Quantitative Finance

Otani, Suguru

doi: 10.48550/arxiv.2204.00713pmid: N/A

Abstract:As the widely applied method for measuring matching assortativeness in a transferable utility matching game, a matching maximum score estimation is proposed by \cite{fox2010qe}. This article reveals that combining unmatched agents, transfers, and individual rationality conditions with sufficiently large penalty terms makes it possible to identify the coefficient parameter of a single common constant, i.e., matching costs in the market.

Şoiman, Florentina;Dumas, Guillaume;Jimenez-Garces, Sonia

doi: 10.1016/j.intfin.2023.101786pmid: N/A

Abstract:Decentralized Finance (DeFi) is a nascent set of financial services, using tokens, smart contracts, and blockchain technology as financial instruments. We investigate four possible drivers of DeFi returns: exposure to cryptocurrency market, the network effect, the investor's attention, and the valuation ratio. As DeFi tokens are distinct from classical cryptocurrencies, we design a new dedicated market index, denoted DeFiX. First, we show that DeFi tokens returns are driven by the investor's attention on technical terms such as "decentralized finance" or "DeFi", and are exposed to their own network variables and cryptocurrency market. We construct a valuation ratio for the DeFi market by dividing the Total Value Locked (TVL) by the Market Capitalization (MC). Our findings do not support the TVL/MC predictive power assumption. Overall, our empirical study shows that the impact of the cryptocurrency market on DeFi returns is stronger than any other considered driver and provides superior explanatory power.