Analysis of Pricing Models Volatility of Financial Assets

<p style="text-align: justify;">In modern conditions of general economic instability problems of forecasting profitability and risk assessment are becoming more relevant. Their decisions are implemented using tools of volatility.</p><p style="text-align: justify;">The first chapter of this work describes possible methods of volatility estimation and results in favor of the rationale for selecting the most effective model GARCH.</p><p style="text-align: justify;">In the second chapter model under study applied to the data of IT and petroleum companies, such as Apple Inc., IBM, Exxon Corporation and Chevron Corporation.</p><p style="text-align: justify;">The aim of this paper is a comparative analysis of efficiency of the volatility estimation model in the example of the world&#39;s largest petroleum and IT companies.</p><p style="text-align: justify;">The goal identified the following tasks:</p><ol><li style="text-align: justify;">To concretize the concept of volatility as the parameter variability of the financial market;</li><li style="text-align: justify;">To describe and systemize volatility estimation models;</li><li style="text-align: justify;">To assess the advantages and disadvantages of the methods for estimate and forecasting volatility, justify their preference for use in different conditions;</li><li style="text-align: justify;">To apply approaches to the estimation of volatility in the example of the world&#39;s largest petroleum and IT companies;</li><li style="text-align: justify;">To identify the role of volatility in the financial market.</li></ol><p style="text-align: justify;">The object of this study is the volatility of stock prices of companies, such as Apple Inc., IBM, Exxon Corporation, Chevron Corporation. In economy these companies are giants, ranking the first lines of the world ranking organizations.</p><p style="text-align: justify;">The subject of this research is mathematical models of volatility estimating. There are the estimators byParkinson, by Garman -Class rating, by Kunitomo (called &quot;the bridge&quot;) and GARCH-model.</p><p style="text-align: justify;">As the tools I used graphical and tabular presentation of statistics tools, analysis methods of forecasting, structural shifts, correlation analysis.</p><p style="text-align: justify;">The basis of research methodology is mathematical modeling. In this project I used methods of mathematical statistics and econometrics. In assessing the characteristics of the models under study applied software environment MATLAB, econometric package EViews, and Microsoft Excel.</p><p style="text-align: justify;">The information base of the work consists of studies of foreign and domestic authors in the application of volatility estimation models. All calculations are based on the use of open data base of quotes of Finam and statistics, taken directly from the official websites of firms under study.</p><p style="text-align: justify;">In my project I proved the importance and urgency of the problem of uncertainty and risk in the stock market. I presented the volatility as a measure of risk. Also volatility has been used as a characteristic of the forecasting of the market motion, And it helps to solve the problem of uncertainty.</p><p style="text-align: justify;">I described and analyzed volatility oscillators and in conclusion I selected GARCH- model in conjunction with &laquo;the bridge&raquo; by Kunitomo as the most effective way to estimate price volatility, which as a result gives of asymptotically accurate and unbiased estimates.</p><p style="text-align: justify;">In future I would like to continue research in this area and develop an analytical software module capable to predict return on assets and build a confidence interval for the prediction.</p>