Imagine you’ve booked tickets for a flight, and go to pick them up and pay for them on the day. You arrive at the airport but find out the airline has overbooked, and already given your ticket away. Worse yet, because you’ve missed this flight you’re going to miss an onward connection. But, you’ll likely get a replacement ticket in a day or two as compensation.
What was the root cause of the financial crisis? Ask any economist or banker and undoubtedly they will at some point mention leverage (see e.g. here, here and here). Yet when a capital requirement based on leverage — the leverage ratio requirement — was introduced, fierce criticism followed (see e.g. here and here). Drawing on the insights from a working paper, and thinking about the main criticism — that a leverage ratio requirement could cause excessive risk-taking — this seems not to have been the case.
Kristina Bluwstein, Marcus Buckmann, Andreas Joseph, Miao Kang, Sujit Kapadia and Özgür Şimşek
Financial crises are recurrent events in economic history. But they are as rare as a Kraftwerk album, making their prediction challenging. In a recent study, we apply robots — in the form of machine learning — to a long-run dataset spanning 140 years, 17 countries and almost 50 crises, successfully predicting almost all crises up to two years ahead. We identify the key economic drivers of our models using Shapley values. The most important predictors are credit growth and the yield curve slope, both domestically and globally. A flat or inverted yield curve is of most concern when interest rates are low and credit growth is high. In such zones of heightened crisis vulnerability, it may be valuable to deploy macroprudential policies.
Financial markets process orders faster now than ever before. However, they remain prone to occasional dysfunction where prices move away from fundamentals. One important type of market fragility is flash events. Identifying such events is crucial to understanding them and their effects. This post displays the results from a new methodology to identify these, but also longer lasting V-shaped events, as we show here with an application to three sovereign bond markets.
Robert Czech, Shiyang Huang, Dong Lou and Tianyu Wang
Government bond yields serve as a benchmark for virtually all other rates in financial markets. But what factors drive these yields? One view is that yields only move notably when important news hit the market, for example monetary policy announcements. Others suspect that some investors have an information advantage due to their access to costly information (e.g. data providers) or more accurate interpretations of public information. In a recent paper, we show that two investor groups – hedge funds and mutual funds – have an information edge in the UK government bond (gilt) market, and that these two investor types operate through different trading strategies and over different horizons.
Recent reforms that followed the Great Financial Crisis, as the establishment of the Single Supervisory Mechanism in Europe and the Prudential Regulatory Authority in the UK, reflect the belief that the governance of banking supervision affects financial stability. However, while existing research identifies the pros and cons of having either a central bank or a separate agency responsible for microprudential banking supervision, the advantages of having this task shared by both institutions (shared supervision) have received considerably less attention.
Have post-crisis reforms of banking regulation made banks and lending more resilient to the shock from Covid-19 and if so by how much? This blog takes one specific example – countercyclical capital buffers (CCyBs) – and shows that policy makers in a range of countries were able to quickly release these capital requirements, enabling banks to use the cumulated buffers. This released capital may in turn potentially help banks to support lending. And it will likely benefit lending in the country releasing requirements on buffers as well as banks’ lending to other countries, leading to potential positive international spillovers (see e.g. discussion of spillovers due to macroprudential policies by the ECB and others).
Today’s financial system is global: credit and several financial asset classes show booms and busts across countries, sometimes with severe repercussions to the global economy. Yet it is debated to what extent common dynamics rather than domestic cycles lie behind financial fluctuations and whether the impact of global drivers is growing. In a recent Staff Working Paper, we observe various global financial cycles going as far back as the 19th century. We find that a volatile global equity price cycle is nowadays the main driver of stock prices across advanced economies. Global cycles in credit and house prices have become larger and longer over the last 30 years, having gained relevance in economies that are more financially open and developed.
Over the last 15 years house prices have increased and home-ownership rates have fallen. But while the *number* of first-time buyers (FTBs) has fallen – what happened to the average *age* of FTBs? Not very much…
Dollar shortages in funding markets outside the United States have been a recurrent feature of the last three major crises, including the turmoil associated with the ongoing Covid-19 pandemic. The Federal Reserve has responded by improving conditions and extending the reach of its network of central bank swap lines, with the aim of channelling US dollars to non-US financial systems. Despite the recurrence of this phenomena, little is known about the macroeconomic consequences of both dollar shortage shocks and central bank swap lines. In this post (and in an underlying Staff Working Paper) I provide some tentative answers.