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  2. Monte Carlo methods in finance - Wikipedia

    en.wikipedia.org/wiki/Monte_Carlo_methods_in_finance

    [6]) In terms of financial theory, this, essentially, is an application of risk neutral valuation; [7] see also risk neutrality. Applications: In Corporate Finance , [ 8 ] [ 9 ] [ 10 ] project finance [ 8 ] and real options analysis , [ 1 ] Monte Carlo Methods are used by financial analysts who wish to construct " stochastic " or probabilistic ...

  3. Mathematical finance - Wikipedia

    en.wikipedia.org/wiki/Mathematical_finance

    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 ...

  4. Financial modeling - Wikipedia

    en.wikipedia.org/wiki/Financial_modeling

    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.

  5. Stock-flow consistent model - Wikipedia

    en.wikipedia.org/wiki/Stock-Flow_consistent_model

    The set of equations in the model defines relationship between different variables, not determined by the accounting framework. The model structure basically helps in understanding how the flows are connected from a behavioral perspective or in simple words how the behavior of a sector affects the flow of funds in the system, e.g., the factors ...

  6. Polynomial regression - Wikipedia

    en.wikipedia.org/wiki/Polynomial_regression

    In statistics, polynomial regression is a form of regression analysis in which the relationship between the independent variable x and the dependent variable y is modeled as an nth degree polynomial in x. Polynomial regression fits a nonlinear relationship between the value of x and the corresponding conditional mean of y, denoted E(y |x).

  7. Ordinary least squares - Wikipedia

    en.wikipedia.org/wiki/Ordinary_least_squares

    In statistics, ordinary least squares (OLS) is a type of linear least squares method for choosing the unknown parameters in a linear regression model (with fixed level-one [clarification needed] effects of a linear function of a set of explanatory variables) by the principle of least squares: minimizing the sum of the squares of the differences between the observed dependent variable (values ...

  8. JoJo Siwa 'Pledged' Not to Share Dating Life Publicly After ...

    www.aol.com/jojo-siwa-pledged-not-share...

    Following her time on the reality show, Siwa found success upon signing on with Nickelodeon. She acted in many of the network's shows and television films, including The Thundermans and School of ...

  9. Autoregressive conditional heteroskedasticity - Wikipedia

    en.wikipedia.org/wiki/Autoregressive_conditional...

    In a sample of T residuals under the null hypothesis of no ARCH errors, the test statistic T'R² follows distribution with q degrees of freedom, where ′ is the number of equations in the model which fits the residuals vs the lags (i.e. ′ =).