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PurposeThe goal of this work is to determine whether Bitcoin behaves as a safe-haven asset. In order to do so, the influence of Economic Policy Uncertainty (EPU) on Bitcoin returns and volatility was studied.Design/methodology/approachIt is evaluated whether, when compared with the evolution of EPU, Bitcoin's returns and volatility show behaviours typical of safe havens or rather, those of conventional speculative assets. When faced with an increase in EPU, safe havens – such as gold – can be expected to increase their returns and volatility, while conventional speculative assets will increase their volatility and reduce their returns. This study uses simple linear regression and quantile regression models on a daily data sample from 19 July 2010 to 11 April 2019, to analyse the influence of EPU on the returns and volatility of Bitcoin and gold.FindingsBitcoin's returns and volatility increase during more uncertain times, just like gold, showing that Bitcoin acts not only as a means of exchange but also shows characteristics of investment assets, specifically of safe havens. These findings provide useful information to investors by allowing Bitcoin to be considered as a tool to protect savings in times of economic uncertainty and to diversify portfolios.Originality/valueThis study complements and expands current research by aiming to answer the question of whether Bitcoin is a simple speculative asset or a safe haven. The most significant contribution is to show that Bitcoin is not a mere speculative asset but behaves like a safe haven.

Purpose This paper aims to examine the impact that monetary policy uncertainty (MPU) has on stock market returns by taking into account limits to arbitrage and the economic cycle. Design/methodology/approach Using four news-based MPU measures, regression models have been applied in this study over a sample period from January 1985 to March 2020. The limits to arbitrage have been considered by taking Russell 1000 Value, Russell 1000 Growth, Russell 2000 Value and Russell 2000 Growth indices, and business cycles were established following the National Bureau of Economic Research. Findings A negative MPU impact on stock returns has been found. In particular, the most subjective and difficult to arbitrate stocks have been more sensitive to MPU. However, it could not be concluded that MPU has a greater or lesser impact on stock returns depending on the economic cycle. Practical implications The findings obtained are particularly useful for monetary policymakers showing the importance and need for greater control over the transparency of their decisions to maintain the stability of financial markets. The findings obtained are also useful for investors when selecting their investment assets at times of the highest MPU. Originality/value To the best of the authors’ knowledge, this is one of the few studies investigating the effect of MPU on stock market returns, and the first to analyse this relationship taking into account the economic cycle and limits to arbitrage.

The media and election campaign managers conduct several polls in the days leading up to the presidential elections. These preelection polls have a different predictive capacity, despite the fact that under a Big Data approach, sources that indicate voting intention can be found. In this article, we propose a free method to anticipate the winner of the presidential election based on this approach. To demonstrate the predictive capacity of this method, we conducted the study for two countries: the United States of America and Canada. To this end, we analysed which candidate had the most Google searches in the months leading up to the polling day. In this article, we have taken into account the past four elections in the United States and the past five in Canada, since Google first published its search statistics in 2004. The results show that this method has predicted the real winner in all the elections held since 2004 and highlights that it is necessary to monitor the next elections for the presidency of the United States in November 2020 and to have more accurate information on the future results.

Purpose This paper aims to evaluate the influence of economic policy uncertainty (EPU) on the momentum effect, analysing its influence depending on the economic cycle and in different quantiles. Design/methodology/approach To determine the influence of EPU in the momentum effect taking into account the economic cycle and the level of the quantile, linear regression and quantile regression have been applied for the period from 2 January 1985 to 30 April 2019 for the US stock market. Findings It is shown that an increased feeling of insecurity associated with EPU reduces the momentum effect, especially in times of recession. Distinguishing by quantiles, an asymmetry in the impact of EPU in the momentum effect is discovered, finding that EPU reduces (increases) the profits of momentum strategies in the lowest (highest) quantiles. In the highest quantiles, an investor can obtain higher extraordinary returns with this strategy. For example, in the highest quantile, a one-point increase in the EPU levels would have increased the daily profitability by 12.7 basis points. These findings have important implications for investors and policymakers. Originality/value To the best of the authors’ knowledge, this is the first paper that evaluates the influence of EPU on the momentum effect by conducting an analysis based on the economic cycle and different quantiles, demonstrating how these factors are relevant in the influence of this uncertainty in the momentum anomaly.