Stablecoins rise to meet the demand for safe assets in decentralized finance. Stablecoin issuers transform risky reserve assets into tokens of stable values, deploying a variety of tactics. To address the questions on the viability of stablecoins, regulations, and the initiatives led by large...

Stablecoins rise to meet the demand for safe assets in decentralized finance. Stablecoin issuers transform risky reserve assets into tokens of stable values, deploying a variety of tactics. To address the questions on the viability of stablecoins, regulations, and the initiatives led by large...

This paper makes use of a reform that allowed firms to use patents as stand-alone collateral, to estimate the magnitude of collateral constraints and to quantify the aggregate impact of these constraints on misallocation and productivity. Using matched firm-bank data for Norway, we find that...

This paper makes use of a reform that allowed firms to use patents as stand-alone collateral, to estimate the magnitude of collateral constraints and to quantify the aggregate impact of these constraints on misallocation and productivity. Using matched firm-bank data for Norway, we find that...

In this study, we compare the out-of-sample forecasting performance of several modern Value-at- Risk (VaR) estimators derived from extreme value theory (EVT). Specifically, in a multi-asset study covering 30 years of stock, bond, commodity and currency market data, we analyse the accuracy of the...

We propose a new method (implemented in an R-program) to simulate long-range daily stock-price data. The program reproduces various stylized facts much better than various parametric models from the extended GARCH-family. In particular, the empirically observed changes in unconditional variance...

The empirical literature of stock market predictability mainly suffers from model uncertainty and parameter instability. To meet this challenge, we propose a novel approach that combines the documented merits of diffusion indices, regime-switching models, and forecast combination to predict the...

The empirical literature of stock market predictability mainly suffers from model uncertainty and parameter instability. To meet this challenge, we propose a novel approach that combines the documented merits of diffusion indices, regime-switching models, and forecast combination to predict the...

Cryptocurrencies are often thought to operate out of the reach of national regulation, but in fact their valuations, transaction volumes and user bases react substantially to news about regulatory actions. The impact depends on the specific regulatory category to which the news relates: events...

The emergence of so-called "decentralised finance" (DeFi) and a shadow financial system of cryptocurrency exchanges and stablecoin issuers raises the challenge of how to apply technology-neutral regulation so that similar risks are subject to the same rules. This paper makes the case for...