As its name suggests, Financial Engineering is the marriage of two key ancient concepts, finance and engineering, that uses mathematical techniques, finance theories, and advanced software engineering techniques to solve crucial, difficult financial problems. Financial engineers are specialists who apply mathematical formulas, programming techniques, and engineering methods in finance theory, as well as analyze market trends, in order to construct data-backed financial models. Many financial engineers utilize algorithms, mathematical rules, and computing to help them in solving financial problems, which has also earned them the title computational engineers.
Financial engineers apply tools and knowledge from computer science, statistics, economics, and applied mathematics fields to address ongoing financial problems, and to develop new and innovative financial products. Using mathematical modeling and computing, financial engineers are able to test and release new tools, such as new methods for analyzing investments, new debt offerings, new investments, new trading strategies, new financial models, and so on. Financial engineering is a multidisciplinary field utilizing computational intelligence, mathematical finance, and statistical modelling to analyze and predict market activities in order to make better investment, trading, and hedging decisions. A multidisciplinary field, Financial engineering uses knowledge from computational science and mathematics of finance to determine potentials and risks of a financial investment instrument.
While financial engineering uses stochastic, modeling, and analytical techniques to develop and deploy novel financial processes for solving problems in finance, this field also generates novel strategies for companies to utilize in order to maximise their business profits. Engineering is the practical application of mathematical or scientific principles to solve problems or to develop useful products and services. An example of financial engineering in practice is the work of quant analysts–usually called quants–who design things like algorithmic or AI trading programs, which are used on the financial markets. Various fields, such as economics, mathematics, computer science, and finance theory, are integrated and used in developing algorithmic or artificial intelligence trading programs that are used in the financial markets.
The difference between quantitative finance and financial engineering is that quants, or quants, are experts who focus on one specific niche of finance (usually the implementation of complex models), whereas financial engineers are practitioners who have broad-based expertise and who apply mathematical techniques to problem solving. Companies frequently hire individuals who have advanced degrees in Financial Engineering, and these specialists serve as investment managers, bankers, or traders using their background in financial engineering to enhance the quality of existing investment products. Investment banks apply financial engineering techniques to problems like developing new products, derivative securities valuation, structuring portfolios, managing risks, and modeling scenarios. Financial engineering (MS) uses tools from finance and economics, engineering, applied mathematics, and statistics to solve problems like derivative securities valuation, strategic planning and dynamic investment strategies, and risk management, of interest to investment banks and commercial banks, trading firms, hedge funds, insurance companies, corporate risk managers, and regulatory agencies.
Using quantitative methods, innovative concepts of strategic planning, and responsible risk management, the concept of financial engineering integrates aspects of mathematics and finance and prepare students for senior positions in finance.