Dynkin Games with Incomplete and Asymmetric Information

We study the value and the optimal strategies for a two-player zero-sum optimal stopping game with incomplete and asymmetric information. In our Bayesian setup, the drift of the underlying diffusion process is unknown to one player (incomplete information feature), but known to the other one (asymmetric information feature). We formulate the problem and reduce it to a fully Markovian setup where the uninformed player optimises over stopping times and the informed one uses randomised stopping times in order to hide their informational advantage. Then we provide a general verification result that allows us to find the value of the game and players’ optimal strategies by solving suitable quasi-variational inequalities with some nonstandard constraints. Finally, we study an example with linear payoffs, in which an explicit solution of the corresponding quasi-variational inequalities can be obtained.

Personalization from Customer Data Aggregation Using List Price

When consumers’ inferences of their reservation values are subject to environmental noise, firms can use customer data aggregation to obtain superior knowledge. This facilitates personalized pricing but may also induce consumer suspicions of overpaying. To alleviate the suspicions and convince consumers of their value, the firm may design its personalization scheme to include a list price in addition to the personalized prices. We find that only a separating equilibrium with list pricing survives the intuitive criterion. Specifically, when consumers underestimate their value, it is essential to use a binding list price to inform the consumers about the market’s price ceiling. Contrary to the conventional wisdom, the firm cannot abuse its informational advantage to steer consumers into overestimation, and price discrimination may strictly benefit the consumers who avoid overpaying. This paper was accepted by Dmitri Kuksov, marketing.

In Defense of Limited Manufacturing Cost Control: Disciplining Acquisition of Private information by Suppliers

When a firm's input supplier can acquire and misreport private information to gain an edge in negotiations, we show that the firm can blunt the supplier's informational advantage by permitting inefficiencies in its own internal production. Specifically, we establish that a modest increase in the cost of the input(s) a firm makes internally credibly commits it to be more aggressive in negotiations with a supplier for the input(s) the firm buys. Recognizing that its potential information rents will be limited, the supplier, in turn, becomes less aggressive in information acquisition. The paper fully characterizes the equilibrium - the firm's investments, the supplier's information acquisition and reporting decisions, and the terms of trade - to demonstrate that often-maligned internal bloat can be an endogenous facilitator of efficient outsourcing.

Price Discovery in the U.S. Treasury Cash Market: On Principal Trading Firms and Dealers

We explore the following question: does the trading activity of registered dealers on Treasury interdealer broker (IDB) platforms differ from that of principal trading firms (PTF), and if so, how and to what effect on market liquidity? To do so, we use a novel dataset that combines Treasury cash transaction reports from FINRA’s Trade Reporting and Compliance Engine (TRACE) and publicly available limit order book data from BrokerTec. We find that trades conducted in a limit order book setting have high permanent price impact when a PTF is the passive party, playing the role of liquidity provider. Conversely, we find that dealer trades have higher price impact when the dealer is the aggressive party, playing the role of liquidity taker. Trades in which multiple firms (whether dealers or PTFs) participate on one or both sides, however, have relatively low price impact. We interpret these results in light of theoretical models suggesting that traders with only a “small” informational advantage prefer to use (passive) limit orders, while traders with a comparatively large informational advantage prefer to use (aggressive) market orders. We also analyze the events that occurred in Treasury markets in March 2020, during the onset of the COVID-19 pandemic.

The Information View of Financial Crises

Short-term debt that can serve as a medium of exchange is designed to be information insensitive. No one should be tempted to acquire private information to gain an informational advantage in trading that could destabilize the value of the debt. Short-term debt minimizes the incentive to acquire information among all securities of equal value backed by the same underlying asset. Moreover, backing short-term debt with debt (i.e., using debt as collateral) minimizes information sensitivity across all types of collateral with equal value. These features are consistent with financial crises occurring periodically. In the information view adopted here, a financial crisis can occur when the collateral backing the short-term debt is thought to have lost enough value to raise doubts among the traders that some may acquire private information. In a crisis, there is a shift from information-insensitive to information-sensitive debt.

Portfolio Choice: Familiarity, Hedging, and Industry Bias

Investors may underdiversify their portfolios by overweighting securities in which they perceive an informational advantage or by underweighting securities to hedge risks outside the portfolio. We investigate underdiversification in institutional portfolio construction by examining the under/overweighting of industries in U.S. property–liability (PL) insurers’ equity portfolios. We find that PL insurers underweight both their own industry and highly correlated industries in their portfolios. This underweighting is larger for PL insurers exposed to higher underwriting risk. Although PL insurers have an informational advantage in investing in their peers, their underwriting risk drives them to underweight stocks in their industry.