Journal of Financial Stability最新文献

Blockchain is a ground-breaking technology with potential applications in fundraising. In this study, we analyze the blockchain-based fundraising data from 2019 to 2021 to investigate the differences between various fundraising models (i.e., ICO, IEO, IDO, and MIX). More specifically, in Study 1, we conduct ANCOVA and ANOVA to examine differences in fundraising success and token performance after listing between different fundraising models. In Study 2, we first explore the factors that affect fundraising success and token performance, and then verify whether the impact of these factors varies between fundraising models. The findings of our research have implications for both firms and investors, assisting firms in selecting the most effective fundraising models and aiding investors in identifying tokens with the greatest potential.

This article examines how competition between banks and a digital PSP impacts the lending rate and the consumers’ use of payment instruments. The digital PSP offers a digital wallet and payment services, but does not offer credit. In contrast, banks invest their deposits in lending activities, which implies that they may incur some costs of adjusting their liquidity needs when consumers make payments. I show that the adoption of the digital wallet for payments may sometimes increase the volume of payments by bank deposit transfers and the lending rate. This results from banks’ trade-off between lowering their costs of liquidity when consumers pay from their digital wallet and reducing the revenues they receive from bank transfer fees.

We develop a general equilibrium model that highlights the trade-offs between physical and digital forms of retail central bank money. The key differences between cash and central bank digital currency (CBDC) include transaction efficiency, possibilities for tax evasion, and, potentially, nominal rates of return. We establish conditions under which cash and CBDC can co-exist and show how government policies can influence relative holdings of cash, CBDC, and other assets. We illustrate how a CBDC can facilitate negative nominal interest rates and helicopter drops, and also how a CBDC can be structured to prevent capital flight from other assets.

Decentralized Autonomous Organization (DAO) is very popular in Decentralized Finance (DeFi) applications as it provides a decentralized governance solution through blockchain. We analyze the governance characteristics in the Maker protocol, its stablecoin DAI and its governance token Maker (MKR). To achieve that, we establish several measurements of centralized governance. Our empirical analysis investigates the effect of centralized governance over a series of factors related to MKR and DAI, such as financial, network and Twitter sentiment indicators. Our results show that governance centralization influences the Maker protocol and that the distribution of voting power matters. The main implication of this study is that centralized governance in MakerDAO very much exists, while DeFi investors face a trade-off between decentralization and performance of a DeFi protocol. This further contributes to the contemporary debate over whether DeFi can be truly decentralized.

Despite high volatility, Bitcoin is known to offer diversification benefits through its relatively low correlation with stock markets. Unlike traditional safe-haven assets, Bitcoin prices strongly respond to time-varying correlations and diversification benefits. We find that a decrease (an increase) in correlation between Bitcoin and S&P500 index returns strongly predicts higher (lower) Bitcoin returns the next day. Under the classical mean–variance framework, we develop a stylized model of Bitcoin prices utilizing extreme disagreement among heterogeneous Bitcoin investors. When our model is calibrated to the observed predictability of Bitcoin returns, the model simultaneously explains the lack of predictability in traditional safe-haven assets such as gold and long-term treasuries.

We examine implications of a central bank digital currency (CBDC) for banks using business models particularly dependent on customer deposits. Employing unique customer data hand-collected from German savings and cooperative banks, we generate conversion rates for deposits into a CBDC. Even at moderate conversion rates, most banks would have experienced funding problems and lost profits if a CBDC had been introduced in most years from 2000 onward. Our results are relevant for commercial banks, contributing to better assessments of the impact of CBDCs on liquidity and profitability and help central banks to identify implementation costs for banks within historical and hypothetical interest rate environments.

We provide a systematic classification and evaluation of the different types of digital currencies. We express skepticism regarding centralized digital currencies and focus our economic analysis on private digital currencies. We specifically highlight the potential for private digital currencies to improve welfare within an emerging market with a selfish government. In that setting, we demonstrate that a private digital currency not only improves citizen welfare but also encourages local investment and enhances government welfare. The fact that a private digital currency enhances government welfare implies a permissive regulatory policy which enables citizens to realize the previously referenced welfare gains.

This paper uses a stylized simulation model to assess the potential impact of climate transition risk on banks’ balance sheets in a climate-stress-testing (i.e. short-run) framework. We show that a moderate to high transition risk increases overall bank losses only relatively modestly if the baseline is a stressed macroeconomic scenario. However, even in a benign macroeconomic scenario, if high-carbon assets are at least 13% riskier than comparable assets a fire sale mechanism could amplify an initially contained shock into a systemic crisis, resulting in significant losses for the EU banking sector. We show that transition risks are concentrated, and find that an additional capital buffer of 0.9% risk-weighted assets on average would be sufficient to protect the system.

This paper quantifies the Too-Systemic-To-Fail (TSTF) paradigm in the Eurozone since the introduction of the Euro through three primary dimensions: Too-Big-To-Fail (TBTF), Too-Interconnected-To-Fail (TITF), and Too-Many-To-Fail (TMTF). We apply prominent systemic risk measures based on public data, including the Granger-causality network (GCN), Delta Conditional Value-at-Risk (ΔCoVaR), Marginal Expected Shortfall (MES), and Systemic Risk Index (SRISK). Financial interconnectedness and systemic risk exposure within the 17-member states of the Eurozone are measured on two levels: (i) identifying which financial sectors (banking, diversified financials, insurance, and real estate) are most exposed to systemic risk in the Eurozone at the union level; and (ii) identifying which member state is most exposed to systemic risk within each financial sector at the country level. We extend the original ΔCoVaR, MES and SRISK models by incorporating the bootstrap Kolmogorov-Smirnov stochastic dominance test to rank institutions based on their exposure to systemic risk formally.

We investigate the time variation in credit rating standards awarded to financial institutions of commercial bank credit ratings awarded by the three principal CRAs from 1990 to 2015 in a world-wide context by testing for well-defined structural shifts. We focus on the part of the ratings that cannot be accounted using publicly available information. We test whether major financial events are conditioning, ex-post such changes Distinctively in this paper’s timespan our analysis covers four periods: (i) before and (ii) after the 2001–2 corporate collapses, followed by (iii) before the global financial crisis and (iv) after the global financial crisis. We find substantial differences in the assignment of bank credit ratings among the three major agencies, Moody’s, Fitch, and S&P. Agencies differ both in terms of re-adjustment of ratings but also on the speed of response to the evens. All three agencies tightened ratings during the 2008 crisis and kept reducing them in its aftermath.