Financial modeling

Financial modeling [1] is the task of building an abstract representation (a model) of a real world financial situation.[2] 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.

Typically, then, financial modeling is understood to mean an exercise in either asset pricing or corporate finance of a quantitative nature. It involves translating a set of hypotheses about the behavior of markets or agents into numerical predictions.[3] At the same time, "financial modeling" is a general term that means different things to different users; the reference usually relates either to accounting and corporate finance applications or to quantitative finance applications.

Accounting

In corporate finance and the accounting profession, financial modeling typically entails financial statement forecasting; usually the preparation of detailed company-specific models used for [2] decision making purposes, valuation and financial analysis. [1] In entrepreneurial and investment contexts, financial models are widely used to illustrate business viability and capital requirements for funding discussions.[4]

Applications include:

To generalize as to the nature of these models: firstly, as they are built around financial statements, calculations and outputs are monthly, quarterly or annual; secondly, the inputs take the form of "assumptions", where the analyst specifies the values that will apply in each period for external / global variables (exchange rates, tax percentage, etc....; may be thought of as the model parameters), and for internal / company specific variables (wages, unit costs, etc....). Correspondingly, both characteristics are reflected (at least implicitly) in the mathematical form of these models

Quantitative finance

In quantitative finance, financial modeling entails the development of a sophisticated mathematical model.[25] Models here deal with asset prices, market movements, portfolio returns and the like.

Relatedly, applications include:

These problems are generally stochastic and continuous in nature, and models here thus require complex algorithms, entailing computer simulation, advanced numerical methods (such as numerical differential equations, numerical linear algebra, dynamic programming) and/or the development of optimization models. The general nature of these problems is discussed under, while specific techniques are listed under. For further discussion here see also: Brownian model of financial markets; Martingale pricing; Financial models with long-tailed distributions and volatility clustering; Extreme value theory; Historical simulation (finance).

Modellers are generally referred to as "quants", i.e. quantitative analysts (or "rocket scientists") and typically have advanced (Ph.D. level) backgrounds in quantitative disciplines such as statistics, physics, engineering, computer science

Competitive modeling

Several financial modeling competitions exist, emphasizing speed and accuracy in modeling. The Microsoft-sponsored ModelOff Financial Modeling World Championships were held annually from 2012 to 2019, with competitions throughout the year and a finals championship in New York or London. After its end in 2020, several other modeling championships have been started, including the Financial Modeling World Cup and Microsoft Excel Collegiate Challenge, also sponsored by Microsoft.[34]

Philosophy of financial modeling

Philosophy of financial modeling is a branch of philosophy concerned with the foundations, methods, and implications of modeling science.

In the philosophy of financial modeling, scholars have more recently begun to question the generally held assumption that financial modelers seek to represent any "real-world" or actually ongoing investment situation. Instead, it has been suggested that the task of the financial modeler resides in demonstrating the possibility of a transaction in a prospective investment scenario, based on a limited set of possibility conditions initially assumed in the model.[35]

See also

• All models are wrong
• Asset pricing model
• Economic model
• Financial engineering
• Financial forecast
• Financial Modelers' Manifesto
• Financial models with long-tailed distributions and volatility clustering
• Financial planning
• Integrated business planning
• Model audit
• Modeling and analysis of financial markets
• Profit model
• Return on modeling effort

Bibliography

General

Corporate finance

Quantitative finance