Olga Cielinska, Andreas Joseph, Ujwal Shreyas, John Tanner and Michalis Vasios
The Bank of England has now access to transaction-level data in over-the-counter derivatives (OTCD) markets which have been identified to lie at the centre of the Global Financial Crisis (GFC) 2007-2009. With tens of millions of daily transactions, these data catapult central banks and regulators into the realm of big data. In our recent Financial Stability Paper, we investigate the impact of the de-pegging in the euro-Swiss franc (EURCHF) market by the Swiss National Bank (SNB) in the morning of 15 January 2015. We reconstruct detailed trading and exposure networks between counterparties and show how these can be used to understand unprecedented intraday price movements, changing liquidity conditions and increased levels of market fragmentation over a longer period.
Alastair Cunningham, David Bradnum and Alastair Firrell.
Uncertainty is a hot topic for economists at the moment. Have business leaders become more uncertain as a result of the EU referendum? If so, has that uncertainty had any effect on their plans? The Bank’s analysts look at lots of measures of economic uncertainty, from complex financial market metrics to how often newspaper articles mention it. But few of those measures are sourced directly from the trading businesses up and down the country whose investment and employment plans affect the UK economy. This blog reports on recent efforts to draw out what the Bank’s wide network of business contacts are telling us about uncertainty – comparing what we’re hearing now to trends seen in recent years.
Most large banks assess the capital they need for regulatory purposes using ‘internal models’. The idea is that banks are in a better position to judge the risks on their own balance sheets. But there are two fundamental problems that can arise when it comes to modelling. The first is complexity. We live in a complex world, but does that mean a complex model is always the best way of dealing with it? Probably not. The second problem is a lack of ‘events’ (eg defaults). If we cannot observe an event, it is difficult to model it credibly, so internal models may not work well.