Oct 17, 2011
Written by:
Al Hill
✓ Reviewed by Kunal Vakil, Co-Founder of TradingSim · Updated Mar 31, 2026
Computational finance is commonly referred to as financial engineering. This branch of finance relies on several factors such as, mathematical finance, computational intelligence, and simulations. These factors are necessary for making decisions in trading, risk management, and investments. Investors, stockholders, or any one who makes an investment can benefit from the principles of computational finance. People that work in the field of computational finance are often referred to as “quants” due to the fact that they need to have great quantitative skills to perform their job. Working in computational finance generally requires at least a masters degree and often times a PhD. There are many areas in which computational finance techniques are used including investment banking, risk management, strategic planning, collateralized debt obligation, and bargaining among others.
Financial Engineering and Rationality: An examination of the Monty Hall problem of financial engineering possibly effecting irrational agents.
International Association of Financial Engineers: A non–profit professional organization focused on promoting advancement in the quantitative finance profession.
MIT Laboratory for Financial Engineering: View research projects by the MIT research center whose focus is to sustain and to encourage computational finance and financial engineering research.
Financial Engineering with Mathematica: Six PDF documents of articles that are based on financial engineering.
Monte Carlo Simulation: An analysis on assessing financial value with the Monte Carlo simulation.
Computational Finance: A look at methods and challenges that can create financial opportunities.
Agent-based Computational Finance: Evaluation on the agent-based models in finance.
The Journal of Computational Finance: A quarterly computational finance journal published internationally.
Financial Engineering: Describes what financial engineering is and provides access to research conducted at McCormick.
Financial-Engineering and Financial-Accounting Perspectives: The McDonough School of Business and Goodes School of Business aim to bring two solutions for regulating instability in other comprehensive income.
Financial Engineering Tutorial: A start up tutorial for financial engineering professional fields.
Evolutionary Computation: A synopsis of the Shu-Heng Chen. Ph.D. article Evolutionary Computatuion: A Principle for Search.
Computational Intelligence: An explicit look at the history and the prominence of computational intelligence in finance.
An Introduction to Computational Finance: An in-depth 13-chapter guide to computational finance.
Introduction to Monte-Carlo Methods: A detailed introduction into the Monte-Carlo methods.
Miraculous Financing: A look at the financial crisis in America and what a change of financial engineering could have done to prevent it.
A Practioner’s Guide to Mathematical Finance: Mathematical finance overlaps computational finance and this guide simplifies mathematical finance.
Credit Enhancement through Financial Engineering: Details how credit enhancement can be achieved through financial engineering.
Developing Skills: Tips and advice for developing skills for successful financial engineering in the Asia-Pacific Economic Cooperation that can be utilized in other professional fields.
Computational Intelligence Society: A group that works to address real world issues with biologically motivated computational paradigms.
Computational Finance Resources: A great list of computational finance resources including software and technical reports.
Computational Finance History: An article explaining the history of the field of computational finance.
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Al Hill
Co-Founder & CEO, TradingSim
Alton Hill is the Co-Founder of TradingSim with over 18 years of trading experience. He completed the Design Thinking Bootcamp at Stanford’s D.School and brings expertise in Product Development to create the best trading simulation experience. His strategy focuses on trend-following systems, targeting high-volatility stocks with strong primary trends using the 15-minute chart.
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