Robert Czech, Pasquale Della Corte, Shiyang Huang and Tianyu Wang
Can investors predict future foreign exchange (FX) rates? Many economists would say that this is an incredibly difficult task, given the weak link between exchange rate fluctuations and the state of an economy – a phenomenon also known as the ‘exchange rate disconnect puzzle’. In a recent paper, we show that some investors in the ‘FX option market’ are indeed able to accurately forecast exchange rate returns, particularly in periods with strong demand for the US dollar. These informed trades primarily take place on days with macroeconomic announcements and in options with higher embedded leverage. We also find that two groups of investors – hedge funds and real money investors – have superior skills in predicting exchange rates.
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.
Recent developments in digital technology fuel the notion that we are at an inflection point in human history, where fully automated robots are on their way to permanently replacing humans at work. To better understand the dynamics between automation and the demand for human labour, I undertook a case study on financial advice robots – colloquially known as roboadvisors. For the roboadvice firms examined, I found that human involvement is still crucial. Full automation is thus a myth, at least for now, in this industry. But roboadvisors do demonstrate that some cognitive ‘non-routine’ tasks can be automated. Previously, ‘non-routine’ tasks had been widely considered as non-automatable. Roboadvisors demonstrate how the frontier of potential automation is not limited to menial, routine tasks.
Central banks accept a wide range of assets from participants as collateral in their liquidity operations – but can this lead to undesired side effects? Such an approach can enhance overall liquidity in the financial sector, by allowing participants to transform illiquid collateral into more liquid assets. But, as a result, the central bank then needs to manage the greater potential risks of holding these riskier assets on its own balance sheet. Financially weaker participants may be encouraged to hold these assets if they can benefit from the higher returns, which compensate for the greater risk. In our recent paper we investigate whether central banks’ acceptance of a broad set of collateral incentivises the concentration of risk by examining the experience of the Bank of England (BoE).
Episodes of vanishing market liquidity haunt dealers. This was true in the great stock market crash of 1929 and remains so today: in August 2018, professional corporate bond traders cited vanishing liquidity as their primary source of worry. Dealers in more-liquid long gilt futures – contracts on 10 year UK government bonds – might be less concerned. But have structural changes in the market led to less resilience over time? We address this question in a recent Staff Working Paper. We find that liquidity in the long gilt futures market has increased slightly over recent years, while remaining resilient to periods of market stress.
Post-crisis regulatory reforms have reshaped and increased the amount of clearing activity in the OTC derivatives market. An emerging issue is so-called “client porting” – i.e. how central counterparties (CCPs) can transfer positions from one clearing member (CM) to another in the aftermath of one member defaulting. In this post, we discuss possible ways to offer clients temporary access to clearing services following a CM default, which we believe could increase the likelihood of successfully porting clients and avoiding further pressure on prices and market stability.
Blockchain is often discussed as if it is one single technology. But it is really a combination of several distinct features – decentralisation, distribution, cryptography, and automation – which are combined in different ways by different platforms. Some of these features may have benefits, while others may be unnecessary or even unhelpful – depending on the specific application. In this post, I consider whether and how these features may have different potential applications in financial services. Blockchain will only be truly useful in settings where one of more of these features solves a problem that existing technologies cannot.
Cryptoassets (or ‘cryptocurrencies’) are notoriously volatile. For example, in November 2018, Bitcoin – one of the more stable cryptoassets – lost 43% of its value in just 11 days. This kind of volatility makes it difficult for cryptoassets to function as money: they’re too unstable to be a good store of value, means of exchange or unit of account. But could so-called ‘stablecoins’ solve this problem and finally provide a price-stable cryptoasset?