This paper proposes a cluster HAR-type model that adopts the hierarchical clustering technique to form the cascade of heterogeneous volatility components. In contrast to the conventional HAR-type models, the proposed cluster models are based on the relevant lagged volatilities selected by the...

Quantifying risk is pivotal for every financial institution. In the conventional framework, time is the key aspect for all the well-established risk measures. However, extracting and analyzing the frequency information conveyed by financial data, could yield improved insights about the inherent...

We analyze the interdependence between the government yield spread and stock returns of the banking sector in Italy during the years 2003-2015. In a first step, we find that after September 2008 the Spearman's rank correlation between the yield spread and the Italian banking system changed...

Should long-term investors account for time-variation in model parameters? We develop a time-varying Vector Autoregressive model that can handle time-variation in intercepts, slopes, volatility and correlation, the leverage effect in volatility and fat tails. Long-term investors should take...

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...

Empirical research on the benefits of investing in inflation-linked bonds usually relies on a limited number of observations due to the relatively recent introduction of these assets. We estimate models for the break-even inflation rate and use these to create hypothetical inflation-linked bond...

Today we live in a post-truth and highly digitalized era characterized by a flow of (mis-) information around the world. Identifying the impact of this information on stock markets and forecasting stock returns and volatilities has become a much more difficult task, perhaps almost impossible....

This paper estimates a bivariate HEAVY system including daily and intra-daily volatility equations and its macro-augmented asymmetric power extension. It focuses on economic factors that exacerbate stock market volatility and represent major threats to financial stability. In particular, it...

We study volatility spillovers among commodity and equity markets by employing a recently developed approach based on realized measures and forecast error variance decomposition invariant to the variable ordering from vector-autoregressions. This enables us to measure total, directional and net...

This paper aims at testing the influence of Subprime Crisis on Chinese stock market returns. By means of newly proposed time series spatial analysis methodology, we investigate the dominance behavior of daily returns on both Shanghai Stock Exchange Composite Index and Shenzhen Stock Exchange...