Abstracts

Bruno Bouchard: Perfect hedging with market impact

We introduce a model that takes market impact and illiquidity costs into account in the hedging of options. This model is based on a discrete rebalancement model with a linear impact (around the origin). We show that this model allows for perfect hedging of options (possibly up to face-lifting the payoff). When the option is uncovered, the price is a solution of a quasi-linear Black-Scholes equation and the hedge is based on a modified delta. When the option is covered, the hedge is the usual delta hedging but the price is a solution of a fully-nonlinear Hamilton-Jacobi-Bellman equation. A small impact development allows to get back to a hedge based on a model without impact up to a first order correction term (when the impact is small). We also provide a dual formulation in the covered case. Joint work with Grégoire Loeper, Mete Soner, Xiaolu Tan, Yiyi Zou and Chao Zhou.

Kostas Kardaras: Identifying Price Informativeness

We consider a market of financial securities with restricted participation, in which traders may not have access to the trade of all securities. The market is assumed thin: traders may influence the market and strategically trade against their price impacts. We prove existence and uniqueness of the equilibrium even when traders are heterogeneous with respect to their beliefs and risk tolerance. An efficient algorithm is provided to numerically obtain the equilibrium prices and allocations given market’s inputs. Joint work with Michail Anthropelos.

Ian Martin: Sentiment and Speculation in a Market with Heterogeneous Beliefs

We present a dynamic model featuring risk-averse investors with heterogeneous beliefs. Individual investors have stable beliefs and risk aversion, but agents who were correct in hindsight become relatively wealthy; their beliefs are overrepresented in market sentiment, so the market is bullish following good news and bearish following bad news. Extreme states are far more important for pricing than they would be in a homogeneous economy. Sentiment drives volatility up, and investors demand high risk premia in compensation. In a continuous-time Brownian limit, moderate investors supply liquidity: they trade against market sentiment in the hope of capturing a variance risk premium created by the presence of extremists. In a Poisson limit that features sudden arrivals of information, the price of insurance, which corresponds to a CDS rate, spikes up following bad news and declines during quiet times. Joint work with Dimitris Papadimitriou.

Marcel Nutz: Shorting in Speculative Markets

In models of trading with heterogeneous beliefs following Harrison‐Kreps, short selling is prohibited and agents face constant marginal costs‐of‐carry. The resale option guarantees that prices exceed buy‐and‐hold prices and the difference is identified as a bubble. We propose a model where risk‐neutral agents face asymmetric increasing marginal costs on long and short positions. Here, agents also value an option to delay, and a Hamilton‐Jacobi‐Bellman equation quantifies the influence of costs on prices. An unexpected decrease in shorting costs may deflate a bubble, linking financial innovations that facilitated shorting of mortgage‐backed securities to the collapse of prices. Joint work with José Scheinkman.

Emiliano Pagnotta: Becker Meets Kyle: Inside Insider Trading

How do illegal insiders trade on private information? Do they internalize legal risk? Using hand-collected data on insiders prosecuted by the SEC, we find that, consistent with Kyle (1985), insiders manage trade size and timing according to market conditions and the value of information. Gender, age, and profession play a lesser role. Various shocks to penalties and likelihood of prosecution show that insiders internalize legal risk by moderating aggressiveness, providing support to regulators’ deterrence ability. Consistent with Becker (1968), following positive shocks to expected penalties, insiders concentrate on fewer signals of higher value. Thus, enforcement actions could hamper price informativeness. Joint work with Marcin Kacperczyk.

Cecilia Parlatore: Identifying Price Informativeness

We show that outcomes (parameter estimates and R-squareds) of regressions of prices on fundamentals allow us to recover exact measures of the ability of asset prices to aggregate dispersed information. Formally, we show how to recover absolute and relative price informativeness in dynamic environments with rich heterogeneity across investors (regarding signals, private trading needs, or preferences), minimal distributional assumptions, multiple risky assets, and allowing for stationary and non-stationary asset payoffs. We implement our methodology empirically, finding stock-specific measures of price informativeness for U.S. stocks. We find a right-skewed distribution of price informativeness, measured in the form of the Kalman gain used by an external observer that conditions its posterior belief on the asset price. The recovered mean and median are 0.05 and 0.02 respectively. We find that price informativeness is higher for stocks with higher market capitalization and higher trading volume. Joint work with Eduardo Davila.

Lasse Pedersen: TBD

Marzena Rostek: Exchange Design and Efficiency

In many markets, traders' demands for an asset are contingent on the price of that asset alone rather than on the price of all assets they trade. We present a model based on the uniform-price double auction which accommodates arbitrary restrictions on cross-asset conditioning, including asset-by-asset market clearing (demand for each asset is conditioned on the price of that asset) and a single market clearing (demand for each asset is conditioned on the prices of all assets). If suitably designed, markets with limited demand conditioning are at least as efficient as a single market clearing for all traders and assets. Joint work with Ji Hee Yoon.

Mete Soner: Trading with Frictions

Frictions such as transaction costs and price impact have substantial impact on portfolio management. Indeed, proportional or fixed transaction costs slow down the trading frequency while price impact reduces the trading speed. Classical problems such as the Merton problem provide valuable insight to these influences and they have been studied in detail. However, most of the problems are highly nonlinear and computationally not very tractable. As the size of the frictions is not very large, asymptotic analysis has proven to be a powerful tool in this context. In this talk, I provide a survey of these techniques in understanding the impact of several different types of friction. In particular, I will outline the asymptotic results obtained in collaboration with Moreau and Muhle-Karbe for price impact and with Altarovici and Muhle-Karbe for transactions costs. I will connect these results to a stylized approach developed in collaboration with Bank and Voss. Joint work with Albert Altarovici, Peter Bank. Ludovic Moreau, Johannes Muhle-Karbe, and Moritz Voss.

Raman Uppal: The Geography of Beliefs

Empirical evidence shows that beliefs of households deviate from rational expectations and instead may be influenced by characteristics such as place of residence, culture, and socioeconomic status, which can be modeled using network theory. We develop a model where a household's beliefs about stock returns are an endogenous outcome of its location in a bipartite network of households and firms. We use this model to establish the relation between households' beliefs about stock returns, which are unobservable, and the portfolio weights allocated to these stocks by these households. We use Finnish data for 126 stocks and the portfolio holdings of 885,868 households to estimate our model and find that distance in the network has a statistically and economically significant effect on the beliefs of households. Our estimates show that agents are connected to firms within a radius of about 145 miles from where they live, and geography has a strong effect on beliefs: a one standard deviation decrease in an agent's distance to a firm's headquarters predicts an increase in portfolio holdings by 165%. Our work provides microfoundations for the bias toward local stocks documented empirically. Joint work with Harjoat Bhamra and Johan Walden.

Dimitri Vayanos: Asset Management Contracts and Equilibrium Prices

We derive equilibrium asset prices when fund managers deviate from benchmark indices to exploit noise-trader induced distortions but fund investors constrain these deviations. Because constraints force managers to buy assets that they underweight when these assets appreciate, overvalued assets have high volatility, and the risk-return relationship becomes inverted. Noise traders bias prices upward because constraints make it harder for managers to underweight overvalued assets, which have high volatility, than to overweight undervalued ones. We endogenize the constraints based on investors' uncertainty about managers' skill, and show that asset-pricing implications can be signicant even for moderate numbers of unskilled managers. Joint work with Andrea Buffa and Paul Woolley.