The aim of this diploma thesis is to analyze the development of the total volume of debt in the Czech Republic and the analysis separately for the household sector and non-financial corporations. From economic theoretical assumptions it can be concluded that there is a correlation between the amount of loans and GDP development or between credit and economic cycle. The thesis is divided into three parts. The first part made up of chapters 1 to 4, describes the theory used further in the text. The second part, Chapter 5, describes the specific time series used in the thesis, i.e. The time series of the volume of debt for the Czech Republic, GDP and interest rates. Interest rates and the volume of debt are further broken down by maturity and also by two selected sectors. The last part, Chapter 6, focusing on co-integration analysis, ADL and error correction models, attempts to capture short-term and long-term relationships between the time series.

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Following the debate by empirical finance research on the presence of non-linear predictability in stock market returns, this study examines forecasting abilities of nonlinear STAR-type models. A non-linear model methodology is applied to daily returns of FTSE, S&P, DAX and Nikkei indices. The research is then extended to long-horizon forecastability of the four series including monthly returns and a buy-and-sell strategy for a three, six and twelve month holding period using non-linear error-correction framework. The recursive out-of-sample forecast is performed using the present value model equilibrium methodology, whereby stock returns are forecasted using macroeconomic variables, in particular the dividend yield and price-earnings ratio. The forecasting exercise revealed the presence of non-linear predictability for all data periods considered, and confirmed an improvement of predictability for long-horizon data. Finally, the present value model approach is applied to the housing market, whereby the house price returns are forecasted using a price-earnings ratio as a measure of fundamental levels of prices. Findings revealed that the UK housing market appears to be characterised with asymmetric non-linear dynamics, and a clear preference for the asymmetric ESTAR model in terms of forecasting accuracy.

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