Often when analysing financial markets, we want to know the statistical distribution of some financial market prices, yields or returns. But the ‘true’ distribution is unknown and unknowable. So we estimate the distribution, based on what we’ve observed in the past. In financial markets, adding one data point can make a huge difference. Sharp moves in Italian bond yields in May 2018 are case in point – in this blog I show how a single day’s trading drastically alters the estimated distribution of returns. This is important to keep in mind when modelling financial market returns, e.g. for risk management purposes or financial stability monitoring.
Evangelos Benos and Christina Fritz
Every day UK banks and corporates (“participants”) make sizeable payments to each other through CHAPS, the country’s high-value payment system. However, these payments are liquidity-intensive: every payment must be pre-funded, i.e. the payer must have in place the full amount to be paid. This can be costly, so each participant would prefer to first receive some money from another one and then make its own payments by recycling the received amount. However, this still requires that some participants supply intra-day liquidity to the system by making the first payments. But who are these participants? This post shows that it is typically the smaller ones and also those perceived by markets to be riskier that get the ball rolling…
Will Holman and Tim Pike
Firms are increasingly investing in automation, substituting capital for labour, as workers become more scarce and costly. We are seeing multiple examples, from automation in food processing to increasingly-common self-service tills. This push for productivity growth is one of the key themes from our meetings with businesses in the past year, which we think suggests a reversal of a decade-long trend.