Information in stock prices: the case of the 2016 U.S. presidential election

On the day before the 2016 U.S. presidential election, the odds of Hillary Clinton winning the presidency, according to political prediction markets, were above 90%. Surprisingly, Donald Trump won the Electoral College handily. In this study, we examine how movements in specific stock prices foreshadowed the eventual outcome. Specifically, we conduct a series of standard event-study tests focused on pharmaceutical companies, which became a focal point during the presidential campaign. Results show that while stocks of pharmaceutical companies significantly underperformed the market prior to the election, prices substantially increased beginning three days before the election outcome. This increase is both statistically significant and economically meaningful and robust to various event-study methodologies. These results suggest that some sectors of the stock market seemed to anticipate the election outcome.     

Trade credit and supplier competition

This paper examines how competition among suppliers affects their willingness to provide trade credit financing. Trade credit extended by a supplier to a cash constrained retailer allows the latter to increase cash purchases from its other suppliers, leading to a free rider problem. A supplier that represents a smaller share of the retailer’s purchases internalizes a smaller part of the benefit from increased spending by the retailer and, as a result, extends less trade credit relative to its sales. In consequence, retailers with dispersed suppliers obtain less trade credit than those whose suppliers are more concentrated. The free rider problem is especially detrimental to a trade creditor when the free-riding suppliers are its product market competitors, leading to a negative relation between product substitutability among suppliers to a given retailer and trade credit that the former provide to the latter. We test the model using both simulated and real data. The estimated relations are consistent with the model’s predictions and are statistically and economically significant.     

HOW DO RATING AGENCIES’ DECISIONS IMPACT STOCK MARKETS? A META‐ANALYSIS

The purpose of this study is to examine how credit rating agencies’ decisions impact the stock market using a systematic and quantitative review of existing empirical studies. Specifically, we employ a meta‐regression analysis (MRA) to investigate the extent and nature of the effect of rating agencies’ decisions on the stock market. We survey 62 studies published between 1978 and 2015. Our first finding is that the cumulative average abnormal returns calculated from this empirical literature are affected by publication bias. After controlling for publication bias, the main findings of our meta‐analysis indicate that negative rating decisions cause statistically significant negative abnormal returns. This evidence suggests an informational effect. Our results also indicate that positive rating decisions do not have a significant effect. Finally, the MRA results reveal the importance of several factors related to primary study design, as well as to the nature of the data.     

Clustered airline flight scheduling: Evidence from airline deregulation in Korea

This paper explores the impacts of competition level on airline scheduling in the Korean domestic short-haul routes where a hub-and-spoke system is not the optimal air transport network strategy. The empirical findings using the Korean airline panel data for the period 2006–2010 suggest that competition leads to less differentiated departure flight times as expected from spatial competition theory. Unlike the previous study on the U.S airline industry, the degree of this tendency for less differentiation differs across the type of routes: the Jeju island routes (leisure type) and the inland routes (business type), in the deregulated period. Following the May 2008 Deregulation Act we find an increasingly clustered pattern of airline scheduling in the Jeju island routes where there have been competitive pressures associated with new low cost entrants. This recent evidence would imply that airline carriers strategically schedule departure flight times and allocate flights between routes as competition increases in the deregulated period.     

The impact of mandatory trans fat labeling on product mix and consumer choice: A longitudinal analysis of the U.S. Market for margarine and spreads

The impact of changes in food labeling policy on food consumption depends on how market participants—both firms and consumers—react to the changes across all products in the market. We investigate how both responded to the U.S. Food and Drug Administration’s 2006 rule mandating that the quantity of trans fat in food products be separately labeled on the mandatory Nutrition Facts Panel across an entire differentiated product category. Using a longitudinal data set tracking both product offerings and consumer purchases in the market for margarine and spreads for over a decade, we analyze how product mix and consumer purchase behaviors were influenced by the new regulatory requirement. We find that the number of products bearing voluntary “trans fat free” labels increased after the labeling regulation was implemented. However, a large number of the newly introduced products exited the market within five years. As a result, the FDA’s 2006 rule had a stronger short-run than long-run effect on product offerings. Even after the introduction of additional “trans fat free” labeled products, such products remained only a small percentage of margarine and spreads product offerings, increasing from a pre-regulation level of 2.3% of the market to a peak of 6.5% in 2007 before dropping to 3.1% by 2011. In addition to firm response, we examine demand-side reactions to the 2006 rule and find that consumers significantly increased their expenditures on “trans fat free” labeled products soon after the labeling changes were implemented, increasing from about 1.2% of the market in 2001 to a peak of 5.9% in 2007, before returning to 1.8% in 2011. We further explore variations in responses across different demographic characteristics. Although long-run effects are small, the market for “trans fat free” labeled margarine and spreads settled into a new equilibrium with a somewhat higher level of products in the market than prior to the 2006 rule taking effect and a somewhat higher share of expenditures in the category. Overall, our category-wide analysis of both firm and consumer behavior indicates that the effects of the labeling policy change were smaller in the longer run in this market than would be indicated by an analysis of only new product introductions in response to the policy change.     

A new approach to measuring riskiness in the equity market: Implications for the risk premium

We introduce a new approach to measuring riskiness in the equity market. We propose option implied and physical measures of riskiness and investigate their performance in predicting future market returns. The predictive regressions indicate a positive and significant relation between time-varying riskiness and expected market returns. The significantly positive link between aggregate riskiness and market risk premium remains intact after controlling for the S&P 500 index option implied volatility (VIX), aggregate idiosyncratic volatility, and a large set of macroeconomic variables. We also provide alternative explanations for the positive relation by showing that aggregate riskiness is higher during economic downturns characterized by high aggregate risk aversion and high expected returns.     

Integrated planning for product selection,shelf-space allocation,and replenishment decision with elasticity and positioning effects

As the retail industry is growing larger and more diversified, retailers' decisions about product selection, shelf-space-allocation, and replenishment become more important and challenging. This paper is to present a model for shelf-space allocation with product selection and replenishment decisions to maximize the retailer's profit. The model is based on a two-dimensional display space in which all shelves and products have widths and heights and includes factors that influence demand for each product, such as space and cross-space elasticities and positioning effects. The integrated model presented is mixed-integer non-linear programming (MINLP) because the demand function is non-convex. This research proposes two heuristic algorithms (tabu search and genetic) to solve the MINLP problem. The results show the effectiveness and efficiency of these algorithms by comparing the outputs to the MINLP optimal solution for small data sets and comparing the algorithm performances for large data sets. The solution methodologies expect to support a simultaneous decision-making process for retailers to maximize their revenue.     

Resurrecting the size effect: Evidence from a panel nonlinear cointegration model for the G7 stock markets

Firm size is known to be an important factor affecting stock returns. This study proposes a panel threshold cointegration model to investigate the impact of the size effect on stock returns for the panel of G7 countries: Canada, France, Germany, Italy, Japan, the U.K., and the U.S. over the period 1991:1–2012:12. The empirical analysis is based upon the nonlinear cointegration framework using the asymmetric ARDL cointegration methodology (Shin et al., 2011). This methodological approach permits a much richer degree of flexibility in the dynamic adjustment process toward equilibrium, than in the classical linear model. Our findings indicate the presence of asymmetric adjustment around a unique long-run equilibrium. In particular, the empirical analysis provides evidence of asymmetric effects between stock returns and the size effect, while controlling for the book-to-market ratio and the price-to-earnings ratio.     

技术创业型企业孵化资本投入的风险管控——来自多案例对比

待孵化的技术创业型企业同时具有概念性技术向差异化产品转化的高风险与产品异质性被认同后溢价评估的高收益特点，导致其投资者多处于隔岸观火却欲罢不能的的孵化投资矛盾中。对孵化资本实施有效的风险管控，成为吸引外部资本投入的关键。基于此，选择在可创概念选育与技术创业孵化领域探索出高成功率路径的概念证明中心、YCombinator和创新工场为研究案例，分析其在创业项目筛选、孵化资金运营等关键环节的风险管控方式，以期完善我国孵化资本管控理论、助力我国商业孵化器提高资金风险管控能力、促进外部资本投入。     

Are betting returns a useful measure of accuracy in (sports) forecasting?

In an economic context, forecasting models are judged in terms not only of accuracy, but also of profitability. The present paper analyses the counterintuitive relationship between accuracy and profitability in probabilistic (sports) forecasts in relation to betting markets. By making use of theoretical considerations, a simulation model, and real-world datasets from three different sports, we demonstrate the possibility of systematically or randomly generating positive betting returns in the absence of a superior model accuracy. The results have methodological implications for sports forecasting and other domains related to betting markets. Betting returns should not be treated as a valid measure of model accuracy, even though they can be regarded as an adequate measure of profitability. Hence, an improved predictive performance might be achieved by carefully considering the roles of both accuracy and profitability when designing models, or, more specifically, when assessing the in-sample fit of data and evaluating out-of-sample forecasting performances.