We develop metrics based on Shapley values for interpreting time-series forecasting models, including "black-box" models from machine learning. Our metrics are model agnostic, so that they are applicable to any model (linear or nonlinear, parametric or nonparametric). Two of the metrics,...

This study employs the recently developed Lagrange multiplier-based causality-in-variance test by Hafner and Herwartz (2006), to determine the volatility spillovers between interest rates and stock returns for the US, the euro area, the UK, and Japan. The investigation pays careful attention to...

This study empirically examines the fragility of five major Asian economies (China, Hong Kong, India, Japan, and South Korea) to economic policy uncertainty (EPU) of US and EU, and oil prices in different state of the economies. To investigate these dynamics, we use the relative tail dependence...

We use a time-varying parameter dynamic factor model with stochastic volatility (DFM-TV-SV) estimated using Bayesian methods to disentangle the relative importance of the common component in FHFA house price movements from state-specific shocks, over the quarterly period of 1975Q2 to 2017Q4. We...

By using a nonlinear VAR model, we investigate whether the response of the US stock and housing markets to uncertainty shocks depends on financial conditions. Our model allows us to change the response of the US financial markets to volatility shocks in periods of normal and financial distress....

This study examines the monetary policy effectiveness of five major Asian countries (China, Hong Kong, India, Japan, and South Korea) using a quantile vector autoregression (QVAR) model-based spillover estimation approach of Balcilar et al. (2020b) at different quantile paths. To do this, we...