Der Untersuchungsgegenstand der Arbeit ist die Darstellung der wichtigsten Anlegermotive bei Marktübertreibungen. Es wird dabei auf Konzepte der verhaltensorientierten Kapitalmarktforschung zurückgegriffen. Basierend auf den gewonnenen Erkenntnissen werden Lösungsansätze zur Vermeidung von...

Gegenstand der Untersuchung ist die Analyse der Maßnahmen der Landesbanken, der Veränderung ihrer Rolle und von Veränderungen der Finanzbranche in Zusammenhang mit dem Wegfall der staatlichen Haftungsgarantien. Die Institute weisen deutliche Parallelen bezüglich der Stoßrichtung der...

We augment the HAR model with additional information channels to forecast realized volatility of WTI futures prices. These channels include stock markets, sentiment indices, commodity and FX markets, and text-based Google indices. We then apply four differing machine learning techniques to...

We study potential drivers for a large cross-section of commodity futures. Unlike previous studies, we examine the effect of monthly drivers on daily returns using mixed-frequency Granger causality tests. We find real economic activity as a main driver on a monthly basis, whereas financial...

Cryptocurrencies such as Bitcoin are establishing themselves as an investment asset and are often named the New Gold. This study, however, shows that the two assets could barely be more different. Firstly, we analyze and compare conditional variance properties of Bitcoin and Gold as well as...

We apply the GARCH-MIDAS framework to forecast the daily, weekly, and monthly volatility of five highly capitalized Cryptocurrencies (Bitcoin, Etherium, Litecoin, Ripple, and Stellar) as well as the Cryptocurrency index CRIX. Based on the prediction quality, we determine the most important...

This paper contributes to the large debate regarding the impact of oil price changes on U.S. GDP growth. Firstly, it replicates empirical findings of prominent studies and finds that the proposed oil price measures have a dissipating effect with recent data up to 2016Q4. Secondly, it re-examines...

This study compares the performance of several methods to calculate the Value-at-Risk of the six main ASEAN stock markets. We use filtered historical simulations, GARCH models, and stochastic volatility models. The out-of-sample performance is analyzed by various backtesting procedures. We find...

In econometrics, long memory models for variance modeling like FIGARCH or FIAPARCH are characterized by a Fractional Differencing term. In order to estimate and apply these models, the infinite MacLaurin expansion of the differencing term has to be truncated at a certain level. We transfer the...

First Version: 03/11/2015This Version: 04/01/2016We expand the literature of volatility and Value-at-Risk forecasting of oil price returns by comparing the recently proposed Mixture Memory GARCH (MMGARCH) model to other discrete volatility models (GARCH, FIGARCH, and HYGARCH). We incorporate an...