Price discovery in tick time

This paper develops a tick time model for the quote setting dynamics on Nasdaq. The model decomposes quotes into an efficient price, asymmetric information and noise. Both the evolution of the efficient price and the information contents of quotes depend on quote durations. New measures for the contribution to price discovery are defined within this model. When aggregated to fixed calendar time intervals, they relate closely to Hasbrouck [Hasbrouck, Joel, 1995, One security, many markets: determining the contribution to price discovery, Journal of Finance 50, 1175–1199] information shares. Empirical results for 20 Nasdaq stocks indicate that ECNs, in particular Island, contribute most to price discovery for active stocks. For less active stocks, wholesale market makers contribute most.     

期货市场与现货市场之间的价格研究--中国农产品市场的经验

本文借助于信息共享模型与波动溢出效应模型对我国大豆和小麦的期、现货市场之间的价格发现进行了多层次的实证研究,定量描述了期、现货市场在价格发现中作用的大小,深入刻画了我国农产品期、现货市场之间的动态关系.研究结果显示:大豆期、现货价格之间存在双向引导关系,小麦仅存在期货对现货的单向引导关系;期、现货市场均扮演着重要的价格发现角色,且期货市场在价格发现中处于主导地位;期、现货市场之间均存在双向波动溢出关系,但现货市场来自期货市场的波动溢出效应均强于期货市场来自现货市场的波动溢出效应;并且,随着期货市场的发展,期、现货市场之间的波动溢出程度均呈逐渐增强态势.     

A Proposed Model for Consumer-Based Brand Equity Analysis on Social Media Using Data Mining and Social Network Analysis

Online social networks have expanded their “virtual borders,” making the Internet more like an environment of social interaction than a business tool. However, even before the emergence and expansion of social media, marketing professionals were interested in identifying consumers' perceptions about brands. Thus, operational models have been proposed to facilitate such a task. Those models, however, can be expensive and inconvenient, since the models use questionnaires for data collection. To help overcome this problem, this article proposes a model for brand equity analysis from the consumer perspective expressed in social networks using opinion mining techniques and social network analysis. The application of the proposed model on data collected from Twitter made it possible to analyze five brand equity dimensions: brand awareness, brand loyalty, perceived sentiment, perceived quality, and brand associations. The results reached by the application of the model show that brand equity can be analyzed from data retrieved from virtual social networks, disclosing how consumers perceive brands in such an environment, without using questionnaires, enabling different brands in different contexts. Those data can be analyzed under both objective and replicable criteria for each of the brand equity elements that make up the model.     

Intraday market effects in electronic soybean futures market during non-trading and trading hour announcements

This article investigates market reactions to major United States Department of Agriculture announcements during non-trading and trading hours in the soybean futures market using microstructure data. Following report release, volume increases and remains elevated for up to 15 to 20 minutes. The volume spikes for the non-trading releases relative to the trading releases, but are identical after the first reaction. Report releases during non-trading hours cause a large spike in volatility at the onset of trading which subsides quickly. In contrast, releases during trading hours result in a smaller volatility spike, which extends for 5–6 min at a higher magnitude. Adjusting volatility by normal trading volatility indicates that volatility in trading hour release is higher in both immediate response and persistence. Return correlations provide little evidence to support systematic under- or overreaction in prices regardless of when the report is released reflecting the efficiency of the market.     

基于R&D指标的先导性战略新兴产业发现研究

在识别和选择先导性战略新兴产业的过程中,按照其未知、待发掘的特点,透过知识发现的视角,采用关联规则方法,根据R&D经费投入强度指标与专利授权量指标之间的强关联规则关系,建立先导性战略新兴产业数据挖掘关联规则识别模型。以中国长三角地区为实证分析对象,在对该地区的战略新兴产业进行识别时,得出5条符合约束条件的强关联规则,其对应的战略新兴产业的产业顺序分别为高端装备制造、生物医药、新材料、新一代信息技术及新能源等5个产业。     

Literature-related discovery (LRD): Lessons learned, and future research directions

Literature-related discovery (LRD) is the linking of two or more literature concepts that have heretofore not been linked (i.e., disjoint), in order to produce novel, interesting, plausible, and intelligible knowledge (i.e., potential discovery). The open discovery systems (ODS) component of LRD starts with a problem to be solved, and generates solutions to that problem through potential discovery. We have been using ODS LRD to identify potential treatments or preventative actions for challenging medical problems, among myriad other applications. The five immediately preceding papers in this Special Issue describe the application of ODS LRD to Raynaud's Phenomenon (RP), cataracts, Parkinson's Disease (PD), Multiple Sclerosis (MS), and Water Purification (WP). We describe the lessons learned from each application, and how the techniques can be improved further.Generation of much potential discovery using ODS LRD is possible when the conceptual roadblocks to discovery are removed. Some of these roadblocks include use of numerical filters that are unrelated to generating discovery, and excessive reliance on literatures directly related to the problem literature of interest. The issue of how to handle large amounts of potential discovery has not been addressed in the literature, since most ODS LRD researchers have tried to find a relatively few potential discovery items. We present a development strategy that capitalizes on the large amounts of potential discovery we have identified.     

基于EMD分解的螺纹钢期货价格发现的实证研究

运用经验模态分解方法(EMD),分别将螺纹钢期货价格和现货价格时间序列分解成若干IMF分量和趋势项。通过对分解后的不同分量进行统计和计量分析发现:①与期货价格与现货价格的相关性相比,相应的趋势项之间具有更高的相关关系;②期货价格的主IMF分量在形态上对现货价格主IMF分量具有引导作用;③IMF中期波动分量和长期波动能够很好的表现出期货价格和现货价格的因果关系。这些结果表明,螺纹钢期货市场已经基本具备了价格发现的功能。     

深化资本市场中枢作用研究

资本市场应当主导我国金融市场由资金配置向资本配置转型、由不动产金融向动产金融转型,同时主导我国生产要素市场化改革。资本市场在经济活动中发挥主导作用的关键在于提升其价值发现能力,而当前我国资本市场价值发现能力欠缺有多方面深层次原因:一是对资产和资金的包容和汇聚不够,二是资本的流动和配置受到制约,三是定价机制受到一定程度的扭曲,四是产权制度不完善,五是市场主体归位尽责情况不理想,六是金融衍生品市场不够成熟。本文建议:一是完善多层次资本市场建设,二是推动市场多空机制均衡发展,三是纠偏资本市场定价机制,四是加速完善现代产权制度,五是强化对市场各主体的培育,六是加强资本市场高质量对外开放。     

Price discovery in commodity derivatives: Speculation or hedging?

We investigate whether commodity futures or options markets play a more important role in the price discovery process in the six most actively traded markets: crude oil, natural gas, gold, silver, corn, and soybeans. Using new information leadership techniques, we report new evidence and report that both markets make a meaningful contribution to price discovery in recent times; however, on average, options lead futures in reflecting new information for a majority of these commodities. We find that increased speculation, rather than hedging activity, in commodity derivatives is a key determinant of price discovery in the options markets.     

Measuring price discovery between nearby and deferred contracts in storable and nonstorable commodity futures markets

Using price discovery measures, including Putniņš’ (2013) information leadership share and intraday data, we quantify the proportional contribution of nearby and deferred contracts in price discovery in the corn and live cattle futures markets. On average, nearby contracts reflect information more quickly than deferred contracts in the corn market, but have a relatively less dominant role in the live cattle market. In both markets, the nearby contract loses dominance when its relative volume share dips below 50%, which typically occurs when the nearby is close to maturity. Regression results indicate that the share of price discovery is mainly related to trading volume and time to expiration in both markets. In the corn market, price discovery share between nearby and deferred contracts is also related to inverse carrying charges, crop year differences, USDA announcements, market crashes, and commodity index position rolls. Differences between corn and live cattle markets are consistent with differences in the contracts’ liquidity and commodity storability.