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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 ...
Financial modeling is the task of building an abstract representation (a model) of a real world financial situation. [1] This is a mathematical model designed to represent (a simplified version of) the performance of a financial asset or portfolio of a business, project, or any other investment.
In sales and trading, quantitative analysts work to determine prices, manage risk, and identify profitable opportunities.Historically this was a distinct activity from trading but the boundary between a desk quantitative analyst and a quantitative trader is increasingly blurred, and it is now difficult to enter trading as a profession without at least some quantitative analysis education.
Monte Carlo methods are used in corporate finance and mathematical finance to value and analyze (complex) instruments, portfolios and investments by simulating the various sources of uncertainty affecting their value, and then determining the distribution of their value over the range of resultant outcomes.
Copula (probability theory) (§ Quantitative finance) Principal component analysis (§ Quantitative finance) Deterministic global optimization; Extended Mathematical Programming (§ EMP for stochastic programming) Genetic algorithm (List of genetic algorithm applications § Finance and Economics) Artificial intelligence:
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.
A major finding with ANNs and stock prediction is that a classification approach (vs. function approximation) using outputs in the form of buy (y=+1) and sell (y=-1) results in better predictive reliability than a quantitative output such as low or high price.
Quantitative strategies are offered in different type of fund structures: Hedge fund. The first quantitative funds were offered as hedge funds and not available to a broad public. The goal of those funds is to earn an absolute return with little constraints and freedom to apply leverage, shorting and derivatives. Mutual fund. With the ...