Money markets are fundamentally different from stock markets. Stock markets are about price discovery for the purpose of allocating risk efficiently. Money markets are about obviating the need for price discovery using over-collateralised debt to reduce the cost of lending. Yet, attempts to...

The spread of distributed ledger technology (DLT) in finance could help to improve the efficiency and quality of supervision. This paper makes the case for embedded supervision, ie a regulatory framework that provides for compliance in tokenised markets to be automatically monitored by reading...

We explore the link between firms' dollar bond borrowing and their FX-hedged funding opportunities, as reflected in a positive corporate basis (the relative cost of local to synthetic currency borrowing). Consistent with previous research, we first document that firms substitute domestic for...

Dividend payouts affect the relative value of claims within a firm. When firms have contingent claims on each other, as in the banking sector, dividend payouts can shift the relative value of stakeholders' claims across firms. Through this channel, one bank's capital policy affects the equity...

The promise of contingent convertible capital securities (CoCos) as a 'bail-in' solution has been the subject of considerable theoretical analysis and debate, but little is known about their effects in practice. In this paper, we undertake the first comprehensive empirical analysis of bank CoCo...

How effective are available policy tools in managing liquidity risks in the mutual fund industry? We assess one such tool - swing pricing - which allows funds to adjust their settlement price in response to large net flows. Our empirical analysis exploits the fact that swing pricing is available...

Open-end mutual funds expose themselves to liquidity risk by granting their investors the right to daily redemptions at the fund's net asset value. We assess how swing pricing can dampen such risks by allowing the fund to settle investor orders at a price below the fund's net asset value. This...

This paper compares the predictive power of credit scoring models based on machine learning techniques with that of traditional loss and default models. Using proprietary transaction-level data from a leading fintech company in China for the period between May and September 2017, we test the...

Using granular data on the contract terms and design details of more than 1.3 million credit card offers, we document how card issuers shroud unappealing, back-loaded features of an offer (e.g., high default APRs, late or over-limit fees) via the position of the information, font size, or...

The market for the credit ratings of Chinese firms is large and growing. We focus our analysis on the firms that have ratings from both domestic and global agencies. Despite the similar symbols, the rating scales of the domestic and global agencies differ: domestic agencies rate firms that are...