This study explores the contrasting impacts of the COVID-19 pandemic on various industries in Australia. Considering all daily announced information, we analyzed the diverse impacts of COVID-19 on the sectoral stock returns from 26 January to 20 July 2020. Sixteen out of twenty examined stock indices negatively react to the daily rise in COVID-19 confirmed cases. Several actions from the Australian government to control the pandemic are relatively ineffective in boosting the overall financial market; however, some positive interactions are captured in five sectors of industrials, health care, metals and mining, materials, and resources. The result shows that all industries that benefited from government financial assistance are either shielded or less severely affected by the pandemic. While sectors that did not directly receive financial remedies relatively showed no enhancement in their overall performance. Having achieved short-term success in helping the economy, the government recorded an all-time high deficit since 2004 that might eventually lead to adverse effects on the overall economy. The Australian equity market is found to be rationally distinct to the crude oil price risk, while positive correlations between AUD/USD rate and real estate-related sectors are reported.

The purpose of the research is to explore the dynamic multiscale linkage between economic policy uncertainty, equity market volatility, energy and sustainable cryptocurrencies during the COVID-19 period. We use a multiscale TVP-VAR model considering level (EPUs and IDEMV) and returns series (cryptocurrencies) from 1 December 2019 to 30 September 2022. The data are then decomposed into six wavelet components, based on the wavelet MODWT method. The TVP-VAR connectedness approach is used to uncover the dynamic connectedness among EPUs, energy and sustainable cryptocurrency returns. Our findings reveal that CNEPU (USEPU) is the strongest (weakest) NET volatility transmitter. IDEMV is the most consistent volatility NET transmitter among all uncertainty indices across the original returns and wavelet scales (D1~D6). Energy cryptocurrencies, i.e., GRID, POW and SNC, are more likely to receive volatility spillovers than sustainable cryptocurrencies during a turbulent period (COVID-19). XLM (XNO) is least (most) affected by volatility spillover in system-wide connectedness, and XLM (ADA and MIOTA) showed a consistent (heterogeneous) non-recipient behavior across the six wavelet (D1~D6) scales and original return series. This study uncovers the dynamic connectedness across multiscale, which will support investors considering different investment horizons (D1~D6).