RESUMO
Did Covid19 induce market turmoil impact the intraday volatility spillovers between energy and other ETFs?. To examine this, we first estimate the realized volatility of ETFs using the 5-min high-frequency data. Next, we employ time-varying parameter vector autoregressions (TVP-VAR). Finally, we utilize the wavelet coherence measure to test the time-frequency impact of COVID-induced sentiment on the spillovers by employing investors' psychological and behavioural factors. We find that oil and stock markets are net transmitters while currency, bonds, and silver markets are net receivers. The wavelet analysis embarked significant impact of media coverage and fake news index towards shaping investors' pessimism for their investments. We proposed useful implications for policymakers, governments, investors, and portfolio managers.
RESUMO
The compass rose pattern in financial data may indicate the presence of a nonlinear, possibly chaotic, data generating mechanism. The analysis of three key financial asset and denoised returns, gold, the Great British Pound/US dollar spot exchange rate, and the Standard & Poor's 500 stock index, reveals that over four equivalent subperiods, from 1996 to 2015, the compass rose pattern changes. This finding provides an opportunity to establish how noise affects financial time series. We conclude that the compass rose pattern is unlikely the product of an underlying nonlinear structure, since there is evidence of nonlinearity in all time periods, even those where the compass rose pattern is not evident. Therefore, the compass rose patterns, seen in the denoised data, suggest that the presence of noise masks the underlying dynamics of the asset returns.
RESUMO
Financial markets are exposed to extreme uncertain circumstances escalating their tail risk. Sustainable, religious, and conventional markets represent three different markets with various characteristics. Motivated with this, the current study measures the tail connectedness between sustainable, religious, and conventional investments by employing a neural network quantile regression approach from December 1, 2008 to May 10, 2021. The neural network recognized religious and conventional investments with maximum exposure to tail risk following the crisis periods reflecting strong diversification benefits of sustainable assets. The Systematic Network Risk Index spots Global Financial Crisis, European Debt Crisis, and COVID-19 pandemic as intensive events yielding high tail risk. The Systematic Fragility Index ranks the stock market in the pre-COVID period and Islamic stocks during the COVID sample as the most susceptible markets. Conversely, the Systematic Hazard Index nominates Islamic stocks as the chief risk contributor in the system. Given these, we portray various implications for policymakers, regulatory bodies, investors, financial market participants, and portfolio managers to diversify their risk using sustainable/green investments.