A Dynamic Model of Characteristic-based Return Predictability
A Dynamic Model of Characteristic-based Return Predictability. Journal of Finance 74(6), 3187-3216
We present a dynamic model that links characteristic‐based return predictability to systematic factors that determine the evolution of firm fundamentals. In the model, an economy‐wide disruption process reallocates profits from existing businesses to new projects and thus generates a source of systematic risk for portfolios of firms sorted on value, profitability, and asset growth. If investors are overconfident about their ability to evaluate the disruption climate, these characteristic‐sorted portfolios exhibit persistent mispricing. The model generates predictions about the conditional predictability of characteristic‐sorted portfolio returns and illustrates how return persistence increases the likelihood of observing characteristic‐based anomalies.
A New Perspective on Post-earnings-announcement-drift: Using a Relative Drift Measure
A New Perspective on Post-earnings-announcement-drift: Using a Relative Drift Measure. Journal of Business Finance and Accounting 46(9/10), 1123-1143.
Prior research finds that there is a delayed reaction to both analyst‐based earnings surprises and random‐walk‐based earnings surprises. Focusing on the market reaction from the post‐announcement window, prior studies show that analyst‐based drift is larger than random walk‐based drift. This finding is counter‐intuitive if we believe large, sophisticated investors tend to trade on analysts’ forecast earnings news and thus react faster and more completely than smaller and less sophisticated investors react to random walk earnings news. In this study, we construct a relative measure of post‐earnings‐announcement drift (PEAD) (i.e., drift as a proportion of total market reaction to earnings news) which we refer to as the ‘drift ratio’, and we provide evidence, consistent with our intuition, that analyst‐based drift ratio is smaller (not greater) than random‐walk‐based drift ratio. We find that this difference is more pronounced in more recent periods and for firms with more sophisticated investors. Our approach to measure the PEAD is more intuitive than that in traditional PEAD literature. Our results thus complement existing research findings by utilizing the drift ratio measure to generate new insights about the drift phenomenon.
Adherence to Clinical Guidelines, Electronic Health Record Use, and Online Reviews
Adherence to Clinical Guidelines, Electronic Health Record Use, and Online Reviews. Journal of Management of Information Systems 36(4), 1071-1104.
To increase transparency of healthcare quality, the Centers for Medicare and Medicaid Services (CMS) initiated the Physician Quality Reporting System (PQRS). However, the impact of PQRS on physicians is unclear, particularly as related to their online reputation. Is there an association between a physician’s online reputation and her adherence to clinical guidelines stipulated in the PQRS? Is online reputation associated with use of electronic health records (EHR)? To investigate these questions, we combine data on online physician reviews with the PQRS data on clinical guideline adherence and EHR use. Unlike prior research, which primarily uses clinical outcomes as proxies for care quality, our study uses adherence to clinical guidelines, a process measure that reflects physician conformance with evidence-based clinical practices. In addition, we focus on EHR use at the physician level, in contrast to the usual approach of examining it at the aggregate institutional level. Consistent with the economic theory of credence goods, we observe no significant relationship between physicians’ adherence to clinical guidelines and their online reviews. Although there is some evidence of association between EHR use and their overall rating, similar relationships are not consistently observed for individual dimensional ratings. Overall, the online reputation of a physician exhibits minimal association with her actual clinical activities — and is mostly driven by latent topics in the textual reviews — implying that the ability of online reviews to inform prospective patients of care quality might be quite limited. Therefore, patients should be cautious when using online physician reviews, and policymakers should increase the accessibility of PQRS and other similar data to help patients make informed physician choices.
Agricultural Partnership for Dairy Farming
Agricultural Partnership for Dairy Farming. Production and Operations Management 28(12), 3042-3059.
This paper studies an innovative agricultural partnership model in the dairy industry. In developing regions, farmers are constrained by limited resources, while it is costly for an enterprise to set up new facilities and raise dairy animals all on its own. Under the partnership model, dairy animals are raised by individual farmers during the maturing stage and then by the enterprise during the milking stage. This can lower the enterprise’s investment cost, ensure milk quality, and also expand the farmers’ capacity given that a new batch can be raised when the old batch goes to the enterprise’s facilities. We find that from the enterprise’s perspective, the performance of this model depends on the farmers’ original capacity and capacity expansion ratio (i.e., how much it can expand under partnership). The profitability of the enterprise can either increase in the farmers’ original capacity if the expansion ratio is small or decreases otherwise. Compared with the conventional decentralized model and the independent integrated model, the partnership model is particularly preferred when the enterprise’s market size is intermediate. Several extensions of our model show that the government quality subsidy offered to the farmers may sometimes lower dairy product quality as well as the enterprise’s profit; when the enterprise aims to maximize the total profit of the partnership, it will contract with more farmers and produce more dairy products; and if the farmers have more bargaining power, the partnership model will benefit the farmers more but be less preferable to the enterprise.
An Additive Model of Decision Making Under Risk and Ambiguity
An Additive Model of Decision Making Under Risk and Ambiguity. Journal of Mathematical Economics 85, 78-92.
We extend the mean–variance (risk–value) tradeoff model to decision making under both risk and ambiguity. This model explicitly captures the tradeoff between the magnitude of risk and the magnitude of ambiguity. A measure that ranks lotteries in terms of the magnitude of ambiguity can also be obtained using this separation. By applying our model to asset pricing under ambiguity, we show that the equity premium can be decomposed into two parts: the risk premium and the ambiguity premium. Further, combining this model with the standard risk–value model, we build on the risk–ambiguity tradeoff to provide the value–risk–ambiguity preference model that does not rely on an approximation argument as the mean–variance model.