This paper examines “fat tails puzzle” in the financial markets. Ignoring the rate of convergence in Central Limit Theorem (CLT) provides the “fat tail” uncertainty. In this paper, we provide a review of the empirical results obtained “fat tails puzzle” using innovative method of...

The study examines the spillover between Twitter Uncertainty Indexes (TUI) and 10 US sectors. Our methodology is twofold: a time-varying parameter vector autoregression (TVP-VAR) to explore the dynamic connectedness among sectoral returns and a regression, mainly ordinary least squares (OLS) and...

This study examines the impact of investor attention on portfolio volatility and sectoral risk spillovers in Borsa Istanbul. We use advanced econometric models, including E-GARCH-X, GJR-GARCH-X, and multivariate BEKK-GARCH-X, and analyze daily data from January 2004 to June 2024. We find that...

Transitioning to a low-carbon economy involves risks for the value of financial assets, with potential ramifications for financial stability. We quantify the systemic impact on financial firms arising from changes in the value of financial assets under three climate transition scenarios that...

Financial risk managers routinely use non-linear time series models to predict the downside risk of the capital under management. They also need to evaluate the adequacy of their model using so-called backtesting procedures. The latter involve hypothesis testing and evaluation of loss functions....

We propose a Markov Switching Graphical Seemingly Unrelated Regression (MS-GSUR) model to investigate time-varying systemic risk based on a range of multi-factor asset pricing models. Methodologically, we develop a Markov Chain Monte Carlo (MCMC) scheme in which latent states are identified on...

We estimate and test long-run risk models using international macroeconomic and financial data. The benchmark model features a representative agent who has recursive preferences with a time preference shock, a persistent component in expected consumption growth, and stochastic volatility in...

The link between systemic risk and economic growth is hard to study because the relationship is believed to be nonlinear and systemic risk is unobservable. The myriad of measures proposed in the literature add model uncertainty as an additional difficulty. I use a Bayesian quantile regression to...

Transitioning to a low-carbon economy involves risks for the value of financial assets, with potential ramifications for financial stability. We quantify the systemic impact on financial firms arising from changes in the value of financial assets under three climate transition scenarios that...

We investigate the direct connection between the uncertainty related to estimated stable ratios of stock prices and risk and return of two pairs trading strategies: a conditional statistical arbitrage method and an implicit arbitrage one. A simulation-based Bayesian procedure is introduced for...