Information Flows across Markets: Evidence from China–Backed Stocks Dual–Listed in Hong Kong and New York

Using a bivariate generalized autoregressive conditional heteroskedasticity (GARCH) model, we examine patterns of information flows for China–backed stocks that are cross–listed on exchanges in Hong Kong and New York. Results analyzing the dual–listed stocks indicate significant mutual feedback of information between domestic (Hong Kong) and offshore (New York) markets in terms of pricing and volatility. Stocks listed on the domestic market appear to play a more significant role of information transmission in the pricing process, whereas stocks listed on the offshore market play a bigger role in volatility spillover.     

Common Stock Returns in Corporate Takeover Bids: The Case of Brokerage House Acquisitions

This paper examines the common stock returns of three groups of bidders that purchased brokerage houses. Only in the cases of horizontal mergers, one brokerage house purchasing another, are there abnormal returns associated with the purchase. Neither bank holding company bidders nor non-financial bidders gain significantly when purchasing a brokerage house. Bank holding company bidders face considerable regulatory delays, and these economic disturbances may eliminate their gains. Bank holding company expansion into these non-bank activities does not appear, at the time of announcement, to either hurt or benefit them; hence, this expansion does not appear to further the loss exposure of the Federal Deposit Insurance Corporation.     

Impacts of Declining U.S. Retail Beef Demand on Farm-Level Beef Prices and Production

A systems model was estimated to determine the effects of declining U.S. retail beef demand on farm-level beef prices and production. Retail beef demand declined by nearly 66% from 1976 to 1999. Results indicate autonomous shifts in retail demand significantly impacted farm-level demands and production. Based on equilibrium multipliers, the 1976–99 reduction in beef demand decreased real slaughter cattle prices and production by 32.1% and 11.2%, respectively. Real feeder cattle prices and production decreased by 8.0% and 22.6%, respectively. Combining the decreases in farm prices and production, slaughter and feeder cattle producers experienced a real revenue reduction of $13.3 billion (61%) due to the long-term decline in demand.     

The impact of skewness in the hedging decision

The impact of skewness in the hedger's objective function is tested using a model of hedging derived from a third‐order Taylor Series approximation of expected utility. To determine the effect of price skewness upon hedging and speculation, analytical results are derived using an example of cotton storage. Findings suggest that when forward risk premiums and price skewness in the spot asset have opposite signs, speculation increases relative to the mean‐variance model. When the signs are identical, speculation will decrease, contradicting findings of mean‐variance models. © 2006 Wiley Periodicals, Inc. Jrl Fut Mark 26:503–520, 2006     

A review and validation of overall survival extrapolation in health technology assessments of cancer immunotherapy by the National Institute for Health and Care Excellence: how did the initial best estimate compare to trial data subsequently made available?

Background: Validation of overall survival (OS) extrapolations of immune-checkpoint inhibitors (ICIs) during the National Institute for Health and Care Excellence (NICE) Single Technology Assessment (STA) process is limited due to data still maturing at the time of submission. Inaccurate extrapolation may lead to inappropriate decision-making. The availability of more mature trial data facilitates a retrospective analysis of the plausibility and validity of initial extrapolations. This study compares these extrapolations to subsequently available longer-term data.

Methods: A systematic search of completed NICE appraisals of ICIs from March 2000 to December 2017 was performed. A targeted search was also undertaken to procure published OS data from the pivotal clinical trials for each identified STA made available post-submission to NICE. Initial Kaplan-Meier curves and associated extrapolations from NICE documentation were extracted to compare the accuracy of OS projections versus the most mature data.

Results: The review identified 11 STAs, of which 10 provided OS data upon submission to NICE. The extrapolations undertaken considered parametric or piecewise survival models. Additional data cut-offs provided a mean of 18 months of OS beyond the end of the original data. Initial extrapolations typically under-estimated OS from the most mature data cut-off by 0.4–2.7%, depending on the choice of assessment method and use of the manufacturer- or ERG-preferred extrapolation.

Conclusion: Long-term extrapolation of OS is required for NICE STAs based on initial immature OS data. The results of this study demonstrate that the initial OS extrapolations employed by manufacturers and ERGs generally predicted OS reasonably well when compared to more mature data (when available), although on average they appeared to underestimate OS. This review and validation shows that, while the choice of OS extrapolation is uncertain, the methods adopted are generally aligned with later-published follow-up data and appear appropriate for informing HTA decisions.     

Content analysis of fake consumer reviews by survey-based text categorization

As the influence of online consumer reviews grows, deceptive reviews are a worsening problem, betraying consumers' trust in reviews by pretending to be authentic and informative. This research identifies factors that can separate deceptive reviews from genuine ones. First, we create a novel means of detection by contrasting authentic versus fake word patterns specific to a given domain (e.g., hotel services). We use a survey on a crowdsourcing platform to obtain both genuine and deceptive reviews of hotels. We learned the word patterns from each category to discriminate genuine reviews from fake ones for positively and negatively evaluated reviews, respectively. We show that our All Terms procedure outperforms current benchmark methods in computational linguistics and marketing. Our extended analysis reveals the factors that determine fake reviews (e.g., a lack of details, present- and future-time orientation, and emotional exaggeration) and the factors influencing people's willingness to write fake reviews (including social media trust, product quality consciousness, deal proneness, hedonic and utilitarian consumption, prosocial behavior, and individualism). We also use our procedure to analyze more than 250,000 real-world hotel reviews to detect fake reviews and identify the hotel and review characteristics influencing review fakery in the industry (e.g., star rating, franchise hotel, hotel size, room price, review timing, and review rating).