The Impact of News on Systematic Risk

This graduate qualification work presents a comprehensive analysis dealing to construction of dynamic or "forward -looking" beta coefficients and to analyze the volatility of a systematic risk depending on news (past shocks of returns). First chapter is considered theoretical bases of studying of constructing dynamic beta coefficients and the influence of crises, news and other events on volatility of beta. Second chapter presents the statistical analysis of the study of the economy and the trading system of the UK stock market and the methodological foundations of construction and evaluation of dynamic betas. The third chapter shows the multidimensional statistical analysis of construction of systemic risk by OLS and CAPM. Dynamic beta was constructed by the Fama-Macbeth method with the rolling regression. Modeling of volatility of dynamic betas with high, medium and low capitalization occurs using ARMA and GARCH models (in accordance with Dickey-Fuller and KPSS stationarity tests, Jacques-Beer normality, Ljung-Box autocorrelation, autocorrelation transformation of Cochran-Orcutt). The modeling of relationship between the influence of macroeconomic factors on dynamic betas is the finishing step. The received results allow to draw a conclusion that the dynamic betas with different capitalization demonstrate the optimal APARCH, TARCH and Taylor/Schwert's GARCH models. The asymmetry of the APARCH model includes events that have both positive and negative effects. The TARCH-model of betas with average capitalization takes into account the effect of the lever, i.e. an unexpected drop in prices increases volatility more than an unexpected price increase. The Taylor/Schwert's GARCH model of low capitalization has a long memory, and the effect of large shocks has less effect than in the conventional GARCH model. Finally, macroeconomic factors such as CPI, GDP, the discount rate of Bank of England have various effects on dynamic beta with different capitalization.