Connectedness between Defi assets and equity markets during COVID-19: A sector analysis.

This paper explores the dynamic connectedness between Defi assets and sector stock markets focused around the COVID-19 pandemic crisis. For that aim, this research applies the TVP-VAR model, and it also computes the optimal weights and hedge ratios for the Defi assets-sector equity portfolios using the DCC-GARCH model. Our main findings reveal that static connectedness is slightly economy- and sector-dependent. Regarding the dynamic connectedness, as expected, the total spillover index changes over time, showing a cruel impact of the global pandemic declaration. Net spillover indices show relevant differences between the Defi assets and certain sectors (net receivers) and sectors such as industrials, materials and information technology (time-varying net transmitters). Finally, the optimal hedge ratios reveal similar levels of coverage in all the periods analyzed, with slight upturns in the cost of such coverage in the crisis period caused by COVID-19.

Forecasting GDP with many predictors in a small open economy: forecast or information pooling?

This study compares two distinct approaches, pooling forecasts from single indicator MIDAS models versus pooling information from indicators into factor MIDAS models, for short-term Singapore GDP growth forecasting with a large ragged-edge mixed frequency dataset. We consider various popular weighting schemes in the literature when conducting forecast pooling. As for factor extraction, both the conventional dynamic factor model and the three-pass regression filter approach are considered. We investigate the relative predictive performance of all methods in a pseudo-out-of-sample forecasting exercise from 2007Q4 to 2020Q3. In the stable growth non-crisis period, no substantial difference in predictive performance is found across forecast models. In comparison, we find information pooling tends to dominate both the quarterly autoregressive benchmark model and the forecast pooling strategy particularly during the Global Financial Crisis. Supplementary Information: The online version contains supplementary material available at 10.1007/s00181-022-02356-9.