The Market Reaction to Interest Rate Change: The Effect of Financial Leverage

This research project examines the relationship between the financial leverage of firms with total book assets above $50M and the Target Federal Fund Rate changes during 1990 to 2015. We do not find that the value-weighted index is affected by change in interest rates. We find that increases in interest rate tends to hurt firms with higher book leverage (debt divided by total assets) than firms with low leverage. Unfortunately, these results do not seem to be robust, and we believe that the major reasons for that is that we use the full interest rate change, rather than the unanticipated component of interest rate change, which is unobservable

On Blockchain We Cooperate: An Evolutionary Game Perspective

Cooperation is fundamental for human prosperity. Blockchain, as a trust machine, is a cooperative institution in cyberspace that supports cooperation through distributed trust with consensus protocols. While studies in computer science focus on fault tolerance problems with consensus algorithms, economic research utilizes incentive designs to analyze agent behaviors. To achieve cooperation on blockchains, emerging interdisciplinary research introduces rationality and game-theoretical solution concepts to study the equilibrium outcomes of various consensus protocols. However, existing studies do not consider the possibility for agents to learn from historical observations. Therefore, we abstract a general consensus protocol as a dynamic game environment, apply a solution concept of bounded rationality to model agent behavior, and resolve the initial conditions for three different stable equilibria. In our game, agents imitatively learn the global history in an evolutionary process toward equilibria, for which we evaluate the outcomes from both computing and economic perspectives in terms of safety, liveness, validity, and social welfare. Our research contributes to the literature across disciplines, including distributed consensus in computer science, game theory in economics on blockchain consensus, evolutionary game theory at the intersection of biology and economics, bounded rationality at the interplay between psychology and economics, and cooperative AI with joint insights into computing and social science. Finally, we discuss that future protocol design can better achieve the most desired outcomes of our honest stable equilibria by increasing the reward-punishment ratio and lowering both the cost-punishment ratio and the pivotality rate

Positive solutions of higher order fractional integral boundary value problem with a parameter

In this paper, we study a higher-order fractional differential equation with integral boundary conditions and a parameter. Under different conditions of nonlinearity, existence and nonexistence results for positive solutions are derived in terms of different intervals of parameter. Our approach relies on the Guo–Krasnoselskii fixed point theorem on cones

SoK: Blockchain Decentralization

Blockchain empowers a decentralized economy by enabling distributed trust in a peer-to-peer network. However, surprisingly, a widely accepted definition or measurement of decentralization is still lacking. We explore a systematization of knowledge (SoK) on blockchain decentralization by comprehensively analyzing existing studies in various aspects. First, we establish a taxonomy for analyzing blockchain decentralization in the five facets of consensus, network, governance, wealth, and transaction. We find a lack of research on the transaction aspects that closely characterize user behavior. Second, we apply Shannon entropy in information theory to propose a decentralization index for blockchain transactions. We show that our index intuitively measures levels of decentralization in peer-to-peer transactions by simulating blockchain token transfers. Third, we apply our index to empirically analyze the dynamics of DeFi token transfers by three methods of description, prediction, and causal inference. In the descriptive analysis, we observe that levels of decentralization converge inter-temporally, regardless of the initial levels. A comparative study across DeFi applications shows that exchange and lending are more decentralized than payment and derivatives across DeFi applications. Second, in the predictive analysis, we also discover that a greater return of Ether, the native coin of the Ethereum blockchain, predicts a greater transaction decentralization in stablecoin that include Ether as collateral. Third, in an event study of causal inference, we find the change of Ethereum Transaction Fee Mechanism to EIP-1559 significantly changes the decentralization level of DeFi transactions. Finally, we identify future research directions

Effects of respondent training on self-report personality assessment: an item response theory approach

Within the item response theory (IRT) framework and inspired by the rater training literature, this study explored the effects of short online respondent training on personality item interpretation and responding and the number of response categories (i.e. polytomous vs. dichotomous) on item performance, model-data fit, and criterion-related validity. Participants recruited from MTurk (n = 1977) were randomly assigned to 1 of the 4 groups differing in training (i.e. training vs. no training) and response scale (i.e. 4-point Likert scale vs. dichotomous), and their responses to dominance and ideal-point personality measures were analyzed with GGUM, SGR, and 2PL. Results indicated that training was associated with more well-performing and more discriminating and informative intermediate items on the ideal-point scales when a dichotomous response scale was used. The dichotomous scale in general was related to better fit, while criterion-related validity stayed unaffected by both training and the response scale. Participants reported that they had been confused about personality items before, and were positive about the online training, which was consistent with the finding that trained participants on average spent 32 seconds less finishing the ideal-point surveys. Implications for future research and practice are discussed