Analysis of Bitcoin prices using market and sentiment variables

This paper proposes an empirical model for analysing the dynamics of Bitcoin prices. To do this, we consider a vector error correction model over two overlapping periods: 2010–17 and 2010–19. Price discovery is achieved through the Gonzalo–Granger permanent‐transitory decomposition. The pricing factors are endogenous linear combinations of the S&P 500 index, gold price, a Google search variable associated to Bitcoin and a fear index proxied by the FED Financial Stress Index. Our empirical analysis shows that during the first period, a linear combination of four pricing factors describes the efficient Bitcoin price. The S&P 500 index and Google searches have a positive effect whereas gold prices and the fear index have a negative effect. In contrast, during the second period, the efficient price behaves idiosyncratically and can be only rationalised by individuals' search for information on the cryptocurrency. These findings provide empirical evidence on the presence of a correction in Bitcoin prices during the period 2018–19 uncorrelated to market fundamentals. We also show that standard empirical asset pricing models perform poorly for explaining Bitcoin prices.     

Market microstructure,banks’ behaviour and interbank spreads: evidence after the crisis

We present a study of the European electronic interbank market of overnight lending (e-MID) before and after the beginning of the financial crisis. The main goal of the paper is to explain the structural changes of lending/borrowing features due to the liquidity turmoil. Unlike previous contributions that focused on banks’ dependent and macro information as explanatory variables, we address the role of banks’ behaviour and market microstructure as determinants of the credit spreads. We show that all banks experienced significant variations in their liquidity costs due to the sensitivity of interbank rates to the timing and side of trades. We argue that, while larger banks did experience better funding conditions after the crisis, this was not just a consequence of the “too big to fail” perception of the market. Larger banks have been able to play more strategically when managing their liquidity by taking advantage of the changing market microstructure.