Rationing in IPOs

We provide a model of bookbuilding in IPOs, in which the issuer can choose to ration shares. We consider two allocation rules. Under share dispersion, before informed investors submit their bids, they know that, in the aggregate, winning bidders will receive only a fraction of their demand. We demonstrate that this mitigates the winner’s curse, that is, the incentive of bidders to shade their bids. It leads to more aggressive bidding, to the extent that rationing can be revenue-enhancing. In a parametric example, we characterize bid and revenue functions, and the optimal degree of rationing. We show that, when investors’ information is diffuse, maximal rationing is optimal. Conversely, when their information is concentrated, the seller should not ration shares. We determine the optimal degree of rationing in a class of credible mechanisms. Our model reconciles the documented anomaly that higher bidders in IPOs do not necessarily receive higher allocations.IPOs

Competition for Listings

We develop a model in which two profit maximizing exchanges compete for IPO listings. They choose the listing fees paid by firms wishing to go public and control the trading costs incurred by investors. All firms prefer lower costs, however firms differ in how they value a decrease in trading costs. Hence, in equilibrium, the exchanges obtain positive expected profits by charging different trading fees and different listing fees. As a result, firms that list on different exchanges have different characteristics. The model has testable implications for the cross-sectional characteristics of IPOs' on different quality exchanges and the relationship between the level of trading costs and listing fees. We also find that competition does not guarantee that exchanges choose welfare maximizing trading rules. In some cases, welfare is larger with a monopolist exchange than with oligopolist exchanges.market microstructure; listings; competition; exchanges; regulation

Has the development of the structured credit market affected the cost of corporate debt? - comments

Credit

Liquidity fragmentation on decentralized exchanges

We study economies of scale in liquidity provision on decentralized exchanges, focusing on the impact of fixed transaction costs such as gas prices on liquidity providers (LPs). Small LPs are disproportionately affected by the fixed cost, resulting in liquidity supply fragmentation between low- and high-fee pools. Analyzing Uniswap data, we find that high-fee pools attract 58% of liquidity supply but execute only 21% of trading volume. Large (institutional) LPs dominate low-fee pools, frequently adjusting positions in response to substantial trading volume. In contrast, small (retail) LPs converge to high-fee pools, accepting lower execution probabilities to mitigate smaller liquidity management costs

Rationing in IPOs

We provide a model of bookbuilding in IPOs, in which the issuer can choose to ration shares. Before informed investors submit their bids, they know that, in the aggregate, winning bidders will receive only a fraction of their demand. We demonstrate that this mitigates the winner’s curse, that is, the incentive of bidders to shade their bids. It leads to more aggressive bidding, to the extent that rationing can be revenue-enhancing. In a parametric example, we characterize bid and revenue functions, and the optimal degree of rationing. We show that, when investors’ information is diffuse, maximal rationing is optimal. Conversely, when their information is concentrated, the seller should not ration shares. We provide testable predictions on bid dispersion and the degree of rationing. Our model reconciles the documented anomaly that higher bidders in IPOs do not necessarily receive higher allocations.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/42727/1/10679_2005_Article_2987.pd

Information acquisition in a limit order market

Abstract We model an infinite horizon trading game of a limit order market with informed traders. Agents with a private and common value motive for trade randomly arrive in a market and may either post prices (submit limit orders) or accept posted prices (submit market orders). If their orders have not executed, traders may reenter the market and thus solve a dynamic problem. We consider agents' incentive to acquire information. We characterize how information acquisition changes agents' strategies and demonstrate the effect of this on the efficiency of market prices. We demonstrate that for some costs of acquiring information, there are multiple equilibria in the information acquisition game. Finally, we demonstrate that information acquisition can make all agents worse off

What Drives the (In)stability of a Stablecoin?

In May 2022, an apparent speculative attack, followed by market panic, led to the precipitous downfall of UST, one of the most popular stablecoins at that time. However, UST is not the only stablecoin to have been depegged in the past. Designing resilient and long-term stable coins, therefore, appears to present a hard challenge. To further scrutinize existing stablecoin designs and ultimately lead to more robust systems, we need to understand where volatility emerges. Our work provides a game-theoretical model aiming to help identify why stablecoins suffer from a depeg. This game-theoretical model reveals that stablecoins have different price equilibria depending on the coin's architecture and mechanism to minimize volatility. Moreover, our theory is supported by extensive empirical data, spanning $1$ year. To that end, we collect daily prices for 22 stablecoins and on-chain data from five blockchains including the Ethereum and the Terra blockchain