This paper introduces a multivariate pure-jump Lévy process which allows for skewness and excess kurtosis of single asset returns and for asymptotic tail dependence in the multivariate setting. It is termed Variance Compound Gamma (VCG). The novelty of my approach is that, by applying a...

This paper introduces a multivariate pure-jump Lévy process which allows for skewness and excess kurtosis of single asset returns and for asymptotic tail dependence in the multivariate setting. It is termed Variance Compound Gamma (VCG). The novelty of my approach is that, by applying a...

Factor modeling is a popular strategy to induce sparsity in multivariate models as they scale to higher dimensions. We develop Bayesian inference for a recently proposed latent factor copula model, which utilizes a pair copula construction to couple the variables with the latent factor. We use...

We review the labor market implications of recent real-business-cycle models that successfully replicate the empirical equity premium. We document the fact that all models considered in this survey with the exception of Boldrin, Christiano, and Fisher (2001) imply a negative correlation of...

We document the empirical fact that asset prices in the consumption-goods and investment-goods sector behave almost identically in the US economy. In order to derive the cyclical behavior of the equity returns in these two sectors, we consider a standard two-sector real-business cycle model with...

This paper introduces a multivariate pure-jump Lévy process which allows for skewness and excess kurtosis of single asset returns and for asymptotic tail dependence in the multivariate setting. It is termed Variance Compound Gamma (VCG). The novelty of my approach is that, by applying a...

This paper examines whether there exists a momentum effect after one-day abnormal returns in the cryptocurrency market. For this purpose a number of hypotheses of interest are tested for the BitCoin, Ethereum and LiteCoin exchange rates vis-à-vis the US dollar over the period...

We develop an Artificial Stock Market - an agent-based simulation model of the stock market with many risky assets. The ASM has three layers of heterogeneous and interacting agents, and generates prices for 150 stocks. We present the current state of the model and demonstrate its ability to...

In this paper, we review the most common specifications of discrete-time stochastic volatility (SV) models and illustrate the major principles of corresponding Markov Chain Monte Carlo (MCMC) based statistical inference. We provide a hands-on ap proach which is easily implemented in empirical...

This paper develops a Monte-Carlo backtesting procedure for risk premia strategies and employs it to study Time-Series Momentum (TSM). Relying on time-series models, empirical residual distributions and copulas we overcome two key drawbacks of conventional backtesting procedures. We create...