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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 general, this literature shows that analysts do not produce better forecasts than simple forecasting models. [3] [4] (Additional to the above outline, for financial forecasts, analysts often also use specific financial historical information, such as the 52-week high of stock prices, to augment their analysis of stock prices. [5])
Forecasting performance appears to be time-dependent, where some exogenous events affect forecast quality. As expert forecasts are generally better than market-based forecasts, forecast performance depends on several factors: model, political economy , financial stability etc.
Naïve forecasts are the most cost-effective forecasting model, and provide a benchmark against which more sophisticated models can be compared. This forecasting method is only suitable for time series data. [17] Using the naïve approach, forecasts are produced that are equal to the last observed value.
Financial risk modeling is the use of formal mathematical and econometric techniques to measure, monitor and control the market risk, credit risk, and operational risk on a firm's balance sheet, on a bank's accounting ledger of tradeable financial assets, or of a fund manager's portfolio value; see Financial risk management.
Technical analysis is an analysis methodology for analysing and forecasting the direction of prices through the study of past market data, primarily price and volume. The efficacy of technical analysis is disputed by the efficient-market hypothesis , which states that stock market prices are essentially unpredictable, [ 5 ] and research on ...