Yao, David D. Department of Industrial Engineering and Operation Research, Columbia University, New York, New York.
Zhou, Xun Yu Mathematical Finance Section, Department of Systems Engineering and Engineering Management, Oxford University, Oxford, United Kingdom.
- Derivative pricing
- Portfolio optimization
- Links to Primary Literature
- Additional Readings
Engineering is about making a product (such as a laptop computer), designing a process (such as turning data into digital packets and transferring them on the Internet), or providing a solution (such as how to manage and optimize a firm's supply chain). Financial engineering (FE) is also concerned with products (such as options, futures, and other derivatives), processes (such as optimizing a portfolio over time, managing a pension or a hedge fund), and solutions (such as how to hedge against risks in exchange rates and in defaults). Engineering is built upon scientific laws and principles and makes extensive use of mathematical and computational tools. Financial engineering is no different, only with a slight variation; its guiding principles are drawn mainly from mathematical sciences and economics as opposed to physical sciences. Engineering design often starts with empirical data, continues with analysis and synthesis, and ends with some systemwide considerations regarding implementation and execution. Likewise, a sound FE model is usually well calibrated by data. Financial data are among the most widely available and most extensively studied data forms in a modern society. In implementation and execution as well as in design, FE uses many engineering ideas and practices. No engineering design is complete without carefully weighing the tradeoff between cost and benefit. In the same spirit, any FE product, process, or solution is ultimately a managed (or hedged) balance between risk and return.
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