Regime specific spillover across cryptocurrencies and the role of COVID‑19

The aim of this study is to examine the daily return spillover among 18 cryptocurrencies under low and high volatility regimes,while considering three pricing factors and the effect of the COVID-19 outbreak.To do so,we apply a Markov regime-switching(MS)vector autoregressive with exogenous variables(VARX)model to a daily dataset from 25-July-2016 to 1-April-2020.The results indicate various patterns of spillover in high and low volatility regimes,especially during the COVID-19 outbreak.The total spillover index varies with time and abruptly intensifies following the outbreak of COVID-19,especially in the high volatility regime.Notably,the network analysis reveals further evidence of much higher spillovers in the high volatility regime during the COVID-19 outbreak,which is consistent with the notion of contagion during stress periods.

Impact of the COVID‑19 outbreak on the US equity sectors:Evidence from quantile return spillovers

The aim of this study is to examine the extreme return spillovers among the US stock market sectors in the light of the COVID-19 outbreak.To this end,we extend the now-traditional Diebold-Yilmaz spillover index to the quantiles domain by building networks of generalized forecast error variance decomposition of a quantile vector autoregressive model specifically for extreme returns.Notably,we control for common movements by using the overall stock market index as a common factor for all sectors and uncover the effect of the COVID-19 outbreak on the dynamics of the network.The results show that the network structure and spillovers differ considerably with respect to the market state.During stable times,the network shows a nice sectoral clustering structure which,however,changes dramatically for both adverse and beneficial market conditions constituting a highly connected network structure.The pandemic period itself shows an interesting restructuring of the network as the dominant clusters become more tightly connected while the rest of the network remains well separated.The sectoral topology thus has not collapsed into a unified market during the pandemic.

Oil-Price Forecasting Based on Various Univariate Time-Series Models

Time-series-based forecasting is essential to determine how past events affect future events. This paper compares the performance accuracy of different time-series models for oil prices. Three types of univariate models are discussed: the exponential smoothing (ES), Holt-Winters (HW) and autoregressive intergrade moving average (ARIMA) models. To determine the best model, six different strategies were applied as selection criteria to quantify these models’ prediction accuracies. This comparison should help policy makers and industry marketing strategists select the best forecasting method in oil market. The three models were compared by applying them to the time series of regular oil prices for West Texas Intermediate (WTI) crude. The comparison indicated that the HW model performed better than the ES model for a prediction with a confidence interval of 95%. However, the ARIMA (2, 1, 2) model yielded the best results, leading us to conclude that this sophisticated and robust model outperformed other simple yet flexible models in oil market.

3D numerical study and comparison of thermal-flow performance of various annular finne d-tub e designs

With the increase of heat transfer problems in marine vehicles and submerged power stations in oceans,the search for an efficient finned-tube heat exchanger has become particularly important.The purpose of the present investigation is to analyze and compare the thermal exchange and flow characteristics between five different fin designs,namely:a concentric circular finned-tube(CCFT),an eccentric circular finned-tube(ECFT),a perforated circular finned-tube(PCFT),a serrated circular finned-tube(SCFT),and a star-shaped finned-tube(S-SFT).The fin design and spacing impact on the thermal-flow performance of a heat exchanger was computed at Reynolds numbers varying from 4,300 to 15,000.From the numerical results,and when the fin spacing has been changed from 2 to 7 mm,an enhancement in the Colburn factor and a reduction in the friction factor and fin performances were observed for all cases under study.Three criteria were checked to select the most efficient fin design:the performance evaluation criterion P EC,the global performance criterion G PC,and the mass global performance criterion M G PC.Whatever the value of Reynolds number,the conventional CCFT provided the lowest performance evaluation criterion P EC,while the SCFT gave the highest amount of P EC.The most significant value of G PC was reached with the ECFT;however,G PC remained almost the same for CCFT,PCFT,SCFT,and S-SFT.In terms of the mass global performance criterion,the S-SFT provides the highest M Gpc as compared with the full fins of CCFT(41-73%higher)and ECFT(29-54%higher).Thus,the heat exchanger with S-SFT is recommended to be used in the cooling of offshore energy systems.