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Valuation in Over-the-Counter Markets

Review of Financial Studies 2007 20(6), 1865-1900
[We provide the impact on asset prices of search-and-bargaining frictions in over-the-counter markets. Under certain conditions, illiquidity discounts are higher when counterparties are harder to find, when sellers have less bargaining power, when the fraction of qualified owners is smaller, or when risk aversion, volatility, or hedging demand is larger. Supply shocks cause prices to jump, and then "recover" over time, with a time signature that is exaggerated by search frictions: The price jump is larger and the recovery is slower in less liquid markets. We discuss a variety of empirical implications.]

Demand-Based Option Pricing

Review of Financial Studies 2009 22(10), 4259-4299
[We model demand-pressure effects on option prices. The model shows that demand pressure in one option contract increases its price by an amount proportional to the variance of the unhedgeable part of the option. Similarly, the demand pressure increases the price of any other option by an amount proportional to the covariance of the unhedgeable parts of the two options. Empirically, we identify aggregate positions of dealers and end-users using a unique dataset, and show that demand-pressure effects make a contribution to wellknown option-pricing puzzles. Indeed, time-series tests show that demand helps explain the overall expensiveness and skew patterns of index options, and cross-sectional tests show that demand impacts the expensiveness of single-stock options as well.]

Margin-based Asset Pricing and Deviations from the Law of One Price

Review of Financial Studies 2011 24(6), 1980-2022
In a model with heterogeneous-risk-aversion agents facing margin constraints, we show how securities' required returns increase in both their betas and their margin requirements. Negative shocks to fundamentals make margin constraints bind, lowering risk-free rates and raising Sharpe ratios of risky securities, especially for high-margin securities. Such a funding-liquidity crisis gives rise to “bases,” that is, price gaps between securities with identical cash-flows but different margins. In the time series, bases depend on the shadow cost of capital, which can be captured through the interest-rate spread between collateralized and uncollateralized loans and, in the cross-section, they depend on relative margins. We test the model empirically using the credit default swap–bond bases and other deviations from the Law of One Price, and use it to evaluate central banks' lending facilities.

Adverse Selection and the Required Return

Review of Financial Studies 2004 17(3), 643-665
An important feature of financial markets is that securities are traded repeatedly by asymmetrically informed investors. We study how current and future adverse selection affect the required return. We find that the bid-ask spread generated by adverse selection is not a cost, on average, for agents who trade, and hence the bid-ask spread does not directly influence the required return. Adverse selection contributes to trading-decision distortions, however, implying allocation costs, which affect the required return. We explicitly derive the effect of adverse selection on required returns, and show how our result differs from models that consider the bid-ask spread to be an exogenous cost.

Impediments to Financial Trade: Theory and Applications

Review of Financial Studies 2020 33(6), 2697-2727 open access
We propose a tractable model of an informationally inefficient market featuring nonrevealing prices, general preferences and payoff distributions, but not noise traders. We show the equivalence between our model and a substantially simpler one in which investors face distortionary investment taxes depending on both their identity and the asset class. This equivalence allows us to account for such phenomena as underdiversification. We further employ the model to assess approaches to performance evaluation and find that it provides a theoretical basis for some intuitive practices, such as style analysis, that have been adopted by finance professionals.

Liquidity and Risk Management

American Economic Review 2007 97(2), 193-197
This paper provides a model of the interaction between risk-management practices and market liquidity. On one hand, tighter risk management reduces the maximum position an institution can take, thus the amount of liquidity it can offer to the market. On the other hand, risk managers can take into account that lower liquidity amplifies the effective risk of a position by lengthening the time it takes to sell it. The main result of the paper is that a feedback effect can arise: tighter risk management reduces liquidity, which in turn leads to tighter risk management, etc. This can help explain sudden drops in liquidity and, since liquidity is priced, in prices in connection with increased volatility or decreased risk-bearing capacity.

Efficiently Inefficient Markets for Assets and Asset Management

Journal of Finance 2018 73(4), 1663-1712 open access
We consider a model where investors can invest directly or search for an asset manager, information about assets is costly, and managers charge an endogenous fee. The efficiency of asset prices is linked to the efficiency of the asset management market: if investors can find managers more easily, more money is allocated to active management, fees are lower, and asset prices are more efficient. Informed managers outperform after fees, uninformed managers underperform, while the average manager's performance depends on the number of “noise allocators.” Small investors should remain uninformed, but large and sophisticated investors benefit from searching for informed active managers since their search cost is low relative to capital. Hence, managers with larger and more sophisticated investors are expected to outperform.

Dynamic Trading with Predictable Returns and Transaction Costs

Journal of Finance 2013 68(6), 2309-2340 open access
We derive a closed‐form optimal dynamic portfolio policy when trading is costly and security returns are predictable by signals with different mean‐reversion speeds. The optimal strategy is characterized by two principles: (1) aim in front of the target, and (2) trade partially toward the current aim. Specifically, the optimal updated portfolio is a linear combination of the existing portfolio and an “aim portfolio,” which is a weighted average of the current Markowitz portfolio (the moving target) and the expected Markowitz portfolios on all future dates (where the target is moving). Intuitively, predictors with slower mean‐reversion (alpha decay) get more weight in the aim portfolio. We implement the optimal strategy for commodity futures and find superior net returns relative to more naive benchmarks.

Financial Entanglement: A Theory of Incomplete Integration, Leverage, Crashes, and Contagion

American Economic Review 2015 105(7), 1979-2010
We propose a unified model of limited market integration, asset-price determination, leveraging, and contagion. Investors and firms are located on a circle, and access to markets involves participation costs that increase with distance. Due to a complementarity between participation and leverage decisions, the equilibrium may exhibit diverse leverage and participation choices across investors, although investors are ex ante identical. Small changes in market-access costs can cause a change in the type of equilibrium, leading to discontinuous price changes, deleveraging, and portfolio-flow reversals. Moreover, the market is subject to contagion—an adverse shock to investors in some locations affects prices everywhere.

Technological Growth and Asset Pricing

Journal of Finance 2012 67(4), 1265-1292
We study the asset‐pricing implications of technological growth in a model with “small,” disembodied productivity shocks and “large,” infrequent technological innovations, which are embodied into new capital vintages. The technological‐adoption process leads to endogenous cycles in output and asset valuations. This process can help explain stylized asset‐valuation patterns around major technological innovations. More importantly, it can help provide a unified, investment‐based theory for numerous well‐documented facts related to excess‐return predictability. To illustrate the distinguishing features of our theory, we highlight novel implications pertaining to the joint time‐series properties of consumption and excess returns.