carlo simulation.

Features

Option Types:

• European (Call/Put)
• American (Call/Put)
• Asian (Arithmetic/Geometric)
• Barrier (Up/Down, In/Out)
• Lookback (Fixed/Floating Strike)
• Bermudan

Variance Reduction Techniques:

• Antithetic Variates
• Control Variates
• Stratified Sampling
• Importance Sampling

Performance:

• Optimized C++ implementation
• Multi-threaded support (planned)
• Typical pricing: 10-200ms for 100K simulations

Quick Start

cd lib
./build.sh --build --test

# Use in your code
#include "mcoptions.h"

auto ctx = mco_context_new();
mco_context_set_num_simulations(ctx, 100000);
double price = mco_european_call(ctx, 100.0, 100.0, 0.05, 0.2, 1.0);
mco_context_free(ctx);

→ Full Library Documentation

---

gRPC Server (server/)

A production-ready gRPC service that exposes the pricing library over the network, with built-in clients.

Features

Server:

• gRPC interface for all option types
• Real-time logging with colored output
• Graceful shutdown (Ctrl+C)
• Handles multiple concurrent clients
• Configurable variance reduction

Clients:

• C++ Client - Interactive menu + CLI support
• Python Client - Simple scripting interface

Quick Start

Terminal 1 - Start Server:

cd server
./build.sh --build --run-server

Terminal 2 - Run Client:

# Interactive mode
./build.sh --run-client

# CLI mode
./build/mcoptions_client --european-call --spot 100 --strike 100

# Python
./build.sh --run-python

→ Full Server Documentation

---

🚀 Installation

Prerequisites

For Library:

sudo apt install -y build-essential premake5 python3 python3-pip
pip3 install pytest cffi

For Server (additional):

sudo apt install -y protobuf-compiler libprotobuf-dev \
                    libgrpc++-dev libgrpc-dev protobuf-compiler-grpc
pip3 install grpcio grpcio-tools

Build Everything

# Build library
cd lib
./build.sh --clean --build --test

# Build server
cd ../server
./build.sh --clean --build

---

Usage Examples

Example 1: Library (C++)

#include "mcoptions.h"

int main() {
    auto ctx = mco_context_new();
    
    // Configure simulation
    mco_context_set_num_simulations(ctx, 100000);
    mco_context_set_antithetic(ctx, 1);
    mco_context_set_control_variates(ctx, 1);
    
    // Price an ATM European call
    double price = mco_european_call(ctx, 100.0, 100.0, 0.05, 0.2, 1.0);
    printf("Price: $%.4f\n", price);
    
    mco_context_free(ctx);
    return 0;
}

Example 2: gRPC Client (Python)

import grpc
import mcoptions_pb2
import mcoptions_pb2_grpc

channel = grpc.insecure_channel('localhost:50051')
stub = mcoptions_pb2_grpc.McOptionsServiceStub(channel)

request = mcoptions_pb2.EuropeanRequest(
    spot=100.0,
    strike=100.0,
    rate=0.05,
    volatility=0.20,
    time_to_maturity=1.0,
    config=mcoptions_pb2.SimulationConfig(
        num_simulations=100000,
        antithetic_enabled=True
    )
)

response = stub.PriceEuropeanCall(request)
print(f"Price: ${response.price:.4f}")

Example 3: Interactive Client

./build.sh --run-client

# Choose from menu:
#   1. Price European Call
#   2. Price European Put
#   3. Price American Call
#   ...
# Enter parameters with helpful defaults

---

Performance

Typical pricing times on modern hardware (100K simulations):

Option Type	Time (ms)	Variance Reduction
European	10-20	AV + CV
American	100-200	AV
Asian	15-30	AV + CV
Barrier	15-30	AV
Lookback	20-40	AV
Bermudan	150-250	AV

AV = Antithetic Variates, CV = Control Variates

---

Testing

Library Tests

cd lib
./build.sh --test
# Runs 39 tests covering all option types and variance reduction

Server Integration Test

# Terminal 1
cd server
./build.sh --run-server

# Terminal 2
./build.sh --run-client
# Or
./build.sh --run-python

---

📖 Documentation

• Library Documentation - Core API reference
• Server Documentation - gRPC service guide
• API Examples - Client code examples

---

🛠️ Architecture

┌─────────────────────────────────────────────┐
│           Client Applications               │
│  (C++, Python, Go, Java, etc.)             │
└─────────────────┬───────────────────────────┘
                  │ gRPC
                  ▼
┌─────────────────────────────────────────────┐
│          gRPC Server (server/)              │
│  - Request handling                         │
│  - Logging                                  │
│  - Validation                               │
└─────────────────┬───────────────────────────┘
                  │ C API
                  ▼
┌─────────────────────────────────────────────┐
│      Core Library (lib/)                    │
│  - Monte Carlo simulation                   │
│  - Variance reduction                       │
│  - Option pricing algorithms                │
└─────────────────────────────────────────────┘

---

Academic Reference

If you use this library in academic work, please consider citing:

@software{mcoptions2024,
  title = {Monte Carlo Options Pricing Library},
  author = {Your Name},
  year = {2024},
  url = {https://github.com/yourusername/MonteCarloLib}
}

---

Acknowledgments

• Built with gRPC
• Testing with pytest
• Build system: premake5

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