Digitalization has led to a rapid expansion of loyalty tokens typically bundled as part of product price. An open question is whether, as technology evolves, firms will have a strong incentive to make loyalty tokens tradable, thereby raising regulation issues, including for monetary and banking authorities. Our main finding is that, under fairly general assumptions, firms will still have strong incentives to maintain non-tradability. This may seem surprising, given that an individual consumer would be willing to pay a premium for tradable tokens. However, provided the tokens do not offer a convenience yield to non-platform consumers, non-tradability compensates by expanding the outstanding stock of tokens outstanding at any one time, thereby providing a better overall form of financing. We further show that an issuer with stronger market power tends to make its revenue more token-dependent. Empirical results from airline mileage and hotel reward programs align with our theory.

Trust fundamentally shapes financial activities, and the persistent variation in trust across societies may lead to huge financial development gap in the globe. We model trust as the collective reputation of borrowers and study how trust exhibits persistent variation across societies, consequently leading to divergent credit and economic growth. Our theory demonstrates distrust to be a self-fulfilling prophecy: lenders believe borrowers are more likely to default and raise interest rates, reducing borrowers' incentive to repay loans, thus fulfilling the expected low trust environment. This shows that high-trust and low-trust equilibria can both exist even in the same society. Financial deregulation benefits high-trust countries more as trust enforces good behaviors in equilibrium. The informal credit market amplifies the equilibrium divergence. Empirically, distrust persistently predicts less formal borrowing, lower credit card ownership, and lower GDP growth with 50% predictability attributed to slower credit expansion. Micro-level evidence explains how trust affects individuals’ switching to informal credit sources. Financial liberalization fosters higher GDP growth in high-trust countries but the opposite in low-trust countries.

Tokens offer convenience in digital networks and earn rewards when staked for consensus generation or economic activities. In our continuous-time model, agents dynamically allocate wealth over on-platform transactions and staking. Aggregate staking ratio crucially shapes platform productivity, grows userbase, and links staking to endogenous reward rates and price dynamics. Transaction fees, token issuance, and user heterogeneity all affect platform lifecycle. Empirical findings support the theoretical predictions: (i) correlation between staking ratio and reward rate is cross-sectionally positive, but time-series-wise negative; (ii) staking ratios positively predict excess returns; (iii) the convenience wedge generates UIP violations and significant crypto carry premia. 

We document a novel high-volume overnight premium (intraday discount). Specifically, stocks with high trading volume exhibit remarkable future outperformance (underperformance) during overnight (intraday) period. The results are pervasive across global equity markets, robust to alternative measures of trading volume, and persistent for at least three years after portfolio formation. Aligned with a model of heterogeneous investors, the overnight premium and intraday discount are more pronounced when (uninformed) investors are more optimistic or certain about the economy. The predictability of trading volume mainly stems from its retail activity component.

Digital platforms are increasingly serving as intermediaries in delegated investment, particularly by adopting recommendation algorithms that deliver personalized suggestions to a large user base. We develop a model to analyze the platform's investor-optimal algorithm design where investors with heterogeneous risk aversion contract with a portfolio manager based on recommendation status. Investors may have limited knowledge about their types, while the manager has risk-chasing incentives due to limited liability. We demonstrate that algorithms can mitigate managers' moral hazard in over risk-taking -- without affecting the contract -- by acting as both information gatekeepers and commitment devices, harnessing the scale of the user base. Optimal recommendation probabilities are non‑monotonic in historical returns. Unlike in consumption platforms, algorithms here extract noisy signals about the manager's actions from historical returns, reduce recommendations under ambiguous signals, and potentially compensate for clear signals, leading to an information rent paid by investors. We further discuss on algorithmic inequality, the joint design of algorithms and contracts, and compariso ns to fund ranking systems. Our results emphasize the innovative role of recommendation algorithms as a digital financial service. Methodologically, we provide a general approach for algorithm design problems in function space with potentially non-monotonic solutions.  

We examine the performance difference between A-share-listed companies in Southern and Northern China. Based on the data from 1996 to 2019, we find that Southern China outperforms Northern in terms of the number of listed companies, aggregate market value, revenue and profit growth rates. We provide a mechanism to explain the observed performance difference between the listed companies in Southern and Northern China. Further analysis suggests that this difference is closely related to the regional business environment, financial resource allocation, and economic policies, and is one of the important reasons for the widening of the economic gap between Southern and Northern China. We provide policy recommendations based on our findings. 

We evaluate the cross-country convergence of financial development and its relationship with GDP growth. Financial inclusion variables have been widely converged across countries, and the catch-up effect of countries with poor financial coverage mainly drives the convergence. In contrast, financial development measures — including domestic credit, liability, mutual fund size, and stock market capitalization — have diverged since 1985 despite the absolute convergence in GDP and financial inclusion. The GDP growth rates strongly correlate with the change in financial development but not the improvement in financial inclusion.