Vienas iš darbo tikslų yra apžvelgti rizikos sąvokos aiškinimus, jos rūšis, veiksnius bei vertinimo ir analizės metodus. Šio darbo tyrimo tikslas – vertinti pasirinktos įmonės X riziką pagal finansinių ataskaitų duomenis. Siekiant įvertinti įmonės riziką ateičiai, darbe prognozuosime 2007 -2008 metams statistinius įmonės dydžius: nuosavo kapitalo vertę, grynąjį pelną, įsipareigojimus, turtą ir kt. Pagal realius ir prognozuotus duomenis skaičiuosime finansinius rodiklius. Prognozes atliksime pagal tiesinius ir netiesinius prognozavimo metodus. / Risk is interpreted and explained very various. The risk is necessary in Lithuanian economical system, because the produce are begun to make earlier than demand begin to grow. The purpose of this work is to review interpretation of risk, it’s kinds, factors, methods of analysis and estimation. In this work, risk of the firm estimate by statistical data of financial accounts. We forecast statistical firm’s data: the capital, the net profit, the liabilities, the assets and etc.; for 2007 and 2008 years. We compute financial indexes by real and forecast data. In this work, we forecast number by trends with seasonal decompositions, curve of Regression, Moving Average method, Simple Exponential smoothing method, Autoregressive model and Autoregressive Integrated Moving Average (ARIMA) model. We use the statistical and analytical software package STATISTICA. After forecasting number of assets, liabilities we got that Polynomial trend with seasonal components is the best model for them. Logarithmical trend with seasonal components is the most infallible model for capital’s forecasting number. The best model for interest is Autoregressive model. The best model for net profit is Regression model. Risk of the firm is estimated by calculated financial indexes ROCE, ROA, ROI.

The aim of this study is to certify the legitimacy of employing quantitative methods in the day-to-day business practice. The task is approached as a case study of a real-life financial planning process. I work with the financial data of POS Media Czech Republic (a media company providing point-of-sale advertising solutions). My intention is to simulate the projection of a pro forma income statement with the use of quantitative methods. More specifically, I am applying time series prediction techniques in order to forecast POS Media's sales. The goal is, first, to demonstrate that quantitative techniques can be handled even with limited statistical background and, second, to discuss the relevancy of the obtained results. In the methodical part of my thesis I deal with the theoretical aspects of financial planning. I further describe various methods of sales forecasting (qualitative vs. quantitative). Special emphasis is put on time series prediction methods. In the application part I provide a short description of POS Media and its business. I use time series decomposition techniques to predict POS Media's sales in 2012. Consequently, I outline the rest of the pro forma income statement.