Leveraging Modern C++ in Quantitative Finance
summary
Shows a concrete Monte Carlo option pricer implemented with C++11/C++17 features: Mersenne Twister 64 engine, standard normal distribution, lambda-driven path generator, and std::async futures to launch many independent scenarios. Uses 10k–100k scenarios, compares serial vs task-based concurrency on a 24-core VM and reports up to ~90% runtime improvement as time steps and scenarios grow. Demonstrates Boost tools (probability distributions, quadrature, circular_buffer, multi_array) and posts full code on GitHub.
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chapters (20)
- 0:00Introduction
- 1:13Endusers
- 6:20Boost
- 10:53Option Value
- 11:50Scenarios
- 13:00Stochastic Process
- 19:29Test Based Concurrency
- 25:02Virtual Machine
- 27:04More Complex Options
- 28:32Recap
- 29:49Boost libraries
- 30:56Probability distributions
- 32:45Standard library
- 33:57Numerical integration
- 36:02Circular Buffers
- 36:48Accumulators
- 37:13Multiarray
- 40:02References
- 40:36Contact Information
- 41:25Questions
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