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.
Francis Breedon, Louisa Chen, Angelo Ranaldo and Nicholas Vause
Most academic studies find that algorithmic trading improves the quality of financial markets in normal times by boosting market liquidity (so larger trades can be executed more quickly at lower cost) and enhancing price efficiency (so market prices better reflect all value-relevant information). But what about in times of market stress? In a recent paper looking at the removal of the Swiss franc cap, we find that algorithmic trading provided less liquidity than usual, at worse prices, and that its contribution to efficient pricing dropped to near zero. Market quality benefits from a diversity of participants pursuing different trading strategies, but it seems this was undermined in this episode by commonalities in the way algorithms responded.
Volatility returned to markets in early February, sparked by strong US wage growth data. After months of calm, the S&P 500 equity index fell by 4% on 5 February and the VIX – a measure of US equity volatility that is sometimes referred to as Wall Street’s “fear gauge” – experienced its largest one-day move in its 28-year history. Interestingly, measures of volatility in other markets, including interest rates and currencies, moved by much less. So what caused the outsized spike in the VIX? Some of the rise was linked to rebalancing flows associated with VIX exchange-traded products (ETPs), which can amplify moves in the volatility market. The events have also led to some questions whether developments in VIX ETPs can also affect the S&P 500 itself –whether the ‘tail’ can wag the ‘dog’.
Calebe de Roure, Ben Morley and Lena Boneva
In August 2016 the MPC announced a package of easing measures, including the Corporate Bond Purchase Scheme (CBPS). In a recent staff working paper, we explore the announcement impact of the CBPS, using the so called “difference in differences” (or “DID”) approach. Overall – to deliver the punchline to eager readers – this analytical technique suggests that the announcement caused spreads on CBPS eligible bonds to tighten by 13bps, compared with comparable euro or dollar denominated bonds (Charts 1b, 2). Continue reading
How low are UK real interest rates by historical standards? Using the Bank’s Millennium of Macroeconomic Data, I compute real bank rate, mortgage rates, and 10-year government bond yields over time.
Joseph Noss, Liam Crowley-Reidy and Lucas Pedace
Anna Orlovskaya and Conor Sewell
Peer to Peer (P2P) lending is a hot topic at Fintech events and has received a lot of attention from academia, journalists, various international bodies and regulators. Following the Financial Crisis, P2P platforms saw an opportunity to fill a gap in the market by offering finance to customers and businesses struggling to get loans from banks. Whilst some argue they will one day revolutionise the whole banking landscape, many platforms have not yet turned a profit. So before asking if they are the future, we should first ask if they have a future at all. Problems such as a higher cost of funds, or limited ability to scale the business, may mean the only viable path is to become more like traditional banks.
Fernando Cerezetti, Emmanouil Karimalis, Ujwal Shreyas and Anannit Sumawong
When a trade is executed and cleared though a central counterparty (CCP), the CCP legally becomes a buyer for every seller and a seller for every buyer. When a CCP member defaults, the need to establish a matched book for cleared positions means the defaulter’s portfolio needs to be closed out. The CCP then faces a central question: what hedges should be executed before the portfolio is liquidated so as to minimize the costs of closeout? In a recent paper, we investigate how distinct hedging strategies may expose a CCP to different sets of risks and costs during the closeout period. Our analysis suggests that CCPs should carefully take into account these strategies when designing their default management processes.
Jeremy Franklin, Scott Woldum, Oliver Wood and Alex Parsons
How do markets react to the release of economic data? We use a set of machine learning and statistical algorithms to try to find out. In the period since the EU referendum, we find that UK data outturns have generally been more positive than market expectations immediately prior to their release. At the same time, the responsiveness of market interest rates to those data surprises fell below historic averages. The sensitivity of market rates has also been below historic averages in the US and Euro area, suggesting international factors may also have played a role. But there are some signs that the sensitivity has increased over the past year in the UK.
Oliver Brenman, Frank Eich, and Jumana Saleheen
The conventional wisdom amongst financial market observers, academics, and journalists is that a steeper yield curve should be good news for bank profitability. The argument goes that because banks borrow short and lend long, a steeper yield curve would raise the wedge between rates paid on liabilities and received on assets – the so-called “net interest margin” (or NIM). In this post, we present cross-country evidence that challenges this view. Our results suggest that it is the level of long-term interest rates, rather than the slope of the yield curve, that drives banks’ NIMs.