Knowledge that Transforms

This paper compares three methods for assessing the contagion of risk among ten Globally Significant International Banks, known as GSIBs, listed on the New York Stock Exchange with daily and weekly data sets from 2007 to 2020, based on Machine Learning and Network Analysis. In particular we identify the banks which are the largest net sources or transmitters of risk, and net receptors of risk. We also examine the response of regulatory actions, in the form of fines and BIS Bin Classification for capital adequacy. Under alternative risk measures, of Range Volatility (RV) of share prices, Credit Default Swap (CDS) premia, and Conditional Value at Risk (ΔCoVar), there is a stronger and significant connection between Contagion and the BIS Bin classifications relative to the connections between Contagion and banking fines, either in the amount or frequency of the fines. These results show that BIS bin classifications respond positively to underlying signals of increased contagion in the form of Range Volatility (RV) and ΔCoVar measures but not to CDS risk premia.

This paper analyses the trade-off between additional loss-absorbing capacity and potentially higher bank risk-taking associated with the introduction of the Basel III Leverage Ratio. This is addressed in both a theoretical and empirical setting. Using a theoretical micro model, we show that a leverage ratio requirement can incentivise banks that are bound by it to increase their risk-taking. This increase in risk-taking however, should be outweighed by the benefits of higher capital, thereby leading to more stable banks. These theoretical predictions are tested and confirmed in an empirical analysis on a large sample of EU banks. Our baseline empirical model suggests that a leverage ratio requirement leads to a significant decline in the distress probability of highly leveraged banks.

We find that societal trust—the extent to which residents of a country trust others—is associated with a more efficient bankruptcy process. Bankruptcy resolutions are faster, efficient outcomes are more likely, and the value lost during the bankruptcy process is lower in countries with higher societal trust. This effect of societal trust on the efficiency of the bankruptcy process is more pronounced in countries with low-income per capita, and in corrupt countries. Our results are derived from the analysis of survey data concerning the outcomes of a hypothetical firm's bankruptcy in 99 countries from 2004 to 2020, a dataset also utilized by Djankov et al. (2008).

First, a rational bubble with a stochastic crash is modelled under conditions of timelessness (or strictly a zero interest rate) and an infinite number of investors. The necessary and sufficient conditions for this bubble are a strictly positive bubble premium and a sufficient number of investors. Second, it is shown that a rational bubble occurs under a strictly negative interest rate. Finally, whether bubbles can be prevented or landed is discussed.

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.

Using granular data from the Spanish Credit Register, we study the contagion of financial distress via the credit quality channel in the Spanish interbank market. We propose a non-linear contagion mechanism dependent on banks’ balance-sheet structure (specifically, their leverage ratios). Moreover, we explicitly model uncertainty in lenders’ assessments of the probability of default of their borrowers, thus incorporating agents’ lack of complete information and heterogeneous expectations in their assessment of future outcomes. We perform multiple simulations across a wide range of possible levels of stress in the system, and we focus on disentangling the effects of these two key model components by comparing the results of our model with those of a linear and deterministic counterpart. In this way, we find that non-linear contagion leads to substantially larger losses than its linear counterpart for a wide range of intermediate levels of stress in the system, while its effects become negligible for very low and very high stress levels. Regarding uncertainty, we find that its effects, while smaller than those of non-linear contagion, are nonetheless relevant and most important around levels of stress at which different parts of the system become unstable. Interestingly, losses can be amplified or mitigated with respect to the deterministic case depending on the specific level of stress considered. Finally, the interaction between both model components—non-linear contagion and uncertainty—alters the area where uncertainty matters.

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 shows how the combined endogenous reaction of banks and investment funds to an exogenous shock can amplify or dampen losses to the financial system compared to results from single-sector stress testing models. We build a new model of contagion propagation using a very large and granular data set for the euro area. Based on the economic shock caused by the Covid-19 outbreak, we model three sources of exogenous shocks: a default shock, a market shock and a redemption shock. Our contagion mechanism operates through a dual channel of liquidity and solvency risk. Our analysis reveals that adding the fund sector to our model for banks leads to additional losses through fire sales and a further depletion of banks’ capital ratios by around one percentage point. The main driver of additional bank losses are endogenous market losses generated by investment funds’ asset liquidation.

This paper finds the first evidence of time variation in the relationship between inflation expectations and the price of cryptocurrency futures. Daily data on the futures markets of Bitcoin – starting in December 2017 – and Ethereum – available since February 2021 – reveal responses to inflation expectations that are consistently positive across both measures in a full sample encompassing 2022. These results hold for a sample that precedes the Luna crash in May 13, 2022. However, the response turns negative in the period between the failures of the Luna and FTX crypto exchanges. We find cryptocurrency futures provide an effective hedge against inflation expectations and may provide a hedge against idiosyncratic market risk if the ensuing uncertainty is embraced by traders leading them to search-for-yield behavior. Risk that is more systemic – and not properly digested by financial markets – may lead futures contract holders to exit their positions ahead of expiration, leading to a bid down of futures prices and an erosion of their hedging ability. This may have contributed to the turbulence in cryptocurrencies experienced during the latter part of 2022.

This paper examines the impact of bank opacity on European financial stability. Based on a panel dataset of listed European banks covering the period 2002–2018, I find that bank opacity has a significant influence on the institution-specific contribution to the ∆Conditional Value at Risk and Marginal Expected Shortfall. The enforcement mechanism and the policies introduced by accounting standard setters and regulators for the risk disclosure of banks have a positive impact on the reduction of systemic risk. Both the risk reporting in accordance with IFRS 7 and the measures introduced by the Basel Committee in the form of the Basel Pillar 3 regulation led to an increase in transparency and thus an improvement in financial market stability. As an independent enforcement mechanism, the country-specific strength of the external auditing profession plays a significant role in fostering stability. The results are robust, by using both alternative opacity measures and instrumental-variable estimations (2SLS) to control for potential endogeneity.