The effect of tick size on managerial learning from stock prices

We investigate the effect of tick size, a key feature of market microstructure, on managerial learning from stock prices. Using a randomized controlled tick-size experiment, the 2016 Tick Size Pilot Program, we find that a larger tick size increases a firm's investment sensitivity to stock prices, suggesting that managers glean more new information from stock prices to guide their investment decisions as the tick size increases. Consistently, we also find that changes in managerial beliefs, as reflected in adjustments of forecasted capital expenditures, respond more strongly to market feedback under a larger tick size. Additional evidence suggests the following mechanism through which tick size affects managerial learning: a larger tick size reduces algorithmic trading, in turn encouraging fundamental information acquisition. Increased fundamental information acquisition generates incremental information about growth opportunities, macroeconomic factors, and industry factors, with respect to which the market has a comparative information advantage over management.     

Forecasting macroeconomic risks

We construct risks around consensus forecasts of real GDP growth, unemployment, and inflation. We find that risks are time-varying, asymmetric, and partly predictable. Tight financial conditions forecast downside growth risk, upside unemployment risk, and increased uncertainty around the inflation forecast. Growth vulnerability arises as the conditional mean and conditional variance of GDP growth are negatively correlated: downside risks are driven by lower mean and higher variance when financial conditions tighten. Similarly, employment vulnerability arises as the conditional mean and conditional variance of unemployment are positively correlated, with tighter financial conditions corresponding to higher forecasted unemployment and higher variance around the consensus forecast.     

大连市沙河口区可持续发展的人口承载力预测

在充分认识大连市沙河口区人口承载力内涵的基础上,对大连市沙河口区2005-2020年人口承载力进行了综合分析,得到了可持续发展的人口承载力预测结果,该结果对于沙河口区人口政策的制定至关重要。     

人工智能归纳学习法在逆向物流发生因素及预测中的应用

企业从事逆向物流所面临的首要问题就是进行战略决策，在合理配置资源、保护环境的基础上实施逆向物流如何才能降低成本、获得可观的经济收益。本文在对逆向物流的概念及其发展现状分析基础上，探讨了信息论为基础的数据归纳分析方法，并结合制造业与逆向物流相关的数据来讨论企业实施逆向物流的因素分类及预测。     

Do analysts overreact to extreme good news in earnings?

We provide an alternative explanation for the previous finding of analysts’ overreaction to extreme good news in earnings. We show that such finding could be a result of analysts’ rational behavior in the face of high earnings uncertainty rather than their cognitive bias. Extreme earnings performance tends to be associated with higher earnings uncertainty that generally leads to more forecast optimism. Once this effect is accounted for, the univariate result of analysts’ overreaction to extreme good news in earnings is subsumed, leaving only their underreaction in general.

旅游市场分类研究及其意义——以佛山市为例

我们在佛山市旅游研究中使用了“市场分类研究法”和“产品-需求对应分析法”，对不同的旅游吸引物所对应的旅游市场进行分类调研和分类处理，发现景点旅游者市场与城市过夜旅游者市场存在着明显的差异。认识这些差异，对于分析区域旅游发展的主导旅游吸引，分析旅游需求趋势和需求预测，对确定区域旅游发展的主动力模型和旅游发层动力机制，制定产品战略和市场战略具有重要的意义。     

第四代技术展望

随着技术与经济全球化，技术预测的合理性，有效性和可操作性等问题再一次提到议事日程上来。本文提出了一种在广义技术创新框架之下，社会，经济，环境的多层次上，硬技术与软技术并重的第四代技术展望理论。     

Forecasting and mediation: Colorado and the clean air act

This paper presents an analysis of discussions designed to resolve technical differences, a process known as data mediation, between originators of divergent forecasts. Differing forecasts of future urban air quality by several agencies led to debate over revisions to the 1977 Clean Air Act proposed during the 97th Congress. Researchers for General Motors, the U.S. Environmental Protection Agency, and the State of Colorado disagreed over the ability of Denver, Colorado ever to attain the health standards for carbon monoxide if automobile emission for high altitude were relaxed. Data mediation led to resolution of some differences. The search for disconfirming evidence was a key element of the successful data mediation. In examining the process of that mediation, it was found that the search for disconfirming evidence requires: (1) balance of scientific expertise and credibility; (2) explicitness of assumptions; and (3) segmenting and bounding of the problem.     

论连锁店的分店补货模型

本文采用实证的方法,对连锁店分店的自动补货模型进行了分析,并研究其对降低连锁店分店库存水平的作用.首先,阐述了连锁店分店库存的重要性,分析了连锁店分店常用的补货模型;分析销量的预测方法：然后通过实证分析模拟人工智能的补货公式,如何实现连锁店分店的全自动补货功能.     

Density forecasting through disaggregation

In this paper, the revised expectations model (REM) is developed to incorporate economic agents’ price expectation formation effects. With this incorporation, two models, an aggregate one sector model and a disaggregated multi-sector model, are estimated and used in density forecasting of the US real GDP growth rate. The experiment shows that use of the disaggregated version of the model, which incorporates price expectation effects along with modern Bayesian MCMC estimation and prediction techniques, produces more precise density forecasts than those yielded by either an aggregate version or benchmark forecasting models.