Contributions published at Financial Economics (Thorsten Hens)

We analyze the forecasting ability of financial variables to predict the state of the Swiss business cycle up to eight quarters ahead. Overall, our results suggest that financial variables convey leading information for the prediction of business cycles, even when applied to a small open economy. However, we clearly find that model specifications need to be extended to include variables accounting for external shocks, such as exchange rates or international commodity prices. It also appears that the forecasting contribution of individual variables changes over time. Specifically, in the last two decades, stock market liquidity has replaced the term spread as the best single predictor.

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Market frictions inhibit the perfect replication of property derivatives, and define the property spread as a price measure in the incomplete real estate market. We identify transaction costs, transaction time, and short sale constraints as the main frictions in this market. Based on these frictions, we set up a framework of arbitrage free price bounds for property derivatives. In turn, we use observed derivative prices to determine the implied cost of the frictions. Lastly, we verify these values by using other research, which confirms the accuracy of our framework.

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Lehren die Universitäten die Fähigkeiten, die in der Praxis gefragt sind? UBS-Personalchef Gery Bruederlin und Finanzprofessor Thorsten Hens im Gespräch.

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This thesis pioneers the access to high frequency intraday corporate bonds data and evaluates the quality of the data received. Furthermore this work describes how to extract intraday corporate bond data. The most important stylized facts of the United States' corporate bond market are calculated to present the location, spread, shape, and dependence of the data packages. In dependence on Engle's News Impact Curve, a new measurement of the inuence of bond liquidities on bid prices, called Spread Impact Curve (SIC), is introduced. It is statistically shown, that the liquidities' impact on the bid prices is greater than on the ask prices. Finally a liquidity forecast model, based on Generalized Autoregressive Conditional Heteroskedastic (GARCH) models, is designed and adopted in order to forecast liquidity in the corporate bond markets.

This study tries to exhibit today's new term structure of commodity futures prices and how it affects long only passive investment products, especially Exchange Traded Commodities. Therefore, trying to replicate the nature of ETCs, a long only commodity futures index was computed and analyzed over the time period from 2006 up until 2011, confirming the new negative trend of returns on long only commodity futures strategies. After highlighting the benefits and risks of commodity investing, we focused on the analysis of the three return components of commodity futures indexes, especially the roll yield, which turned out to be the main reason for ETCs underperforming the spot prices of commodities.

Many traditional signal processing techniques in finance have limited ability to explain trading processes and distributional properties of the actual market prices. This is typically manifested in model misspecification and pricing and forecasting inaccuracy. For instance, the assumption that log stock returns are normally distributed is widely used in modern mathematical finance.

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This thesis identifies the most powerful serial dependence estimator for daily financial returns with a monte carlo experiment and uses it to estimate market efficiency over time. With these efficiency estimates, the Alpha Opportunity Barometer is constructed, a time series that indicates market efficiency at any point in time. It is shown with a custom statistical test that past short term mean reversion indicated low future returns, high future volatility and momentum for the past ten years in major stock indices and some commodities.

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