Bank stock performance and bank regulation around the globe.

We analyze the effect of bank capital, regulation, and supervision on the annual stock performance of global banks during the period of 1999–2012. We study a large comprehensive panel of international banks and find that higher Tier 1 capital decreases a bank's stock performance over the whole sample period. However, during turbulent times stocks of more highly capitalized banks perform significantly better. Additionally, we find strong evidence that banks that are more likely to receive government bailout during financial distress realize smaller stock performance. In contrast, we find no convincing evidence that banks that generate higher non-interest income have a higher performance

Bitcoin Under the Microscope

This paper explores and describes historical on-chain transaction data recorded on the Bitcoin blockchain, constructs a panel of all individual Bitcoin users, and computes their balances in the cross-section and over time. We run clustering algorithms to combine addresses that belong to the same user into wallets and we find that using wallets over addresses as the unit of analysis allows for more economically meaningful interpretations of user behavior. We identify and divide wallets into user categories - miners, exchanges, services, retail wallets and receiving-only addresses - and observe varying activity levels and balances in the cross-section and over time, corresponding to their intended role in the Bitcoin network. Our findings also suggest heterogeneity in financial performance across user categories with miners exhibiting higher realized returns relative to exchanges and retail users

Do Capital Requirements Make Banks Safer? Evidence from a Quasinatural Experiment

We use the EBA capital exercise of 2011 as a quasi-natural experiment to investigate how capital requirements affect various measures of bank solvency risk. We show that, while regulatory measures of solvency improve, non-regulatory measures indicate a deterioration in bank solvency in response to higher capital requirements. The decline in bank solvency is driven by a permanent reduction in banks’ market value of equity. This finding is consistent with a reduction in bank profitability, rather than a repricing of bank equity due to a reduction of implicit and explicit too-big-too-fail guarantees. We then discuss alternative policies to improve bank solvency

Bitcoin under the microscope

This paper explores and describes historical on-chain transaction data recorded on the Bitcoin blockchain, constructs a panel of all individual Bitcoin users, and computes their balances in the cross-section and over time. We run clustering algorithms to combine addresses that belong to the same user into wallets and we find that using wallets over addresses as the unit of analysis allows for more economically meaningful interpretations of user behavior. We identify and divide wallets into user categories -- miners, exchanges, services, retail wallets and receiving-only addresses -- and observe varying activity levels and balances in the cross-section and over time, corresponding to their intended role in the Bitcoin network. Our findings also suggest heterogeneity in financial performance across user categories with miners exhibiting higher realized returns relative to exchanges and retail users

Coin concentration of Proof-of-Stake blockchains

This paper studies the concentration of block production in selected Proof-of-Stake (PoS) blockchains and finds evidence consistent with participants entering and leaving the consensus process, thereby changing the concentration level, but not with disproportionate compounding of wealth for large stakes

Bitcoin under the microscope

This paper explores and describes historical on-chain transaction data recorded on the Bitcoin blockchain, constructs a panel of all individual Bitcoin users, and computes their balances in the cross-section and over time. We run clustering algorithms to combine addresses that belong to the same user into wallets and we find that using wallets over addresses as the unit of analysis allows for more economically meaningful interpretations of user behavior. We identify and divide wallets into user categories – miners, exchanges, services, retail wallets and receiving-only addresses – and observe varying activity levels and balances in the cross-section and over time, corresponding to their intended role in the Bitcoin network. Our findings also suggest heterogeneity in financial performance across user categories with miners exhibiting higher realized returns relative to exchanges and retail users

How are texts analyzed in blockchain research? A systematic literature review

Abstract This paper provides a systematic literature review of text analysis methodologies used in blockchain-related research to comprehend and synthesize existing studies across disciplines and define future research directions. We summarize the research scope, text data, and methodologies of 124 papers and identify the two most common combinations of these dimensions: (1) papers that focus on specific cryptocurrencies tend to apply sentiment analysis to instant user-generated content or news articles to discover the correlations between public opinion and market behavior, and (2) studies that examine the broad concept of blockchain with text data from documents published by companies tend to apply topic modeling techniques to explore classifications and trends in blockchain development. We discover five major research topics in the academic literature: relationship discovery, cryptocurrency performance prediction, classification and trend, crime and regulation, and perception of blockchain. Based on these findings, we highlight three potential research directions for researchers to select topics and implement suitable methodologies for text analysis

A Comparison of Tail Dependence Estimators

We review several commonly used methods for estimating the tail dependence in a given data sample. In simulations, we show that especially static estimators produce severely biased estimates of tail dependence when applied to samples with time-varying extreme dependence. In some instances, using static estimators for time-varying data leads to estimates more than twice as high as the true tail dependence. Our findings attenuate the need to account for the time-variation in extreme dependence by using dynamic models. Taking all simulations into account, the dynamic tail dependence estimators perform best with the Dynamic Symmetric Copula (DSC) taking the lead. We test our findings in an empirical study and show that the choice of estimator significantly affects the importance of tail dependence for asset prices