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The skills required of a financial rocket scientist are broadly based. These include knowledge of microeconomics, macroeconomics, [6] pure mathematics, [2] statistics, information technologies and financial market practice. [7] The microeconomics knowledge is necessary because the firm itself is an entity subject to microeconomics laws. [8]
Social studies of finance is an interdisciplinary research area that combines perspectives from anthropology, economic sociology, science and technology studies, international political economy, behavioral finance, and cultural studies in the study of financial markets and financial instruments. Work in social studies of finance emphasizes the ...
Financial engineering is a multidisciplinary field involving financial theory, methods of engineering, tools of mathematics and the practice of programming. [3] It has also been defined as the application of technical methods, especially from mathematical finance and computational finance, in the practice of finance.
Computational finance is a branch of applied computer science that deals with problems of practical interest in finance. [1] Some slightly different definitions are the study of data and algorithms currently used in finance [ 2 ] and the mathematics of computer programs that realize financial models or systems .
The key financial insight behind the model is that one can perfectly hedge the option by buying and selling the underlying asset in just the right way and consequently "eliminate risk", absenting the risk adjustment from the pricing (, the value, or price, of the option, grows at , the risk-free rate).
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Mathematical finance, also known as quantitative finance and financial mathematics, is a field of applied mathematics, concerned with mathematical modeling in the financial field. In general, there exist two separate branches of finance that require advanced quantitative techniques: derivatives pricing on the one hand, and risk and portfolio ...
The potential of modern financial economics theory to complement existing actuarial science was recognized by actuaries in the mid-twentieth century. [11] In the late 1980s and early 1990s, there was a distinct effort for actuaries to combine financial theory and stochastic methods into their established models. [ 12 ]