Contributions published at Financial Economics (Felix Kübler)

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We present a exible and scalable method for computing global solutions of high-dimensional stochastic dynamic models. Within a time iteration or value function iteration setup, we interpolate functions using an adaptive sparse grid algorithm. With increasing dimensions, sparse grids grow much more slowly than standard tensor product grids. Moreover, adaptivity adds a second layer of sparsity, as grid points are added only where they are most needed, for instance in regions with steep gradients or at non-differentiabilities. To further speed up the solution process, our implementation is fully hybrid parallel, combining distributed and shared memory parallelization paradigms, and thus permits an efficient use of high-performance computing architectures. To demonstrate the broad applicability of our method, we solve two very different types of dynamic models: first, high-dimensional international real business cycle models with capital adjustment costs and irreversible investment; second, multiproduct menu-cost models with temporary sales and economies of scope in price setting.

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We introduce and deploy a generic, highly scalable computational method to solve high-dimensional dynamic stochastic economic models on high-performance computing platforms. Within an MPI---TBB parallel, nonlinear time iteration framework, we approximate economic policy functions using an adaptive sparse grid algorithm with d-linear basis functions that is combined with a dimensional decomposition scheme. Numerical experiments on "Piz Daint" (Cray XC30) at the Swiss National Supercomputing Centre show that our framework scales nicely to at least 1,000 compute nodes. As an economic application, we compute global solutions to international real business cycle models up to 200 continuous dimensions with significant speedup values over state-of-the-art techniques.

The demand for assets as prices and initial wealth vary identifies beliefs and attitudes towards risk. We derive conditions that guarantee identification with no knowledge either of the cardinal utility index or of the distribution of future endowments or payoffs of assets; the argument applies even if the asset market is incomplete and demand is observed only locally.

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Assuming the classic contingent claim setting, a number of financial asset demand tests of Expected Utility have been developed and implemented in experimental settings. However the domain of preferences of these asset demand tests differ from the mixture space of distributions assumed in the traditional binary lottery laboratory tests of von Neumann-Morgenstern Expected Utility preferences. We derive new sets axioms that are necessary and sufficient for preferences over contingent claims to be representable by an Expected Utility function. We also indicate the additional axioms required to extend the representation to the more general case of preferences over risky prospects.

We assess the quantitative implications of the re-use of collateral on financial market leverage, volatility, and welfare within an infinite-horizon asset-pricing model with heterogeneous agents. In our model, the ability of agents to re-use frees up collateral that can be used to back more transactions. Re-use thus contributes to the build-up of leverage and significantly increases volatility in financial markets. When introducing limits on re-use, we find that volatility is strictly decreasing as these limits become tighter, yet the impact on welfare is non-monotone. In the model, allowing for some re-use can improve welfare as it enables agents to share risk more effectively. Allowing reuse beyond intermediate levels, however, can lead to excessive leverage and lower welfare. So the analysis in this paper provides a rationale for limiting, yet not banning, re-use in financial markets.

This thesis investigates the question if there was a change in the deviation from the covered interest rate parity (CIP) during the Brexit. The Forex market has been gaining increasing attention over the recent decades. Different currency pairs show that there were deviations from the CIP. And it is assumed that in turbulent times these deviations increase and may persist for a longer period. The subject of this Master thesis is the investigation how the deviation from CIP behaved, during the time of the Brexit referendum. The primary aim is to test the null hypothesis, which claims that comparing the months of the year 2016 did not led to significant changes in the mean deviations from CIP distribution for two different currency pairs. The hypothesis is additionally tested for the mean percentage change of the deviation from CIP. The thesis also investigates if the Brexit referendum has led to a different regime regarding the volatility of the deviation and its mean. The duration and the time of possible regime switches are reported.

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We develop a simple general equilibrium model to study the interactions between financial arbitrage and the real economy under collateral constraints. In good times, arbitrage activities help boost the production sectors by providing external funds to capital investment. However, when exposed to adverse shocks and panic market reactions, arbitrage also amplifies the financial distress and makes it easier for the economy to fall into self-fulfilling crises. Moreover, the possibility of regime switches triggered by exogenous shocks also complicates the path to recovery. The combination of financial distress and pessimistic market anticipation not only slows down the recovery process, but also can trap the economy in a less healthy steady state.

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