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Economics of Financial Technology

Paper Session

Saturday, Jan. 5, 2019 10:15 AM - 12:15 PM

Hilton Atlanta, 405
Hosted By: Chinese Economic Association in North America & American Economic Association
  • Chair: Siu Fai Leung, Hong Kong University of Science and Technology

The Economics of Cryptocurrencies-Bitcoin and Beyond

Jonathan Chiu
,
Bank of Canada
Thorsten V. Koeppl
,
Queen's University

Abstract

How well can a cryptocurrency serve as a means of payment? We study the optimal design of cryptocurrencies and assess quantitatively how well such currencies can support bilateral trade. The challenge for cryptocurrencies is to overcome double-spending by relying on competition to update the blockchain (costly mining) and by delaying settlement. We estimate that the current Bitcoin scheme generates a large welfare loss of 1.4% of consumption. This welfare loss can be lowered substantially to 0.08% by adopting an optimal design that reduces mining and relies exclusively on money growth rather than transaction fees to finance mining rewards. We also point out that cryptocurrencies can potentially challenge retail payment systems provided scaling limitations can be addressed.

Textual Factors

William Cong
,
University of Chicago
Tengyuan Liang
,
University of Chicago

Abstract

Fintech startups leverage big/alternative/unstructured data, in particular texts, for originating loans, predicting stock returns, improving customer service, etc. Meanwhile, the interpretability of textual analysis can potentially help us better understand business economics and finance. We develop a textual-factor framework to analyze large-scale text-based data, which captures complex linguistic structures without sacrificing computational scalability and economic interpretability. We then demonstrate potential applications of our methodology to issues in finance and economics, such as asset returns, information transmission, and forecasts of economic outcomes. In particular, we introduce a text-based factor pricing model of asset returns. By combining the strengths of neural network language models and generative statistical modeling, our textual framework attempts to leverage high-performance computation and strike the balance between model complexity and interpretability.

Bitcoin as Decentralized Money: Prices, Mining, and Network Security

Emiliano S. Pagnotta
,
Imperial College London

Abstract

We address the determination and evolution of bitcoin prices in a simple monetary economy that captures the salient features of a decentralized network. Network users forecast the transactional and resale value of bitcoin holdings and consider the risk of a network attack. Miners contribute resources that enhance network security and compete for mining rewards received in units of the same unbacked token. In equilibrium, the overall production of network security and the bitcoin price are jointly determined. We characterize how the network technologies and participants, users and miners, affect the number and dynamic stability properties of equilibria. We find that the relation between bitcoin prices and the supply growth rate is not monotonic: the same price is consistent with different rates. The model’s outcomes demonstrate how intrinsic price–security feedback effects can amplify or moderate the price volatility effect of demand shocks. We find rational patterns of price momentum and crashes, and that small and large stochastic bubbles can exist in general equilibrium and show how the probability of bursting decreases with the bitcoin price.
Discussant(s)
Deniz Okat
,
Hong Kong University of Science and Technology
Jonathan Chiu
,
Bank of Canada
JEL Classifications
  • E5 - Monetary Policy, Central Banking, and the Supply of Money and Credit
  • G2 - Financial Institutions and Services