No description available.

Moderne statistische und ökonometrische Methoden behandeln erfolgreich stilisierte Fakten auf den Finanzmärkten. Die vorgestellten Techniken erstreben die Dynamik von Finanzmarktdaten genauer als traditionelle Ansätze zu verstehen. Wirtschaftliche und finanzielle Vorteile sind erzielbar. Die Ergebnisse werden hier in praktischen Beispielen ausgewertet, die sich vor allem auf die Prognose von Finanzmarktdaten fokussieren. Unsere Anwendungen umfassen: (i) die Modellierung und die Vorhersage des Liquiditätsangebotes, (ii) die Lokalisierung des ’Multiplicative Error Model’ und (iii) die Erbringung von Evidenz für den empirischen Zustandsfaktorparadox über Landern. / Modern methods in statistics and econometrics successfully deal with stylized facts observed on financial markets. The presented techniques aim to understand the dynamics of financial market data more accurate than traditional approaches. Economic and financial benefits are achievable. The results are here evaluated in practical examples that mainly focus on forecasting of financial data. Our applications include: (i) modelling and forecasting of liquidity supply, (ii) localizing multiplicative error models and (iii) providing evidence for the empirical pricing kernel paradox across countries.

Recent nancial crises have highlighted the sensitivity and vulnerability of nancial markets to in ation, which reduces the value of money and a ects the net returns of nancial instruments. In response to this, investors who are concerned with maintaining their investment's purchasing power rather than its market value are resorting to in ation linked (IL) products to hedge their in ation risk. Consequently, the in ation market has been rapidly growing for the last decade and has further great potential growth worldwide. It is highly probable that in ation linked derivatives will eventually be as common as conventional products. Another cause of the in ation market boost is the growing extension of the time frame of nancial transactions, which has generated an increase in in ation expectation; since 1980 the average time to maturity of long-dated transactions went from one decade to three decades. This is, in part, due to the ageing population in the developed world. This research investigates some alternative models in order to improve the match between model prices and observed prices in the American and South African in ation markets. It takes into account the relative illiquidity of IL products. The main tools used are L evy distributions, macroeconomic factors, no-arbitrage and pricing kernel models. L evy processes can replicate the behaviour of the return innovations of a wide range of nancial securities. Adding a stochastic time change to the L evy process randomises the market clock, thus generating stochastic volatilities, higher stochastic return moments and eventually stochastic skewness. These are observed stylised facts most conventional models do not achieve. Moreover, in contrast to the hidden factor approach, each L evy process component and its stochastic time change can readily be assigned an economic meaning. This explicit economic mapping facilitates the interpretation of current models and provides a more intuitive approach to building new models that capture other observed behaviours. Finally, L evy processes also provide tractable formulas for derivative pricing and market estimations. In general, in ation is a consequence of macroeconomic factors. Exogenous dynamics of the most signi cant of these factors are used to deduce the endogenous in ation dynamics in some of the considered models. In these cases, the calibration of the pricing kernel models requires little historical data on IL derivatives. In fact, the required macroeconomic historical data is easily available because of the current national and international legislation.

Seit der Entdeckung der arbitragefreien Bewertung hat sich das Gebiet finance grundlegend geändert - sowohl in der Theorie als auch in der Anwendung. Märkte für Derivate haben sich entwickelt und Optionen dienen heutzutage als Basis- und als Absicherungsinstrumente. In dieser Dissertation betrachten wir einige Märkte für Aktienderivate. Wir beginnen mit statistischen Analysen des Marktes für europäische Optionen und des Marktes für Varianzswaps, weil diese Produkte die hauptsächlichen Absicherungsinstrumente für komplexe Optionen sind. Dann betrachten wir verschiedene Optionspreismodelle und ihre Kalibrierung an beobachtete Preisoberflächen. Schließlich untersuchen wir die Verbindung zwischen Optionspreisen und dem grundlegenden ökonomischen Konzept der Risikoaversion anhand des empirischen Preiskernes. / Since the ideas of arbitrage free pricing were born, finance has changed radically - both in theory and practice. Derivatives markets have evolved and options serve nowadays as underlyings and as hedging instruments. In this thesis, we consider some markets for equity derivatives. We start by statistical analysis of the markets for European options and variance swaps because these products are important for hedging more complex claims. Then we consider different option pricing models and their calibration to observed price surfaces. Finally, we investigate the connection between option prices and the fundamental economic concept of risk aversion by the empirical pricing kernel.

Thesis focus on derivation of macro-finance model for analysis of yield curve and its dynamics using macroeconomic factors. Underlying model is based on basic Dynamic Stochastic General Equilibrium DSGE approach that stems from Real Business Cycle theory and New Keynesian Macroeconomics. The model includes four main building blocks: households, firms, government and central bank. Log-linearized solution of the model serves as an input for derivation of yield curve and its main determinants -- pricing kernel, price of risk and affine term structure of interest rates -- based on no-arbitrage assumption. The Thesis shows a possible way of consistent derivation of structural macro-finance model, with reasonable computational burden that allows for time varying term premia. A simple VAR model, widely used in macro-finance literature, serves as a benchmark. The paper also presents a brief comparison and shows an ability of both models to fit an average yield curve observed from the data. Lastly, the importance of term structure analysis is demonstrated using case of Central Bank deciding about policy rate and Government conducting debt management.