DESIGN AND DEVELOPMENT OF MATHEMATICAL MODELS FOR FINANCIAL FORECASTING

Making educated judgements in the complex and unpredictably changing world of finance depends critically on the construction and use of mathematical models for financial forecasting. The main components of developing such models are briefly summarised in this abstract. Using historical data and pertinent variables, financial forecasting entails making predictions about future financial outcomes, such as stock prices, market trends, economic indicators, or firm performance. In order to analyse and understand this data in a systematic manner and provide reliable forecasts, forecasters use mathematical models. Time series analysis, analysis of regression, random models, and artificial intelligence algorithms are just a few of the mathematical methods used. These models are created specifically to meet the demands of the forecasting work, taking into account the type of information, the time horizon, and the desired level of accuracy. Parameter calculation, fitting the model, and validation are all aspects of model development. Optimization methods are used to estimate the parameters, and a framework is then fitted utilizing the available data. The model must be validated in order to be evaluated for effectiveness and reliability in making future predictions. The last mathematical model is used to make predictions. It can be applied to forecast future financial variables, analyse risks, gauge investment potential, and aid in decision-making. To account for shifting market conditions and assure the reliability of the forecasts, the model must be regularly monitored and updated.