Bankers, Markets & Investors

What do we know about assets’ behavior and connectedness between Bitcoin, oil, and G7 stocks amid the COVID-19 pandemic?

Hassan OBEID — 2022-12-22

This study examines information dissemination across G7 markets for Bitcoin, stocks, and oil before and during the COVID-19 pandemic. We used a vector autoregressive model and impulse response function to analyze data. Our findings suggest that the pandemic has had a considerable effect on increasing the directional causalities and time-varying connectedness between Bitcoin, oil, and G7 stock indices during the crisis. Bitcoin significantly influences oil and stock returns during the pandemic. Moreover, the response of Bitcoin to shocks in stocks returns is more pronounced for France, Germany, Italy, and the United Kingdom than Japan, the United States, and Canada. The results could aid investors with portfolio diversification and hedging strategy in different G7 stock markets.

How does bank capital influence lending and securities holdings? Evidence from Asian banks

Whelsy BOUNGOU — 2022-12-22

Using panel dataset of 370 banks from 15 Asian countries over the period 2010-2018, this paper provides empirical evidence on the impact of bank capital on lending, and securities holdings. Our findings suggest that the increase in bank capital reduces lending supply, especially lending with a maturity between 1 and 5 years. Moreover, we highlight that the incentives to hold more securities (such as investment and trading securities) increase as banks’ capital increases. We also show that the banks that responded most were highly deposit-dependent and small. Overall, our results suggest that Asian banks respond to a capital increase by decreasing the supply of loans against an increase in securities holding.

Connectedness between conventional and digital assets amid COVID-19 pandemic: Evidence from G7 stocks, Oil and Bitcoin

Aymen TURKI — 2022-12-22

This study examines the connectedness between G7 indices, Bitcoin, and oil during the COVID-19 pandemic. Based on daily data from January 1, 2016 to April 1, 2021, a vector auto-regression model and an impulse response function are employed to illustrate the time path of these assets following own and cross-shocks. Our study exhibits the considerable effect of the pandemic on increasing directional causalities and time-varying connectedness between G7 indices, Bitcoin, and oil. The findings indicate that G7 indices’ own shocks almost immediately lower forecasts of stock return urging the diversification to reduce risk. Moreover, the significant negative response of oil to shocks amid the pandemic reflects its high vulnerability during mitigated periods. Unlike other countries, we find a relative resilience of Bitcoin to S&P 500 shocks, and we consequently recommend Bitcoin as a diversifier to American
investors during the pandemic. Our results are useful for both investors and policymakers who need to think ahead, rather than waiting to have a downside G7 returns movement in turbulent periods.

Can Collective Emotions Improve Bitcoin Volatility Forecasts?

Fredj JAWADI — 2022-12-22

This paper extends the study of Bourghelle et al. (2022) to check whether collective emotions could help forecast bitcoin volatility over the period 2018-2021. To this end, we first assess whether consideration of investor sentiment and collective emotions can give us clearer insights into bitcoin dynamics over the period in question and whether it can help to explain the different shifts in price. Formally, we ran causality tests and, as in Bourghelle et al. (2022), built a two equation nonlinear vector autoregressive (VAR) model to assess for further lead-lag effects between bitcoin volatility and collective emotions. Second, we proposed in-sample forecasts of bitcoin volatility to test whether it would be possible to improve our forecasts by taking investors’ emotions and sentiment into account. Our findings show that market sentiment and investors’ emotions provide useful information that can explain shifts, structural breaks, and changes in bitcoin volatility. Further, collective emotions improve bitcoin volatility forecasting as our nonlinear model, including emotions-related news, supplants the benchmark linear model.

Can Collective Emotions Improve Bitcoin Volatility Forecasts?

David BOURGHELLE — 2022-12-22

This paper extends the study of Bourghelle et al. (2022) to check whether collective emotions could help to forecast bitcoin volatility over the period 2018-2021. To this end, we first assess whether consideration of investor sentiment and collective emotions can give us clearer insights into bitcoin dynamics over the period in question and whether they can help to explain the different price fluctuations. Formally, we ran causality tests and, as in Bourghelle et al. (2022), built a two-equation nonlinear vector autoregressive (VAR) model to assess for further lead-lag effects between bitcoin volatility and collective emotions. Second, we proposed in-sample forecasts of bitcoin volatility to test whether our forecasts could be improved by taking investors’
emotions and sentiment into account. Our findings show that market sentiment and investors’ emotions provide useful information that can help to explain
fluctuations, structural breaks, and changes in bitcoin volatility. Further, collective emotions improve bitcoin volatility forecasting as our nonlinear model, including emotions-related news, supplants the benchmark linear model.

The Determinants of Equity Lines Financing: An International Study

Ilias ANNAOUI — 2022-12-22

Equity lines financing allows companies to increase their capital by issuing shares in successive tranches, as and when required over an agreed period of time, in order to boost equity and cash flow. The purpose of this article is to examine the factors which inform the use of this method, considering the specific parameters of businesses using equity lines, as well as variables linked to the institutional and economic context. Employing a model based on the Generalized Method of Moments (GMM) technique, we studied 407 firms in 15 countries making using of equity lines Financing in the period 2004-2018. The results confirm that the existence of opportunities for growth, the existence of a well-developed secondary market (maturity, expertise in financial intermediation activities, volume of transactions etc.) and the broader economic outlook are the principal explanatory variables behind the determinants of equity line financing.