Research


I'm a 4th-year Ph.D. candidate in Economics and Finance at the University of California, Berkeley. My research interest lies in the field of finance, market microstructure, and FinTech.






Upcoming Presentation
  • Georgia State University/RFS FinTech Conference: 2/8,9 at GSU.
  • Stern Annual Microstructure Meeting: 5/10 at NYU Stern.
  • Southampton Cryptocurrency Research Conference: 6/15,16 at U of Southampton (by my coauthor).
  • Northern Finance Association Conference: 9/13 at Vancouver, Canada.
Working Papers


"The empirical analysis of Bitcoin market in the general equilibrium framework,"  with T. Hattori (MOF, Japan) July 2019 [SSRNpdf].

This paper firstly pursues the fundamental price of Bitcoin in the general equilibrium framework and its empirical characteristics. Our theoretical model predicts that (i) the Bitcoin price and the total hash rate are determined simultaneously in the long-run and (ii) the hash rate of Bitcoin Granger-causes Bitcoin prices in the short-run. Using a cointegration framework, our empirical analysis provides consistent results with these theoretical predictions. Our empirical results suggest that the Bitcoin market has been under a fundamental value instead of speculative bubbles.


"Industry Competition: The Blockchain versus Centralized Authority,"  July 2019 [SSRNpdf].

Existing industries must deal with encroachment by the blockchain protocol. We provide an abstract asset-trading model to analyze the competition between the blockchain operated by the distributed ledger system (DLS) and the traditional industry run by a centralized authority. They both provide a trading method to users (traders) and try to mitigate information asymmetry between users. In contrast to the traditional models of industry competition (e.g., Bertrand and Cournot), the blockchain’s strategy is determined competitively by its miners and users. Our model characterizes when and why the blockchain can be more efficient than the centralized authority and investigates why we need the blockchain system in addition to the existing trading methods.


"A Unified Theory of the Blockchain Economy,"  April 2019 [SSRNpdf].

In a blockchain economy, the incentive of record keepers and activity of blockchain users interact with each other through general equilibrium effects. On the one hand, users (buyers and sellers of goods) make transactions by using the blockchain protocol to mitigate informational frictions, and this activity pins down the demand for cryptocurrency and affects its price. On the other hand, record keepers maintain the blockchain system and determine how efficiently it can mitigate informational frictions among users, thereby affecting the users' activity and price of cryptocurrency. However, the price of cryptocurrency also affects the record keepers' behavior because they are motivated by a reward that is paid in cryptocurrency. These channels generate a feedback (complementarity) effect that is boiled down to a fixed point problem. We show that multiple equilibria can arise in which collective deviation of miners (e.g., fork) can deteriorate the blockchain's efficiency and consumers' welfare.


"Speed Choice by High-Frequency Traders with Speed Bumps,"  July 2018 [SSRNpdf, slides], 
-awarded the 2018 Moriguchi Prize at ISER Osaka University.
-Presented at NYU Stern Annual Microstructure Meeting, Berkeley Finance Seminar, Osaka University ISER, University of Tokyo.

We study how high-frequency traders (HFTs) strategically decide their speed level in a market with a random speed bump. If HFTs recognize the market impact of their speed decision, they perceive a wider bid-ask spread as an endogenous upward-sloping cost of being faster. We find that the speed elasticity of the bid-ask spread (slope of the endogenous cost function) negatively depends on the expected length of a speed bump since a longer delay makes market makers insensitive to HFTs' speed increment. Hence, speed bumps promote the investment of HFTs in high-speed technology by reducing the marginal cost of getting faster, undermining their intended purpose of protecting market makers. Depending on the expected length of a bump, an arms race among HFTs exhibits both complementarity and substitution. These findings explain the ambiguous empirical results regarding speed bumps and adverse selection for market makers.


"Economic Implications of Blockchain Platforms,"  with D. Adachi (Yale), Feb 2018 [SSRNpdf], 
- Presented at NFA Conference (planned), Southampton CRC, RFS/GSU FinTech Conference, SWET at Hokkaido, WINDS at UPenn.

In an economy with asymmetric information, the smart contract in the blockchain protocol mitigates the uncertainty. Since the blockchain as a new trading platform triggers market segmentation and differentiation of agents in both of the sell- and buy-sides of the market, it reconfigures the asymmetric information and generates spreads in asset price and quality between the blockchain platform and traditional one. We show that marginal innovation and sophistication of the smart contract have non-monotonic effects on the trading value in the blockchain platform, its fundamental value, the price of cryptocurrency, and consumers’ welfare. Moreover, a blockchain manager, who controls the level of the innovation of the smart contract, has an incentive to keep it lower than the first-best level when the underlying asymmetric information is not severe, leading to welfare loss for consumers. 


"Endogenous Information Cycles," June 2017  [SSRNpdf][slides][OnlineAppendix], R&R at Journal of Economic Theory.

A simple generalization of an existing study regarding information and business cycles allows us to explain an endogenous bust. In such a cycle, a booming economy experiences a bust despite the absence of an exogenous trigger shock; instead, increasing economic activity in a boom state itself causes a crash. The key to understanding this is a feedback loop between investment activity and the efficiency of a public signal that aggregates market information and determines the aggregate risk. The high-risk and low economic activity augment each other (a positive feedback), making the downturn state stable. In a low-risk and high-activity state, however, the feedback can be negative: an increasing activity contaminates the public signal, generating a spike in the risk. Since a switch from the positive to negative feedback is governed by the endogenous level of the economic activity, a transition from a boom to crash is explained as an endogenous event.


"Information Contamination and Market Crashes," Dec 2016 [SSRNpdf] [codes]
I study self-organized market crashes with overshooting. Unlike standard models, booms and busts happen without any aggregate shocks nor successive idiosyncratic shocks. Only one idiosyncratic trigger shock explains the entire boom/bust through the interaction between ambiguity averse traders. They exhibit Ss-type inaction behavior, and their consecutive participation leads to the price upheaval, while the price information becomes imprecise during the boom. Then, this triggers the sudden escape of some traders from the market, which, in turn, leads to the further escape of other traders and the crash. I also analyze the soft-landing scenario and the long-run behavior of the economy. 

Research at Early Stages
"Asset Price Bubbles and Inflation Rate" [pdf] (Master's thesis)
"Long-run implications of a tiny delay in high-speed markets"
"Over-the-counter markets in the blockchain era"