Algorithmic stablecoins and devaluation risk

Using the devaluation of the TerraUSD peg as a case study, this column shows how algorithmic stablecoins are vulnerable to speculative attacks when the system is under-collateralised. The authors point to solutions – stable collateral and over-collateralisation – to stabilise the peg.

Interest Rate Parity in Decentralized Finance

[Draft available on request] In this paper, we provide a model to explain equilibrium pricing of interest rates on Defi lending protocols.We pin down the fundamental sources of risk that explain the cross-section of interest rates.

Market risk assessment: A multi-asset, agent-based approach applied to a DeFi lending protocol

We assess the market risk of the lending protocol using a multi-asset agent-based model to simulate ensembles of users subject to price-driven liquidation risk. Our multi-asset methodology shows that the protocol’s systemic risk is small under stress and that enough collateral is always present to underwrite active loans.

Decentralized Stablecoins and Collateral Risk (Research Assistant)

The paper study the mechanisms that govern price stability of MakerDAO's DAI token, the first decentralized stable coin.Using data on the universe of collateralized debt positions, we show that DAI price covaries negatively with returns to risky collateral. The peg-price volatility is related to collateral risk, while the stability rate has little ability to stabilize the coin. The introduction of safe collateral types has led to an increase in peg stability

News and After-Hours Trading in Equities market (Research Assitant)

This paper explores after-hours trading (AHT) in U.S. equity markets.

Effects of Airbnb on the housing market: Evidence from London.

I combine data from Airbnb and Zoopla and examine how the prices of individual houses evolve over time as Airbnb penetrates the market in Greater London.

Do workers, managers, and stations matter for effective policing? A decomposition of productivity into three dimensions of unobserved heterogeneity.

I develop an estimation methodology that allows for three-sided heterogeneity. I implement this on matched panel data. I use machine learning in the classification step of the estimation of a Markovian model of worker mobility and apply it to novel data on police departments.

Resisting modernisation due to resentment? Evidence from British India.

Using novel data combining the religion of the final pre-colonial ruler with literacy outcomes of Hindus and Muslims in India between 1881 and 1921, we show that religious groups resisted modern education due to foreign occupation.

Private Returns to Bureaucratic Appointments: Evidence from Financial Disclosures

We examine the high-powered financial incentives for bureaucrats. We digitize the financial disclosures of elite bureaucrats from India and combine this novel data with web-scraped career histories to estimate the private returns to public servants …